DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the porosity data in line 10. There is insufficient antecedent basis for this element of the claim. Prior to claiming this element, the claim includes well log data representing porosity measurements. It is unclear if the porosity data in line 10 is referring to the well log data representing porosity measurements or the porosity measurements themselves. For purposes of this examination, the claim is being read as determining, from the well log data representing porosity measurements, facies probability functions for the plurality of wells in lines 10-11.
Claim 1 further recites the facies proportions of the subset of wells in lines 14-15. This element lacks proper antecedent basis. Prior to claiming this element, the claim includes facies proportions associated with the subset of wells in lines 8-9. The element claimed in lines 14-15 appears to imply the same element in lines 8-9; however it is not explicitly clear that facies proportions associated with the subset of wells is exactly the same as the facies proportions of the subset of wells. For purposes of this examination, the claim is being read as the facies proportions associated with the subset of wells in lines 14-15.
Claims 8 and 15 mirror the limitations described in Claim 1 and are rejected under the same rationale. The dependent claims 2-7, 9-14, and 16-20 of respective independent claims 1, 8, and 15 incorporate the deficiencies of their associated independent claim and are likewise rejected for the same rationale.
Claim 5 recites in the facies data of the well log data which lacks proper antecedent basis. In Claim 1, from which Claim 5 depends, facies data is described in line 6 and well log data is described in lines 3 and 4. However, facies data is not described as being part of the well log data.
Claims 12 and 19 mirror the deficiency cited in claim 5 and are rejected under the same rationale.
Claim 17 contains grammatical errors or omissions that render the claim unclear as to what is particularly being claimed. The scope of the claim cannot be assumed and therefore the claim is indefinite. Specifically, it is unclear how the term region contributes to the claim in line 5, prior to based on the control signal. Furthermore, it appears that the applicant is intending to claim that the controlling of the drilling of a well occurs at the determined location in the subsurface region. However, the claim could alternatively be interpreted to entail drilling a well at a location different that the determined location because the claim recites the location in a subsurface. For purposes of this examination, the claim is being interpreted to mean:
“generating a control signal based on the determined location in the subsurface region; and
based on the control signal, controlling drilling of a well at the determined location in the subsurface region.”
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The following section follows the 2019 Patent Eligibility Guidance (PEG) for analyzing subject matter eligibility:
Step 1 - Statutory Category:
Step 1 of the PEG analysis entails considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101 (process, machine, manufacture, or composition of matter).
Step 2A Prong One - Judicial exception:
In Step 2A Prong 1, examiners evaluate whether the claim recites a judicial exception (an abstract idea, law of nature, or a natural phenomenon).
Step 2A Prong Two - Integration into a practical application:
If claims recite a judicial exception, the claim requires further analysis in Step 2A Prong 2. In Step 2A Prong 2, examiners evaluate whether the claim as a whole integrates the exception into a practical application. This evaluation considers any additional elements in the claim beyond any recited judicial exceptions.
Step 2B - Significantly More:
If the additional elements identified in Step 2A Prong 2 do not integrate the exception into a practical application, then the claim is directed to the recited judicial exception and requires further analysis under Step 2B- Significantly More. This evaluation is to evaluate if the additional elements of the claim provide an inventive concept.
As noted in the MPEP 2106.05(II): The identification of the additional element(s) in the claim from Step 2A Prong 2, as well as the conclusions from Step 2A Prong 2 on the considerations discussed in MPEP 2106.05(a) -(c), (e), (f), and (h) are to be carried over. Claim limitations identified as Insignificant Extra-Solution Activities are re-evaluated to determine if the elements are beyond what is well -understood, routine, and conventional (WURC) activity, as dictated by MPEP 2106.05(II).
The additional elements are evaluated to determine if any additional element or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP § 2106.05(d).
Examiner notes limitations identified as judicial exceptions are indicated in italicized bold and limitations identified as additional elements are indicated using italics.
Claim 1
Step 1: Claim 1 and its dependent claims 2-7 are directed to a method which falls within one of the four statutory categories of a process.
Step 2A Prong 1: Claim 1 recites a judicial exception:
determining, from the facies data, facies proportions associated with the subset of wells; The claim limitation can be reasonably read to entail making evaluations of facies data to derive judgements of facies proportions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
determining, from the porosity data, facies probability functions for the plurality of wells; The claim limitation can be reasonably read to entail making evaluations of porosity data to derive judgements of facies probability functions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. Furthermore, because the claim recites the generation of a mathematical formula (probability function), the claim further includes the abstract idea of mathematical concepts.
determining, based on the facies probability functions, facies proportions at the plurality of wells; The claim limitation can be reasonably read to entail making evaluations of facies probability functions to derive judgements of facies proportions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. Furthermore, because the claim further recites the utilization of probability functions to derive proportions (understood as a ratio describing the part to whole value), the limitation further recites the mathematical relationships and therefore further includes the abstract idea of mathematical concepts.
updating the facies proportions at the plurality of wells using the facies proportions of the subset of wells; The claim limitation can be reasonably read to entail making a judgement as to the facies proportions according to evaluation of facies proportions of the subset of wells. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
based on the updated facies proportions at the plurality of wells, generating a three-dimensional (3D) facies trend model for the subsurface region at each of the wells of the plurality; and The claim limitation can be reasonably read to entail evaluating the updated facies proportions to further make a judgement as to a 3D facies trend model. This task may be performed using the human mind or using assistive aids such as pen and paper because the mechanism by which the model is generated is not beyond human capacity. For example, a human being using assistive aids may assign a trend value at every specific grid node or cell of a model wherein such may be done using grid paper or a table with rows and columns corresponding to the specified values at the locations. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
generating, based on the 3D facies trend model, extended facies data for one or more wells of the plurality of wells that are not in the subset of wells that are associated with facies data. The claim limitation can be reasonably read to entail evaluating the 3D facies trend model to further derive judgments of extended facies data. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Therefore, the claim recites a judicial exception.
Step 2A Prong 2: Additional elements were identified and are noted in italics.
receiving, from a plurality of wells of a reservoir, well log data measured by sensors in each of the wells of the plurality of wells, the well log data representing porosity measurements of the subsurface region at each of the wells of the plurality, wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells;- This limitation has been identified as Insignificant Extra-Solution Activity (MPEP 2106.05(g)) of mere data gathering.
The courts have found that adding insignificant extra- solution activity to the judicial exception (Insignificant Extra Solution Activity (MPEP 2106.05(g))) does not integrate the judicial exception into a practical application.
When viewed independently and within the claim as a whole, the additional element does not appear to integrate the judicial exception into a practical application. The claim appears to be performing a series of steps which can be practically performed in the human mind using received well log data as specified in the claim. However, there is no apparent improvement to technology or a technical field reflected by the claim, no application of the judicial exception by any specific or particular machine or claimed mechanism of applying the judicial exception in a meaningful capacity.
Step 2B: As discussed in Step 2A Prong 2, additional elements were identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) which must be further evaluated to determine if they are beyond WURC activities. Additional elements identified otherwise and conclusions from Step 2A Prong 2 are carried over for evaluating if the claim, as a whole, amounts to an inventive concept that is significantly more than the judicial exception:
receiving, from a plurality of wells of a reservoir, well log data measured by sensors in each of the wells of the plurality of wells, the well log data representing porosity measurements of the subsurface region at each of the wells of the plurality, wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells; – This limitation has been identified as the insignificant extra solution activity of mere data gathering, as stated previously. Under broadest reasonable interpretation and when read in light of the specification, receiving well log data encompasses the transmission and receiving of data over a network. Such a computer function has been found by the courts as well understood, routine, and conventional activity when claimed in a merely generic manner such as in the claims (See MPEP 2106.05(d)(II)(i)).
The courts have found that simply appending insignificant extra solution activities that are well-understood, routine, and conventional activities to the judicial exception does not qualify the limitations as “significantly more” than the recited judicial exception. Furthermore, when evaluating the ordered combination, the means by which the received data is used in the mental process is not claimed in such a way as to present an inventive concept or significantly more than the exception.
With the additional element viewed independently and as part of the ordered combination, the claim as a whole does not appear to amount to significantly more than the recited judicial exception because the claim is using well-understood, routine, and conventional activity to enable the performance of a task that can practically be performed within the human mind or using pen and paper as an assistive physical aid. Therefore, the claim does not include additional elements, alone or in combination that are sufficient to amount to significantly more than the recited judicial exception.
Conclusion: Based on this rationale, the claim has been deemed to be ineligible subject matter under 35 U.S.C. 101.
Claim 2
Step 1: Regarding dependent claim 2, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 2 additionally recites the limitation determining, based on the extended facies data, reservoir volumetrics data for the subsurface region; and which can reasonably be read to entail evaluating the extended facies data to make a judgement about reservoir volumetrics data. The claim further recites the limitation determining, based on the reservoir volumetrics data, a location in the subsurface region that includes hydrocarbon deposits which can reasonably be read to entail evaluating the volumetrics data to make a judgement of a location. These tasks may be performed using the human mind and therefore these claim limitations include the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2 & Step 2B: Claim 2 does not recite any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 3
Step 1: Regarding dependent claim 3, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 3 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 3 additionally recites the limitation drilling, at the location in the subsurface region, a well.. This limitation has been identified as Mere Instructions To Apply An Exception (MPEP 2106.05(f)) for the generic recitation of “apply it” with regard to a value obtained as part of the mental process. The courts have ruled merely reciting “apply it” or a generic equivalent to the exception does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application because the claim does not reflect an improvement to technology or another field, nor does the claim particularly limit the embodiments to the drilling occurring by way of an inventive machine. There is on apparent application of use of the judicial exception in a meaningful way beyond linking it to the technological environment of drilling applications.
Step 2B: The courts have found that limitations that amount to reciting “apply it” or an equivalent to the judicial exception are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception. When viewed individually and as a whole, the claimed limitation generically recites the effect of a judicial exception while claiming every mode of accomplishing that effect. Specifically, the way drilling occurs or considers the location data is not claimed in an inventive manner that would demonstrate an inventive concept.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 4
Step 1: Regarding dependent claim 4, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 4 additionally recites the generating an areal trend map; and, which can reasonably be read to entail make a judgment of an areal trend map. Such judgement may be expressed on paper using physical assistive aids. Further the claim recites generating, based on the areal trend map, the 3D facies trend model. which may entail evaluating the areal trend map to derive judgments of the 3D facies trend model. Likewise, the creation of the trend model may be done by way of assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2: Claim 4 additionally recites the limitation receiving geological maps data;. This limitation has been identified as Insignificant Extra-Solution Activity (MPEP 2106.05(g)) of mere data gathering. The courts have ruled that appending insignificant extra solution activity to the judicial exception does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: Under broadest reasonable interpretation and when read in light of the specification, receiving map data encompasses receiving data over a network. This has been found by the courts to be a computer function that is well understood, routine, and conventional when claimed in a merely generic manner. The courts have found that limitations that amount to adding insignificant extra solution activity, which is well understood, routine, and conventional are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 5
Step 1: Regarding dependent claim 5, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 5 additionally recites the limitation detecting, in the facies data of the well log data, vertical trends in facies in the subsurface region; which may entail making observations and judgements according to the facies data of the well log data. Further, the claim recites generating vertical proportion curves from the vertical trends in the facies data; and which may entail evaluating the vertical trends to make a judgement as to vertical proportion curves and subsequently expressing them using pen and paper as assistive aids. Lastly, the claim recites the limitation generating, based on the vertical proportion curves, the 3D facies trend model. which can reasonably be read to entail evaluating the vertical proportion curves and using the information to derive judgements characterizing the 3D facies trend model, which may be expressed using assistive aids such as pen and paper. These tasks may be performed using the human mind or using assistive aids as described herein. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2 & Step 2B: Claim 5 does not recite any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 6
Step 1: Regarding dependent claim 6, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 6 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 6 additionally recites the limitation wherein the extended facies data represent facies that are present at each of the plurality of wells. This limitation has been identified as Field of Use and Technological Environment (MPEP 2106.05(h)) because the limitation amounts to describing a data association to the field of use. The courts have ruled generally linking the judicial exception to a particular technological environment and field of use does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to generally linking the use of the judicial exception to a particular technological environment and field of use are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 7
Step 1: Regarding dependent claim 7, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 7 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 7 additionally recites the limitation wherein the subset of wells include cored wells from which facies data are directly measured.. This limitation has been identified as Field of Use and Technological Environment (MPEP 2106.05(h)). The courts have ruled generally linking the use of the judicial exception to a particular technological environment does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to generally linking the judicial exception to a particular technological environment or field of use are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 8
Step 1: Claim 8 and its dependent claims 9-14 are directed to a system which falls within one of the four statutory categories of a machine.
Step 2A Prong 1: Claim 8 recites a judicial exception:
determining, from the facies data, facies proportions associated with the subset of wells; The claim limitation can be reasonably read to entail making evaluations of facies data to derive judgements of facies proportions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
determining, from the porosity data, facies probability functions for the plurality of wells; The claim limitation can be reasonably read to entail making evaluations of porosity data to derive judgements of facies probability functions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. Furthermore, because the claim recites the generation of a mathematical formula (probability function), the claim further includes the abstract idea of mathematical concepts.
determining, based on the facies probability functions, facies proportions at the plurality of wells; The claim limitation can be reasonably read to entail making evaluations of facies probability functions to derive judgements of facies proportions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. Furthermore, because the claim further recites the utilization of probability functions to derive proportions (understood as a ratio describing the part to whole value), the limitation further recites the mathematical relationships and therefore further includes the abstract idea of mathematical concepts.
updating the facies proportions at the plurality of wells using the facies proportions of the subset of wells; The claim limitation can be reasonably read to entail making a judgement as to the facies proportions according to evaluation of facies proportions of the subset of wells. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
based on the updated facies proportions at the plurality of wells, generating a three-dimensional (3D) facies trend model for the subsurface region at each of the wells of the plurality; and The claim limitation can be reasonably read to entail evaluating the updated facies proportions to further make a judgement as to a 3D facies trend model. This task may be performed using the human mind or using assistive aids such as pen and paper because the mechanism by which the model is generated is not beyond human capacity. For example, a human being using assistive aids may assign a trend value at every specific grid node or cell of a model wherein such may be done using grid paper or a table with rows and columns corresponding to the specified values at the locations. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
generating, based on the 3D facies trend model, extended facies data for one or more wells of the plurality of wells that are not in the subset of wells that are associated with facies data. The claim limitation can be reasonably read to entail evaluating the 3D facies trend model to further derive judgments of extended facies data. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Therefore, the claim recites a judicial exception.
Step 2A Prong 2: Additional elements were identified and are noted in italics.
at least one processor; and - This limitation has been identified as Mere Instructions To Apply An Exception (MPEP 2106.05(f)) for invoking generic computing components as a tool by which to apply the exception
memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: - This limitation has been identified as Mere Instructions To Apply An Exception (MPEP 2106.05(f)) for invoking generic computing components as a tool by which to apply the exception
receiving, from sensors in each of a plurality of wells in a reservoir, well log data measured by sensors in each of the wells of the plurality of wells, the well log data representing porosity measurements of the subsurface region at each of the wells of the plurality, wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells;- This limitation has been identified as Insignificant Extra-Solution Activity (MPEP 2106.05(g)) of mere data gathering.
The courts have found that including mere instructions to apply the judicial exception using generic computing components (Mere Instructions To Apply An Exception (MPEP 2106.05(f))) and adding insignificant extra- solution activity to the judicial exception (Insignificant Extra Solution Activity (MPEP 2106.05(g))) does not integrate the judicial exception into a practical application.
When viewed independently and within the claim as a whole, the additional element does not appear to integrate the judicial exception into a practical application. The claim appears to be performing a series of steps which can be practically performed in the human mind using received well log data as specified in the claim and implementing the mental process steps by way of generic computers. However, there is no apparent improvement to technology or a technical field reflected by the claim, no application of the judicial exception by any specific or particular machine or claimed mechanism of applying the judicial exception in a meaningful capacity.
Step 2B: As discussed in Step 2A Prong 2, additional elements were identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) which must be further evaluated to determine if they are beyond WURC activities. Additional elements identified otherwise and conclusions from Step 2A Prong 2 are carried over for evaluating if the claim, as a whole, amounts to an inventive concept that is significantly more than the judicial exception:
receiving, from a plurality of wells of a reservoir, well log data measured by sensors in each of the wells of the plurality of wells, the well log data representing porosity measurements of the subsurface region at each of the wells of the plurality, wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells; – This limitation has been identified as the insignificant extra solution activity of mere data gathering, as stated previously. Under broadest reasonable interpretation and when read in light of the specification, receiving well log data encompasses the transmission and receiving of data over a network. Such a computer function has been found by the courts as well understood, routine, and conventional activity when claimed in a merely generic manner such as in the claims (See MPEP 2106.05(d)(II)(i)).
The courts have found that simply appending insignificant extra solution activities that are well-understood, routine, and conventional activities to the judicial exception does not qualify the limitations as “significantly more” than the recited judicial exception. Furthermore, when evaluating the ordered combination, the means by which the received data is used in the mental process is not claimed in such a way as to present an inventive concept or significantly more than the exception. Furthermore, the courts have found that including mere instructions to apply the judicial exception in a computing environment are not enough to qualify the claim as significantly more than the exception.
With the additional element viewed independently and as part of the ordered combination, the claim as a whole does not appear to amount to significantly more than the recited judicial exception because the claim is using well-understood, routine, and conventional activity and generic computers to enable the performance of a task that can practically be performed within the human mind or using pen and paper as an assistive physical aid. Therefore, the claim does not include additional elements, alone or in combination that are sufficient to amount to significantly more than the recited judicial exception.
Conclusion: Based on this rationale, the claim has been deemed to be ineligible subject matter under 35 U.S.C. 101.
Claim 9
Step 1: Regarding dependent claim 9, the judicial exception of independent claim 8 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 9 additionally recites the limitation determining, based on the extended facies data, reservoir volumetrics data for the subsurface region; and, which can reasonably be read to entail evaluating the extended facies data to make a judgement about reservoir volumetrics data. The claim further recites the limitation determining, based on the reservoir volumetrics data, a location in the subsurface region that includes hydrocarbon deposits which can reasonably be read to entail evaluating the volumetrics data to make a judgement of a location. These tasks may be performed using the human mind and therefore these claim limitations include the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2 & Step 2B: Claim 9 does not recite any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 10
Step 1: Regarding dependent claim 10, the judicial exception of independent claim 8 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 10 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 10 additionally recites the limitation drilling, at the location in the subsurface region, a well using the drill.. This limitation has been identified as Mere Instructions To Apply An Exception (MPEP 2106.05(f)) for the generic recitation of “apply it” with regard to a value obtained as part of the mental process. The courts have ruled merely reciting “apply it” or a generic equivalent to the exception does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application because the claim does not reflect an improvement to technology or another field, nor does the claim particularly limit the embodiments to the drilling occurring by way of an inventive machine. There is on apparent application of use of the judicial exception in a meaningful way beyond linking it to the technological environment of drilling applications.
Step 2B: The courts have found that limitations that amount to reciting “apply it” or an equivalent to the judicial exception are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception. When viewed individually and as a whole, the claimed limitation generically recites the effect of a judicial exception while claiming every mode of accomplishing that effect. Specifically, the way drilling occurs or considers the location data is not claimed in an inventive manner that would demonstrate an inventive concept.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 11
Step 1: Regarding dependent claim 11, the judicial exception of independent claim 8 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 11 additionally recites the generating an areal trend map; and, which can reasonably be read to entail make a judgment of an areal trend map. Such judgement may be expressed on paper using physical assistive aids. Further the claim recites generating, based on the areal trend map, the 3D facies trend model. which may entail evaluating the areal trend map to derive judgments of the 3D facies trend model. Likewise, the creation of the trend model may be done by way of assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2: Claim 11 additionally recites the limitation receiving geological maps data;. This limitation has been identified as Insignificant Extra-Solution Activity (MPEP 2106.05(g)) of mere data gathering. The courts have ruled that appending insignificant extra solution activity to the judicial exception does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: Under broadest reasonable interpretation and when read in light of the specification, receiving map data encompasses receiving data over a network. This has been found by the courts to be a computer function that is well understood, routine, and conventional when claimed in a merely generic manner. The courts have found that limitations that amount to adding insignificant extra solution activity, which is well understood, routine, and conventional are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 12
Step 1: Regarding dependent claim 12, the judicial exception of independent claim 8 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 12 additionally recites the limitation detecting, in the facies data of the well log data, vertical trends in facies in the subsurface region; which may entail making observations and judgements according to the facies data of the well log data. Further, the claim recites generating vertical proportion curves from the vertical trends in the facies data; and which may entail evaluating the vertical trends to make a judgement as to vertical proportion curves and subsequently expressing them using pen and paper as assistive aids. Lastly, the claim recites the limitation generating, based on the vertical proportion curves, the 3D facies trend model. which can reasonably be read to entail evaluating the vertical proportion curves and using the information to derive judgements characterizing the 3D facies trend model, which may be expressed using assistive aids such as pen and paper. These tasks may be performed using the human mind or using assistive aids as described herein. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2 & Step 2B: Claim 12 does not recite any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 13
Step 1: Regarding dependent claim 13, the judicial exception of independent claim 8 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 13 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 13 additionally recites the limitation wherein the extended facies data represent facies that are present at each of the plurality of wells. This limitation has been identified as Field of Use and Technological Environment (MPEP 2106.05(h)) because the limitation amounts to describing a data association to the field of use. The courts have ruled generally linking the judicial exception to a particular technological environment and field of use does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to generally linking the use of the judicial exception to a particular technological environment and field of use are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 14
Step 1: Regarding dependent claim 14, the judicial exception of independent claim 8 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 14 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 14 additionally recites the limitation wherein the subset of wells include cored wells from which facies data are directly measured.. This limitation has been identified as Field of Use and Technological Environment (MPEP 2106.05(h)). The courts have ruled generally linking the use of the judicial exception to a particular technological environment does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to generally linking the judicial exception to a particular technological environment or field of use are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 15
Step 1: Claim 15 and its dependent claims 16-20 are directed to a non-transitory computer readable media which falls within one of the four statutory categories of a manufacture.
Step 2A Prong 1: Claim 15 recites a judicial exception:
determining, from the facies data, facies proportions associated with the subset of wells; The claim limitation can be reasonably read to entail making evaluations of facies data to derive judgements of facies proportions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
determining, from the porosity data, facies probability functions for the plurality of wells; The claim limitation can be reasonably read to entail making evaluations of porosity data to derive judgements of facies probability functions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. Furthermore, because the claim recites the generation of a mathematical formula (probability function), the claim further includes the abstract idea of mathematical concepts.
determining, based on the facies probability functions, facies proportions at the plurality of wells; The claim limitation can be reasonably read to entail making evaluations of facies probability functions to derive judgements of facies proportions. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. Furthermore, because the claim further recites the utilization of probability functions to derive proportions (understood as a ratio describing the part to whole value), the limitation further recites the mathematical relationships and therefore further includes the abstract idea of mathematical concepts.
updating the facies proportions at the plurality of wells using the facies proportions of the subset of wells; The claim limitation can be reasonably read to entail making a judgement as to the facies proportions according to evaluation of facies proportions of the subset of wells. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
based on the updated facies proportions at the plurality of wells, generating a three-dimensional (3D) facies trend model for the subsurface region at each of the wells of the plurality; and The claim limitation can be reasonably read to entail evaluating the updated facies proportions to further make a judgement as to a 3D facies trend model. This task may be performed using the human mind or using assistive aids such as pen and paper because the mechanism by which the model is generated is not beyond human capacity. For example, a human being using assistive aids may assign a trend value at every specific grid node or cell of a model wherein such may be done using grid paper or a table with rows and columns corresponding to the specified values at the locations. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
generating, based on the 3D facies trend model, extended facies data for one or more wells of the plurality of wells that are not in the subset of wells that are associated with facies data. The claim limitation can be reasonably read to entail evaluating the 3D facies trend model to further derive judgments of extended facies data. This task may be performed using the human mind or using assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Therefore, the claim recites a judicial exception.
Step 2A Prong 2: Additional elements were identified and are noted in italics.
receiving, from sensors in each of a plurality of wells, well log data measured by sensors in each of the wells of the plurality of wells, the well log data representing porosity measurements of a subsurface region at each of the wells of the plurality, wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells;- This limitation has been identified as Insignificant Extra-Solution Activity (MPEP 2106.05(g)) of mere data gathering.
The courts have found that adding insignificant extra- solution activity to the judicial exception (Insignificant Extra Solution Activity (MPEP 2106.05(g))) does not integrate the judicial exception into a practical application.
When viewed independently and within the claim as a whole, the additional element does not appear to integrate the judicial exception into a practical application. The claim appears to be performing a series of steps which can be practically performed in the human mind using received well log data as specified in the claim. However, there is no apparent improvement to technology or a technical field reflected by the claim, no application of the judicial exception by any specific or particular machine or claimed mechanism of applying the judicial exception in a meaningful capacity.
Step 2B: As discussed in Step 2A Prong 2, additional elements were identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) which must be further evaluated to determine if they are beyond WURC activities. Additional elements identified otherwise and conclusions from Step 2A Prong 2 are carried over for evaluating if the claim, as a whole, amounts to an inventive concept that is significantly more than the judicial exception:
receiving, from a plurality of wells of a reservoir, well log data measured by sensors in each of the wells of the plurality of wells, the well log data representing porosity measurements of the subsurface region at each of the wells of the plurality, wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells; – This limitation has been identified as the insignificant extra solution activity of mere data gathering, as stated previously. Under broadest reasonable interpretation and when read in light of the specification, receiving well log data encompasses the transmission and receiving of data over a network. Such a computer function has been found by the courts as well understood, routine, and conventional activity when claimed in a merely generic manner such as in the claims (See MPEP 2106.05(d)(II)(i)).
The courts have found that simply appending insignificant extra solution activities that are well-understood, routine, and conventional activities to the judicial exception does not qualify the limitations as “significantly more” than the recited judicial exception. Furthermore, when evaluating the ordered combination, the means by which the received data is used in the mental process is not claimed in such a way as to present an inventive concept or significantly more than the exception.
With the additional element viewed independently and as part of the ordered combination, the claim as a whole does not appear to amount to significantly more than the recited judicial exception because the claim is using well-understood, routine, and conventional activity to enable the performance of a task that can practically be performed within the human mind or using pen and paper as an assistive physical aid. Therefore, the claim does not include additional elements, alone or in combination that are sufficient to amount to significantly more than the recited judicial exception.
Conclusion: Based on this rationale, the claim has been deemed to be ineligible subject matter under 35 U.S.C. 101.
Claim 16
Step 1: Regarding dependent claim 16, the judicial exception of independent claim 15 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 16 additionally recites the limitation determining, based on the extended facies data, reservoir volumetrics data for the subsurface region; and, which can reasonably be read to entail evaluating the extended facies data to make a judgement about reservoir volumetrics data. The claim further recites the limitation determining, based on the reservoir volumetrics data, a location in the subsurface region that includes hydrocarbon deposits which can reasonably be read to entail evaluating the volumetrics data to make a judgement of a location. These tasks may be performed using the human mind and therefore these claim limitations include the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2 & Step 2B: Claim 16 does not recite any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 17
Step 1: Regarding dependent claim 17, the judicial exception of independent claim 15 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 17 additionally recites generating a control signal based on the determined location in the subsurface region; and which, except for the recitation of generic computing components in the preamble of the claim, is a process that can be performed using the human mind and assistive aids. For example, a human being can evaluate the determined location in the subsurface region and make a judgement as to tell drilling personnel to start, stop, or otherwise modify a drilling operation. The derived control signal may be expressed using pen and paper as an assistive aid as a medium by which to relay said instruction. Though the claim states this process is performed as being an operation on a computer-readable media, the courts do not distinguish between mental processes performed entirely in the human mind or those performed in a computing environment or using other assistive aids. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2: Claim 17 additionally recites the limitation generating a control signal based on the determined location in the subsurface region; and Though the claim lacks clarity, when read in light of the specification and in light of the similar claims, this limitation has been identified as Mere Instructions To Apply An Exception (MPEP 2106.05(f)) for the generic recitation of “apply it” with regard to a value obtained as part of the mental process. The courts have ruled merely reciting “apply it” or a generic equivalent to the exception does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application because the claim does not reflect an improvement to technology or another field, nor does the claim particularly limit the embodiments to the drilling occurring by way of an inventive machine. There is on apparent application of use of the judicial exception in a meaningful way beyond linking it to the technological environment of drilling applications.
Step 2B: The courts have found that limitations that amount to reciting “apply it” or an equivalent to the judicial exception are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception. When viewed individually and as a whole, the claimed limitation generically recites the effect of a judicial exception while claiming every mode of accomplishing that effect. Specifically, the way drilling occurs or considers the location data is not claimed in an inventive manner that would demonstrate an inventive concept.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 18
Step 1: Regarding dependent claim 18, the judicial exception of independent claim 15 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 18 additionally recites the generating an areal trend map; and, which can reasonably be read to entail make a judgment of an areal trend map. Such judgement may be expressed on paper using physical assistive aids. Further the claim recites generating, based on the areal trend map, the 3D facies trend model. which may entail evaluating the areal trend map to derive judgments of the 3D facies trend model. Likewise, the creation of the trend model may be done by way of assistive aids such as pen and paper. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2: Claim 18 additionally recites the limitation receiving geological maps data;. This limitation has been identified as Insignificant Extra-Solution Activity (MPEP 2106.05(g)) of mere data gathering. The courts have ruled that appending insignificant extra solution activity to the judicial exception does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: Under broadest reasonable interpretation and when read in light of the specification, receiving map data encompasses receiving data over a network. This has been found by the courts to be a computer function that is well understood, routine, and conventional when claimed in a merely generic manner. The courts have found that limitations that amount to adding insignificant extra solution activity which is well understood, routine, and conventional are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 19
Step 1: Regarding dependent claim 19, the judicial exception of independent claim 15 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 19 additionally recites the limitation detecting, in the facies data of the well log data, vertical trends in facies in the subsurface region; which may entail making observations and judgements according to the facies data of the well log data. Further, the claim recites generating vertical proportion curves from the vertical trends in the facies data; and which may entail evaluating the vertical trends to make a judgement as to vertical proportion curves and subsequently expressing them using pen and paper as assistive aids. Lastly, the claim recites the limitation generating, based on the vertical proportion curves, the 3D facies trend model. which can reasonably be read to entail evaluating the vertical proportion curves and using the information to derive judgements characterizing the 3D facies trend model, which may be expressed using assistive aids such as pen and paper. These tasks may be performed using the human mind or using assistive aids as described herein. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2 & Step 2B: Claim 19 does not recite any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 20
Step 1: Regarding dependent claim 20, the judicial exception of independent claim 15 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 6 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 20 additionally recites the limitation wherein the extended facies data represent facies that are present at each of the plurality of wells. This limitation has been identified as Field of Use and Technological Environment (MPEP 2106.05(h)) because the limitation amounts to describing a data association to the field of use. The courts have ruled generally linking the judicial exception to a particular technological environment and field of use does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to generally linking the use of the judicial exception to a particular technological environment and field of use are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2, 4-6, 8-9, 11-13, 15-16, and 18-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhang et al (US Patent No. US 8,838,425 B2), hereinafter referred to as Zhang.
Regarding claim 1, Zhang teaches A method for porosity-assisted facies modeling for extracting hydrocarbons from a subsurface region, the method comprising: ((Zhang, Abstract) "A method for generating one or more geological models for oil field exploration."); ((Zhang, Claim 1) "A method for generating one or more geological models for oil field exploration, comprising:")
receiving, from a plurality of wells of a reservoir, well log data ((Zhang, Col. 5, Lines 47-51) "At step 210, the computer application may receive well facies data from well facies logs. Well facies logs may be well logs that have been acquired at various locations in a survey area such as boreholes and the like, as described above with reference to FIG.1.") measured by sensors in each of the wells of the plurality of wells ((Zhang, Col. 14 , Lines 6-9 & 13-16) "The system computer 630 may be in communication with the logging device described in FIG. 1 (either directly or via a recording unit, not shown), to receive signals indicating the measurements on the earth formations.[[…]] In one implementation, these signals and data may be sent to the system computer 630 directly from sensors, such as well logs and the like."), the well log data representing porosity measurements of the subsurface region at each of the wells of the plurality, ((Zhang, Col 5, Lines 2-30) "The logging device 100 may represent any type of logging device that takes measurements from which formation characteristics can be determined, for example, by solving complex inverse problems. The logging device 100 may be an electrical type of logging device (including devices such as resistivity, induction, and electromagnetic propagation devices), a nuclear logging device, a sonic logging device, or a fluid sampling logging device, or combinations thereof. Various devices may be combined in a tool string and/or used during separate logging runs. Also, measurements may be taken during drilling and/or tripping and/or sliding. Examples of the types of formation characteristics that can be determined using these types of devices include: determination, from deep three-dimensional electromagnetic measurements, of distance and direction to faults or deposits, such as salt domes or hydrocarbons; determination, from acoustic shear and/or compressional wave speeds and/or wave attenuations, of formation porosity, permeability, and/or lithology; determination of formation anisotropy from electromagnetic and/or acoustic measurements; determination, from attenuation and frequency of a rod or plate vibrating in a fluid, of formation fluid viscosity and/or density; determination, from resistivity and/or nuclear magnetic resonance (NMR) measurements, of formation water saturation and/or permeability; determination, from count rates of gamma rays and/or neutrons at spaced detectors, of formation porosity and/or density; and determination, from electromagnetic, acoustic and/or nuclear measurements, of formation bed thickness") wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells; ((Zhang, Col. 5, Lines 31-34) "In one implementation, the measurements obtained by logging device 100 may include well facies data in the well logs (facies logs). Facies logs may indicate the absolute presence or absence of a targeted facies at different spatial locations."); ((Zhang, Col5, Lines 47-51) "At step 210, the computer application may receive well facies data from well facies logs. Well facies logs may be well logs that have been acquired at various locations in a survey area such as boreholes and the like, as described above with reference to FIG.1. Well facies logs may indicate the absolute presence or absence of a targeted facies at different spatial locations.")
determining, from the facies data, facies proportions associated with the subset of wells; ((Zhang, Col 4, Lines 5-7) "Generally, the vertical facies proportion curve and the lateral proportion may be determined based on well facies data in well facies logs.")
determining, from the porosity data, facies probability functions for the plurality of wells; A facies probability cube is generated using well log data, wherein the probability cube is characterized by probability functions indicating the likelihood of the variable of interest at the specified pixels ((Zhang, Col. 8, Lines 33-63) "At step 260, the computer application may generate a facies probability cube using a modified Sequential Gaussian Simulation (SGS IM) algorithm. The conventional Sequential Gaussian Simulation (SGSIM) algorithm, as described in Deutsch, C. V. and Joumel, A. G., 1998, GSLIB: Geostatistical Software Library and User's Guide. Oxford University Press, New York, p. 369 (Deutsch and Journel, 1998), is a popular geostatistical algorithm that is used to simulate a petrophsyical properties distribution of any continuous variable, such as porosity or permeability in a model (i.e., facies probability cube). It is a pixel-based sequential simulation where r is the gamma function. The expected value, second moment and variance of a Beta random variable X with parameters a and ~ are: approach under a multi-Gaussian assumption. The SGSIM algorithm first transforms well log data into standard normal values using a process called normal score transformation. The well log data is transferred into standard normal values for practical purposes because the continuous variables may not follow a Gaussian distribution. FIG. 12 illustrates an example of a Cumulative Density Function (CDF) curve in the original probability space and a CDF curve in the normal score space. The algorithm then proceeds by selecting a random pixel (or voxel in 3D) in a model. Because of the multi-Gaussian assumption, the SGS IM algorithm may make a determination of a conditional cumulative density function ( ccdf) at the selected pixel to determine the probability of the existence of a continuous variable at the selected pixel location. In order to make the determination of the conditional cumulative density function ( ccdf) at the selected pixel, the SGSIM algorithm solves a local kriging system to obtain an estimated kriging mean and variance based on well data obtained from well logs that are within the neighborhood of the selected pixel in the model.").
determining, based on the facies probability functions, facies proportions at the plurality of wells; Facies proportions are determined using the SGSIM algorithm while building the facies probability cube ((Zhang, Col. 9, Lines 36-50) " However, in order to constrain the facies probability cube to the vertical proportion curve, the modified SGS IM algorithm may increase or decrease the kriging mean msk * according to the difference between a running facies proportion and a target facies proportion at the Z-layer at selected pixel. (Step 540). The running facies proportion is defined as the simulated facies proportion before the simulation reaches the selected pixel, and the target facies proportion is the proportion value of the target facies at the selected pixel as indicated from the vertical proportion curve. In order to calculate the running proportion, the computer application may perform a back transformation of the simulated pixels from the normal score values into the original probability space.")
updating the facies proportions at the plurality of wells using the facies proportions of the subset of wells; The facies probability cube is generated considering facies data and associated proportion curves. ((Zhang, Col 4, Lines 5-7) "Generally, the vertical facies proportion curve and the lateral proportion may be determined based on well facies data in well facies logs.") ((Zhang, Col. 6, Lines 9-54) "In one implementation, VPC can be calculated from well facies logs (from step 210) interpretation, geological conceptual models or analogs similar to the reservoir under study. If well facies data are available, the well facies data may be combined with geological interpretations of the seismic area to generated interpreted well facies data. The interpreted well facies data may then be used as anchors in generating facies probability cubes, i.e. they indicate the absolute presences/ absences of the targeted facies at different spatial locations: probability is 1 for its presence and O for its absence. The vertical facies proportion curve can be calculated by extracting the facies proportion along each vertical layer (i.e., Z-layer) of a modeling grid. In case of very sparse wells, the calculated proportion curve may not be reliable and hence, its modification and editing may be performed based on geological interpretations or analogs similar to the studied reservoir. At step 230, the computer application may receive a lateral facies proportion map (LPM). FIG. 8 illustrates an example of a LPM. FIG. 15 illustrates how the LPM 1520 may be used in method 200. The lateral proportion map may be a 2 dimensional map in the XY plane that represents the variation of lateral proportions of certain facies in terms of an average proportion along the Z direction. In this manner, the lateral proportion map may illustrate lateral trends such as progradation or transition. In one implementation, the computer application may obtain the lateral facies proportion map by interpolating facies proportion from each well facies log or by calibrating seismic interpretations of each well facies log. The information included in the lateral facies proportion map may be useful when facies depositions have apparent lateral trends, such as progradation or a transition as observed from received seismic data, well facies log interpretations or conceptual models. The computer application may create lateral proportion maps based on well facies data using any smooth interpolator, such as a kriging technique in 2-point geostatistics or moving averaging algorithms. For instance, at each well location, the computer application may calculate a facies proportion. The facies proportion value may then be considered to be one of the hard data used as an anchor point to control the smooth interpolator. In one implementation, the computer application may also add interpreted trends into the LPM by adding data from "pseudo" wells. In any case, by integrating LPM into reservoir modeling, the computer application may be able to generate a facies probability cube that has more realistic results")
based on the updated facies proportions at the plurality of wells, generating a three-dimensional (3D) facies trend model for the subsurface region at each of the wells of the plurality; and ((Zhang, Col 10, Lines 65-67) "FIG. 10 illustrates an example of a fluvial sand probability cube generated using method 200.") See also Figure 2 depicting method 200 comprising the step of updating proportions, as given above. The fluvial sand probability cube is generated using a vertical proportions curve and lateral proportion map, which are described as indicating trends of the facies ((Zhang, Col 10, Line 67- Col 11, Lines 1-2) "FIG. 15 illustrates how the fluvial sand probability cube 1530 may have been generated using the VPC 1510 and the LPM 1520 as described in method 200."); ((Zhang, Col 5, Lines 66-67 and Col 6, Lines 1-8) "As such, the amount of specific facies deposits changes with the variation of geological times or depths leading to a systematic vertical trend of facies proportions. For example, in a fluvial-dominated deltaic environment, the sand deposit may be high at the bottom of a reservoir unit, become lower in the middle of the reservoir unit and becomes high again at the top of the reservoir unit. Coarsening or fining upwards characteristics in geological deposition for a certain facies is also a trend indicator of the deposition of that facies.")
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generating, based on the 3D facies trend model, extended facies data for one or more wells of the plurality of wells that are not in the subset of wells that are associated with facies data. A singular facies probability cube model may be extended to a multiple facies model ((Zhang ,Col 11, Lines 19-29) "Method 200 generates a facies probability cube by targeting one facies at a time. As a result, the probability cubes 20 reflect the spatial variation of the likelihood of the selected facies. In reservoir modeling, however, there are often more than two facies present within the earth. Users rarely build multiple facies probability cubes for each facies at one time due to the difficulty of making each facies probability cube 25 consistent with each other. To overcome this difficulty, method 3 00 and method 400, described below, may be used to create a multiple facies model based on the facies probability cube generated by method 200."). The probability cube is suggested as being useful for enabling characterization where well data is scarce, wherein well log data includes facies logs ((Zhang, Col 2, Lines 28-30) "In particular, facies probability cubes can assist in geological modeling or reservoir characterization when well data is scarce."); ((Zhang, Col 5, Lines 31-33) "In one implementation, the measurements obtained by logging device 100 may include well facies data in the well logs (facies logs).")
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Regarding claim 2, Zhang teaches The method of claim 1, further comprising: as stated previously and further teaches
determining, based on the extended facies data, reservoir volumetrics data for the subsurface region; and The multiple facies (extended facies data) are considered per-voxel (volumetrics data) in creating the multiple facies model according to the algorithm ((Zhang, Col 9, Lines 27-35) " The modified SGSIM algorithm may then select a random pixel ( or voxel in 3D) in a model of the facies probability cube. (Step 520). Next, in the simulation stage, the modified SGSIM algorithm may solve a local kriging system at the selected pixel to determine a kriging mean msk * and a kriging variance a2 sk based on well data obtained from well logs that are within the neighborhood of the selected pixel in the model. (Step 530)."); ((Zhang, Col 12, Lines) " At step 430, the computer application may hierarchically draw each individual facies at each simulated pixel in the binary facies probability cube. In one implementation, in order to hierarchically draw each individual facies, the computer application may use user-defined proportions for each facies of the multi-facies model. Using the defined proportions, the binary facies probability cube of step 410 and the training image of step 420, at step 440, the computer application may generate the multi-facies model using the multipoint statistics algorithm, described in Conditional Simulation of Complex Geological Structures Using Multiple Point Statistics. Mathematical Geology, v. 34, p. 1-22 (Strebelle, 2002). In one implementation, method 400 may be more practical when there are distinct and clear facies associations in the training image. By generating the multi-facies model using the multi-point statistics algorithm, the computer application may generate the multi-facies model once without using a hierarchical refining process as described in method 300. [[…]] As such, method 400 may recursively draw facies at each simulated pixel/voxel during the sequential simulation by the following rules:"); ((Zhang, Col 2, Lines 9-10) " MPS uses ID, 2D or 3D "training images" as quantitative templates to model subsurface property fields.")
determining, based on the reservoir volumetrics data, a location in the subsurface region that includes hydrocarbon deposits. ((Zhang,Col 2, Lines 19-21) "The resulting geological or reservoir models can then be used for oil field explorations by identifying hydrocarbon deposits in the Earth."); ((Zhang, Col 11, Lines 47-53) " For instance, if the facies probability cube received at step 310 represented locations where sand exists in the survey area, at step 320, the computer application may recursively evaluate the locations 50 where sand exists in the received facies probability cube such that the sand locations will be categorized into a different facies such as levees, crevasse or background.")
Regarding claim 4, Zhang teaches The method of claim 1, further comprising: and further teaches
receiving geological maps data; Geological data that corresponds to spatial locations (map data) is obtained as logging device measurements ((Zhang, Col 5, Lines 31-34) "In one implementation, the measurements obtained by logging device 100 may include well facies data in the well logs (facies logs). Facies logs may indicate the absolute presence or absence of a targeted facies at different spatial locations")
generating an areal trend map; and ((Zhang, Col 6, Lines 28-41) "The lateral proportion map may be a 2 dimensional map in the XY plane that represents the variation of lateral proportions of certain facies in terms of an average proportion along the Z direction. In this manner, the lateral proportion map may illustrate lateral trends such as progradation or transition. In one implementation, the computer application may obtain the lateral facies proportion map by interpolating facies proportion from each well facies log or by calibrating seismic interpretations of each well facies log. The information included in the lateral facies proportion map may be useful when facies depositions have apparent lateral trends, such as progradation or a transition as observed from received seismic data, well facies log interpretations or conceptual models.")
generating, based on the areal trend map, the 3D facies trend model. ((Zhang, Col, 10, Line 67- Col 11, Lines 1-2) "FIG. 15 illustrates how the fluvial sand probability cube 1530 may have been generated using the VPC 1510 and the LPM 1520 as described in method 200.")
Regarding claim 5, Zhang teaches The method of claim 1, further comprising: and further teaches
detecting, in the facies data of the well log data, vertical trends in facies in the
subsurface region; ((Zhang, Col 5, Lines 47-53) "At step 210, the computer application may receive well facies data from well facies logs. Well facies logs may be well logs that have been acquired at various locations in a survey area such as boreholes and the like, as described above with reference to FIG.1. Well facies logs may indicate the absolute presence or absence of a targeted facies at different spatial locations. ")
generating vertical proportion curves from the vertical trends in the facies data;
and ((Zhang, Col 4, Lines 5-7) "Generally, the vertical facies proportion curve and the lateral proportion may be determined based on well facies data in well facies logs."); ((Zhang, Col 6, Lines 9-21) "In one implementation, VPC can be calculated from well facies logs (from step 210) interpretation, geological conceptual models or analogs similar to the reservoir under study. If well facies data are available, the well facies data may be combined with geological interpretations of the seismic area to generated interpreted well facies data. The interpreted well
facies data may then be used as anchors in generating facies probability cubes, i.e. they indicate the absolute presences/ absences of the targeted facies at different spatial locations: probability is 1 for its presence and O for its absence. The vertical facies proportion curve can be calculated by extracting the facies proportion along each vertical layer (i.e., Z-layer) of a modeling grid. ")
generating, based on the vertical proportion curves, the 3D facies trend model. ((Zhang, Col 10, Line 67- Col 11, Lines 1-2) "FIG. 15 illustrates how the fluvial sand probability cube 1530 may have been generated using the VPC 1510 and the LPM 1520 as described in method 200.")
Regarding claim 6, Zhang teaches the method of claim 1, as stated previously and further teaches wherein the extended facies data represent facies that are present at each of the plurality of wells. ((Zhang, Col 11, Lines 38-53) " At step 320, after receiving the binary facies probability cube, the computer application may hierarchically generate an additional binary facies probability cube. As such, the 40 computer application may recursively generate an additional dimensions or facies on the binary facies cube received at step 310. In this manner, the computer application may repeat method 200 using the received binary facies probability cube. However, when repeating method 200, the computer application may generate a quaternary facies probability cube to indicate the presence of an additional facies. For instance, if the facies probability cube received at step 310 represented locations where sand exists in the survey area, at step 320, the computer application may recursively evaluate the locations where sand exists in the received facies probability cube such that the sand locations will be categorized into a different facies such as levees, crevasse or background."); ((Zhang, Col 12, Lines 1-5) "At step 340, the computer application may generate a multiple facies model based on each individual facies probability cube. FIG. 14 illustrates an example of a multiple-facies model. FIG.15 illustrates how the multi-facies model 1540 is generated."); ((Zhang, Col 11, Lines 22-29) "In reservoir modeling, however, there are often more than two facies present within the earth. Users rarely build multiple facies probability cubes for each facies at one time due to the difficulty of making each facies probability cube 25 consistent with each other. To overcome this difficulty, method 3 00 and method 400, described below, may be used to create a multiple facies model based on the facies probability cube generated by method 200").
Regarding claim 8, Zhang teaches A system for extracting hydrocarbons from a subsurface region, the system comprising: ((Zhang, Col 4, Lines 50-55) " FIG. 1 illustrates a schematic diagram of a logging apparatus in accordance with implementations of various techniques described herein. FIG. 1 shows a borehole 32 that has been drilled in formations 31 with drilling equipment, and typically, using drilling fluid or mud that results in a mudcake represented at 35.")
at least one processor; and ((Zhang, Col 17, Lines 6-7) " 17. A system, comprising: a processor; and")
a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: ((Zhang, Col 17, Lines 6-9) " 17. A system, comprising: a processor; and a memory comprising program instructions executable by the processor to:")
receiving, from sensors in each of a plurality of wells of a reservoir, well log data measured by sensors in each of the wells of the plurality of wells, ((Zhang, Col. 5, Lines 47-51) "At step 210, the computer application may receive well facies data from well facies logs. Well facies logs may be well logs that have been acquired at various locations in a survey area such as boreholes and the like, as described above with reference to FIG.1."); ((Zhang, Col. 14 , Lines 6-9 & 13-16) "The system computer 630 may be in communication with the logging device described in FIG. 1 (either directly or via a recording unit, not shown), to receive signals indicating the measurements on the earth formations.[[…]] In one implementation, these signals and data may be sent to the system computer 630 directly from sensors, such as well logs and the like."), the well log data representing porosity measurements of the subsurface region at each of the wells of the plurality, , ((Zhang, Col 5, Lines 2-30) "The logging device 100 may represent any type of logging device that takes measurements from which formation characteristics can be determined, for example, by solving complex inverse problems. The logging device 100 may be an electrical type of logging device (including devices such as resistivity, induction, and electromagnetic propagation devices), a nuclear logging device, a sonic logging device, or a fluid sampling logging device, or combinations thereof. Various devices may be combined in a tool string and/or used during separate logging runs. Also, measurements may be taken during drilling and/or tripping and/or sliding. Examples of the types of formation characteristics that can be determined using these types of devices include: determination, from deep three-dimensional electromagnetic measurements, of distance and direction to faults or deposits, such as salt domes or hydrocarbons; determination, from acoustic shear and/or compressional wave speeds and/or wave attenuations, of formation porosity, permeability, and/or lithology; determination of formation anisotropy from electromagnetic and/or acoustic measurements; determination, from attenuation and frequency of a rod or plate vibrating in a fluid, of formation fluid viscosity and/or density; determination, from resistivity and/or nuclear magnetic resonance (NMR) measurements, of formation water saturation and/or permeability; determination, from count rates of gamma rays and/or neutrons at spaced detectors, of formation porosity and/or density; and determination, from electromagnetic, acoustic and/or nuclear measurements, of formation bed thickness") wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells; ((Zhang, Col. 5, Lines 31-34) "In one implementation, the measurements obtained by logging device 100 may include well facies data in the well logs (facies logs). Facies logs may indicate the absolute presence or absence of a targeted facies at different spatial locations."); ((Zhang, Col5, Lines 47-51) "At step 210, the computer application may receive well facies data from well facies logs. Well facies logs may be well logs that have been acquired at various locations in a survey area such as boreholes and the like, as described above with reference to FIG.1. Well facies logs may indicate the absolute presence or absence of a targeted facies at different spatial locations.")
determining, from the facies data, facies proportions associated with the subset of wells; ((Zhang, Col 4, Lines 5-7) "Generally, the vertical facies proportion curve and the lateral proportion may be determined based on well facies data in well facies logs.")
determining, from the porosity data, facies probability functions for the plurality of wells; A facies probability cube is generated using well log data, wherein the probability cube is characterized by probability functions indicating the likelihood of the variable of interest at the specified pixels ((Zhang, Col. 8, Lines 33-63) "At step 260, the computer application may generate a facies probability cube using a modified Sequential Gaussian Simulation (SGS IM) algorithm. The conventional Sequential Gaussian Simulation (SGSIM) algorithm, as described in Deutsch, C. V. and Joumel, A. G., 1998, GSLIB: Geostatistical Software Library and User's Guide. Oxford University Press, New York, p. 369 (Deutsch and Journel, 1998), is a popular geostatistical algorithm that is used to simulate a petrophsyical properties distribution of any continuous variable, such as porosity or permeability in a model (i.e., facies probability cube). It is a pixel-based sequential simulation where r is the gamma function. The expected value, second moment and variance of a Beta random variable X with parameters a and ~ are: approach under a multi-Gaussian assumption. The SGSIM algorithm first transforms well log data into standard normal values using a process called normal score transformation. The well log data is transferred into standard normal values for practical purposes because the continuous variables may not follow a Gaussian distribution. FIG. 12 illustrates an example of a Cumulative Density Function (CDF) curve in the original probability space and a CDF curve in the normal score space. The algorithm then proceeds by selecting a random pixel (or voxel in 3D) in a model. Because of the multi-Gaussian assumption, the SGS IM algorithm may make a determination of a conditional cumulative density function ( ccdf) at the selected pixel to determine the probability of the existence of a continuous variable at the selected pixel location. In order to make the determination of the conditional cumulative density function ( ccdf) at the selected pixel, the SGSIM algorithm solves a local kriging system to obtain an estimated kriging mean and variance based on well data obtained from well logs that are within the neighborhood of the selected pixel in the model.").
determining, based on the facies probability functions, facies proportions at the plurality of wells; Facies proportions are determined using the SGSIM algorithm while building the facies probability cube ((Zhang, Col. 9, Lines 36-50) " However, in order to constrain the facies probability cube to the vertical proportion curve, the modified SGS IM algorithm may increase or decrease the kriging mean msk * according to the difference between a running facies proportion and a target facies proportion at the Z-layer at selected pixel. (Step 540). The running facies proportion is defined as the simulated facies proportion before the simulation reaches the selected pixel, and the target facies proportion is the proportion value of the target facies at the selected pixel as indicated from the vertical proportion curve. In order to calculate the running proportion, the computer application may perform a back transformation of the simulated pixels from the normal score values into the original probability space.")
updating the facies proportions at the plurality of wells using the facies proportions of the subset of wells; The facies probability cube is generated considering facies data and associated proportion curves. ((Zhang, Col 4, Lines 5-7) "Generally, the vertical facies proportion curve and the lateral proportion may be determined based on well facies data in well facies logs.") ((Zhang, Col. 6, Lines 9-54) "In one implementation, VPC can be calculated from well facies logs (from step 210) interpretation, geological conceptual models or analogs similar to the reservoir under study. If well facies data are available, the well facies data may be combined with geological interpretations of the seismic area to generated interpreted well facies data. The interpreted well facies data may then be used as anchors in generating facies probability cubes, i.e. they indicate the absolute presences/ absences of the targeted facies at different spatial locations: probability is 1 for its presence and O for its absence. The vertical facies proportion curve can be calculated by extracting the facies proportion along each vertical layer (i.e., Z-layer) of a modeling grid. In case of very sparse wells, the calculated proportion curve may not be reliable and hence, its modification and editing may be performed based on geological interpretations or analogs similar to the studied reservoir. At step 230, the computer application may receive a lateral facies proportion map (LPM). FIG. 8 illustrates an example of a LPM. FIG. 15 illustrates how the LPM 1520 may be used in method 200. The lateral proportion map may be a 2 dimensional map in the XY plane that represents the variation of lateral proportions of certain facies in terms of an average proportion along the Z direction. In this manner, the lateral proportion map may illustrate lateral trends such as progradation or transition. In one implementation, the computer application may obtain the lateral facies proportion map by interpolating facies proportion from each well facies log or by calibrating seismic interpretations of each well facies log. The information included in the lateral facies proportion map may be useful when facies depositions have apparent lateral trends, such as progradation or a transition as observed from received seismic data, well facies log interpretations or conceptual models. The computer application may create lateral proportion maps based on well facies data using any smooth interpolator, such as a kriging technique in 2-point geostatistics or moving averaging algorithms. For instance, at each well location, the computer application may calculate a facies proportion. The facies proportion value may then be considered to be one of the hard data used as an anchor point to control the smooth interpolator. In one implementation, the computer application may also add interpreted trends into the LPM by adding data from "pseudo" wells. In any case, by integrating LPM into reservoir modeling, the computer application may be able to generate a facies probability cube that has more realistic results")
based on the updated facies proportions at the plurality of wells, generating a three-dimensional (3D) facies trend model for the subsurface region at each of the wells of the plurality; and ((Zhang, Col 10, Lines 65-67) "FIG. 10 illustrates an example of a fluvial sand probability cube generated using method 200.") See also Figure 2 depicting method 200 comprising the step of updating proportions, as given above. The fluvial sand probability cube is generated using a vertical proportions curve and lateral proportion map, which are described as indicating trends of the facies ((Zhang, Col 10, Line 67- Col 11, Lines 1-2) "FIG. 15 illustrates how the fluvial sand probability cube 1530 may have been generated using the VPC 1510 and the LPM 1520 as described in method 200."); ((Zhang, Col 5, Lines 66-67 and Col 6, Lines 1-8) "As such, the amount of specific facies deposits changes with the variation of geological times or depths leading to a systematic vertical trend of facies proportions. For example, in a fluvial-dominated deltaic environment, the sand deposit may be high at the bottom of a reservoir unit, become lower in the middle of the reservoir unit and becomes high again at the top of the reservoir unit. Coarsening or fining upwards characteristics in geological deposition for a certain facies is also a trend indicator of the deposition of that facies.")
generating, based on the 3D facies trend model, extended facies data for one or more wells of the plurality of wells that are not in the subset of wells that are associated with facies data. A singular facies probability cube model may be extended to a multiple facies model ((Zhang ,Col 11, Lines 19-29) "Method 200 generates a facies probability cube by targeting one facies at a time. As a result, the probability cubes 20 reflect the spatial variation of the likelihood of the selected facies. In reservoir modeling, however, there are often more than two facies present within the earth. Users rarely build multiple facies probability cubes for each facies at one time due to the difficulty of making each facies probability cube 25 consistent with each other. To overcome this difficulty, method 3 00 and method 400, described below, may be used to create a multiple facies model based on the facies probability cube generated by method 200."). The probability cube is suggested as being useful for enabling characterization where well data is scarce, wherein well log data includes facies logs ((Zhang, Col 2, Lines 28-30) "In particular, facies probability cubes can assist in geological modeling or reservoir characterization when well data is scarce."); ((Zhang, Col 5, Lines 31-33) "In one implementation, the measurements obtained by logging device 100 may include well facies data in the well logs (facies logs).")
Regarding claim 9, Zhang teaches The system of claim 8, the operations further comprising: as stated previously and the limitations:
determining, based on the extended facies data, reservoir volumetrics data for the subsurface region; and
determining, based on the reservoir volumetrics data, a location in the subsurface region that includes hydrocarbon deposits are substantially similar to that recited in claim 2 but with respect to independent claim 8 and is therefore rejected for the same rationale as given for claim 2.
Regarding claim 11, Zhang teaches The system of claim 8, the operations further comprising: as stated previously and further the limitations:
receiving geological maps data;
generating an areal trend map; and
generating, based on the areal trend map, the 3D facies trend model. are substantially similar to that recited in claim 4 but with respect to independent claim 8 and is rejected for the same rationale as given for claim 4.
Regarding claim 12, Zhang teaches The system of claim 8, the operations further comprising: as stated previously and the remaining limitations:
detecting, in the facies data of the well log data, vertical trends in facies in the subsurface region;
generating vertical proportion curves from the vertical trends in the facies data; and
generating, based on the vertical proportion curves, the 3D facies trend model are substantially similar to that recited in claim 5 but with respect to independent claim 8 and is rejected for the same rationale as given for claim 5.
Regarding claim 13, Zhang teaches The system of claim 8, as stated previously and the remaining limitation:
wherein the extended facies data represent facies that are present at each of the plurality of wells is substantially similar to that recited in claim 6 but with respect to independent claim 8 and is rejected for the same rationale as given for claim 6.
Regarding claim 15, Zhang teaches One or more non-transitory computer-readable media storing instructions to cause at least one processor to perform operations comprising: ((Zhang, Col 15, Lines 58-62) "13. A non-transitory computer-readable medium for generating one or more geological models for oil field exploration, the computer-readable medium having stored thereon 60 computer-executable instructions which, when executed by a computer, cause the computer to:")
receiving, from sensors in each of a plurality of wells of a reservoir, well log data measured by sensors in each of the wells of the plurality of wells, ((Zhang, Col. 5, Lines 47-51) "At step 210, the computer application may receive well facies data from well facies logs. Well facies logs may be well logs that have been acquired at various locations in a survey area such as boreholes and the like, as described above with reference to FIG.1."); ((Zhang, Col. 14 , Lines 6-9 & 13-16) "The system computer 630 may be in communication with the logging device described in FIG. 1 (either directly or via a recording unit, not shown), to receive signals indicating the measurements on the earth formations.[[…]] In one implementation, these signals and data may be sent to the system computer 630 directly from sensors, such as well logs and the like."), the well log data representing porosity measurements of a subsurface region at each of the wells of the plurality, ((Zhang, Col 5, Lines 2-30) "The logging device 100 may represent any type of logging device that takes measurements from which formation characteristics can be determined, for example, by solving complex inverse problems. The logging device 100 may be an electrical type of logging device (including devices such as resistivity, induction, and electromagnetic propagation devices), a nuclear logging device, a sonic logging device, or a fluid sampling logging device, or combinations thereof. Various devices may be combined in a tool string and/or used during separate logging runs. Also, measurements may be taken during drilling and/or tripping and/or sliding. Examples of the types of formation characteristics that can be determined using these types of devices include: determination, from deep three-dimensional electromagnetic measurements, of distance and direction to faults or deposits, such as salt domes or hydrocarbons; determination, from acoustic shear and/or compressional wave speeds and/or wave attenuations, of formation porosity, permeability, and/or lithology; determination of formation anisotropy from electromagnetic and/or acoustic measurements; determination, from attenuation and frequency of a rod or plate vibrating in a fluid, of formation fluid viscosity and/or density; determination, from resistivity and/or nuclear magnetic resonance (NMR) measurements, of formation water saturation and/or permeability; determination, from count rates of gamma rays and/or neutrons at spaced detectors, of formation porosity and/or density; and determination, from electromagnetic, acoustic and/or nuclear measurements, of formation bed thickness") wherein at least a subset of the wells are associated with facies data representing facies at the subset of the wells; ((Zhang, Col. 5, Lines 31-34) "In one implementation, the measurements obtained by logging device 100 may include well facies data in the well logs (facies logs). Facies logs may indicate the absolute presence or absence of a targeted facies at different spatial locations."); ((Zhang, Col5, Lines 47-51) "At step 210, the computer application may receive well facies data from well facies logs. Well facies logs may be well logs that have been acquired at various locations in a survey area such as boreholes and the like, as described above with reference to FIG.1. Well facies logs may indicate the absolute presence or absence of a targeted facies at different spatial locations.")
determining, from the facies data, facies proportions associated with the subset of wells; ((Zhang, Col 4, Lines 5-7) "Generally, the vertical facies proportion curve and the lateral proportion may be determined based on well facies data in well facies logs.")
determining, from the porosity data, facies probability functions for the plurality of wells; A facies probability cube is generated using well log data, wherein the probability cube is characterized by probability functions indicating the likelihood of the variable of interest at the specified pixels ((Zhang, Col. 8, Lines 33-63) "At step 260, the computer application may generate a facies probability cube using a modified Sequential Gaussian Simulation (SGS IM) algorithm. The conventional Sequential Gaussian Simulation (SGSIM) algorithm, as described in Deutsch, C. V. and Joumel, A. G., 1998, GSLIB: Geostatistical Software Library and User's Guide. Oxford University Press, New York, p. 369 (Deutsch and Journel, 1998), is a popular geostatistical algorithm that is used to simulate a petrophsyical properties distribution of any continuous variable, such as porosity or permeability in a model (i.e., facies probability cube). It is a pixel-based sequential simulation where r is the gamma function. The expected value, second moment and variance of a Beta random variable X with parameters a and ~ are: approach under a multi-Gaussian assumption. The SGSIM algorithm first transforms well log data into standard normal values using a process called normal score transformation. The well log data is transferred into standard normal values for practical purposes because the continuous variables may not follow a Gaussian distribution. FIG. 12 illustrates an example of a Cumulative Density Function (CDF) curve in the original probability space and a CDF curve in the normal score space. The algorithm then proceeds by selecting a random pixel (or voxel in 3D) in a model. Because of the multi-Gaussian assumption, the SGS IM algorithm may make a determination of a conditional cumulative density function ( ccdf) at the selected pixel to determine the probability of the existence of a continuous variable at the selected pixel location. In order to make the determination of the conditional cumulative density function ( ccdf) at the selected pixel, the SGSIM algorithm solves a local kriging system to obtain an estimated kriging mean and variance based on well data obtained from well logs that are within the neighborhood of the selected pixel in the model.").
determining, based on the facies probability functions, facies proportions at the plurality of wells; Facies proportions are determined using the SGSIM algorithm while building the facies probability cube ((Zhang, Col. 9, Lines 36-50) " However, in order to constrain the facies probability cube to the vertical proportion curve, the modified SGS IM algorithm may increase or decrease the kriging mean msk * according to the difference between a running facies proportion and a target facies proportion at the Z-layer at selected pixel. (Step 540). The running facies proportion is defined as the simulated facies proportion before the simulation reaches the selected pixel, and the target facies proportion is the proportion value of the target facies at the selected pixel as indicated from the vertical proportion curve. In order to calculate the running proportion, the computer application may perform a back transformation of the simulated pixels from the normal score values into the original probability space.")
updating the facies proportions at the plurality of wells using the facies proportions of the subset of wells; The facies probability cube is generated considering facies data and associated proportion curves. ((Zhang, Col 4, Lines 5-7) "Generally, the vertical facies proportion curve and the lateral proportion may be determined based on well facies data in well facies logs.") ((Zhang, Col. 6, Lines 9-54) "In one implementation, VPC can be calculated from well facies logs (from step 210) interpretation, geological conceptual models or analogs similar to the reservoir under study. If well facies data are available, the well facies data may be combined with geological interpretations of the seismic area to generated interpreted well facies data. The interpreted well facies data may then be used as anchors in generating facies probability cubes, i.e. they indicate the absolute presences/ absences of the targeted facies at different spatial locations: probability is 1 for its presence and O for its absence. The vertical facies proportion curve can be calculated by extracting the facies proportion along each vertical layer (i.e., Z-layer) of a modeling grid. In case of very sparse wells, the calculated proportion curve may not be reliable and hence, its modification and editing may be performed based on geological interpretations or analogs similar to the studied reservoir. At step 230, the computer application may receive a lateral facies proportion map (LPM). FIG. 8 illustrates an example of a LPM. FIG. 15 illustrates how the LPM 1520 may be used in method 200. The lateral proportion map may be a 2 dimensional map in the XY plane that represents the variation of lateral proportions of certain facies in terms of an average proportion along the Z direction. In this manner, the lateral proportion map may illustrate lateral trends such as progradation or transition. In one implementation, the computer application may obtain the lateral facies proportion map by interpolating facies proportion from each well facies log or by calibrating seismic interpretations of each well facies log. The information included in the lateral facies proportion map may be useful when facies depositions have apparent lateral trends, such as progradation or a transition as observed from received seismic data, well facies log interpretations or conceptual models. The computer application may create lateral proportion maps based on well facies data using any smooth interpolator, such as a kriging technique in 2-point geostatistics or moving averaging algorithms. For instance, at each well location, the computer application may calculate a facies proportion. The facies proportion value may then be considered to be one of the hard data used as an anchor point to control the smooth interpolator. In one implementation, the computer application may also add interpreted trends into the LPM by adding data from "pseudo" wells. In any case, by integrating LPM into reservoir modeling, the computer application may be able to generate a facies probability cube that has more realistic results")
based on the updated facies proportions at the plurality of wells, generating a three-dimensional (3D) facies trend model for the subsurface region at each of the wells of the plurality; and ((Zhang, Col 10, Lines 65-67) "FIG. 10 illustrates an example of a fluvial sand probability cube generated using method 200.") See also Figure 2 depicting method 200 comprising the step of updating proportions, as given above. The fluvial sand probability cube is generated using a vertical proportions curve and lateral proportion map, which are described as indicating trends of the facies ((Zhang, Col 10, Line 67- Col 11, Lines 1-2) "FIG. 15 illustrates how the fluvial sand probability cube 1530 may have been generated using the VPC 1510 and the LPM 1520 as described in method 200."); ((Zhang, Col 5, Lines 66-67 and Col 6, Lines 1-8) "As such, the amount of specific facies deposits changes with the variation of geological times or depths leading to a systematic vertical trend of facies proportions. For example, in a fluvial-dominated deltaic environment, the sand deposit may be high at the bottom of a reservoir unit, become lower in the middle of the reservoir unit and becomes high again at the top of the reservoir unit. Coarsening or fining upwards characteristics in geological deposition for a certain facies is also a trend indicator of the deposition of that facies.")
generating, based on the 3D facies trend model, extended facies data for one or more wells of the plurality of wells that are not in the subset of wells that are associated with facies data. A singular facies probability cube model may be extended to a multiple facies model ((Zhang ,Col 11, Lines 19-29) "Method 200 generates a facies probability cube by targeting one facies at a time. As a result, the probability cubes 20 reflect the spatial variation of the likelihood of the selected facies. In reservoir modeling, however, there are often more than two facies present within the earth. Users rarely build multiple facies probability cubes for each facies at one time due to the difficulty of making each facies probability cube 25 consistent with each other. To overcome this difficulty, method 3 00 and method 400, described below, may be used to create a multiple facies model based on the facies probability cube generated by method 200."). The probability cube is suggested as being useful for enabling characterization where well data is scarce, wherein well log data includes facies logs ((Zhang, Col 2, Lines 28-30) "In particular, facies probability cubes can assist in geological modeling or reservoir characterization when well data is scarce."); ((Zhang, Col 5, Lines 31-33) "In one implementation, the measurements obtained by logging device 100 may include well facies data in the well logs (facies logs).")
Regarding claim 16, Zhang teaches The one or more non-transitory computer-readable media of claim 15, the operations further comprising: as stated previously and the limitations:
determining, based on the extended facies data, reservoir volumetrics data for the subsurface region; and
determining, based on the reservoir volumetrics data, a location in the subsurface region that includes hydrocarbon deposits are substantially similar to that recited in claim 2 but with respect to independent claim 15 and is rejection for the same rationale as given form claim 2.
Regarding claim 18, Zhang teaches The one or more non-transitory computer-readable media of claim 15, the operations further comprising: as stated previously and the remaining limitations:
receiving geological maps data;
generating an areal trend map; and
generating, based on the areal trend map, the 3D facies trend model. model are substantially similar to that recited in claim 4 but with respect to independent claim 15 and is rejected for the same rationale as given for claim 4.
Regarding claim 19, Zhang teaches The one or more non-transitory computer-readable media of claim 15, the operations further comprising: as stated previously and the remaining limitations:
detecting, in the facies data of the well log data, vertical trends in facies in the subsurface region;
generating vertical proportion curves from the vertical trends in the facies data; and
generating, based on the vertical proportion curves, the 3D facies trend model are substantially similar to that recited in claim 5 but with respect to independent claim 15 and is rejected for the same rationale as given for claim 5.
Regarding claim 20, Zhang teaches The one or more non-transitory computer-readable media of claim 15, as stated previously and the remaining limitation:
wherein the extended facies data represent facies that are present at each of the plurality of wells is substantially similar to that recited in claim 6 but with respect to independent claim 15 and is rejected for the same rationale as given for claim 6.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 3, 7, 10, 14, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (US 8,838,425 B2) as applied to claims 1, 8 and 15 above, and further in view of Algheryafi et al (WO2022061009A1), hereinafter referred to as Algheryafi.
Regarding claim 3, Zhang teaches The method of claim 2, further comprising: as stated previously but does not teach explicitly drilling, at the location in the subsurface region, a well.
However, Algheryafi is relied upon to teach drilling, at the location in the subsurface region, a well. ((Algheryafi,¶37) “ In some embodiments, the modified facies model 164 is used as a basis for determining parameters 170 for the well 106. For example, a well parameter 170 of the horizontal wellbore of the well 106 may be determined based on the modified facies model 164 , and the well 106 may be developed in accordance with the parameter. The well parameter 170 may include, for example, a drilling parameter (e.g., a well trajectory) and the well 106 may be drilled in accordance with the drilling parameter (e.g., the well 106 may be drilled to follow the well trajectory).").
Zhang and Algheryafi are both analogous to the claimed invention because they are both related to the same field of endeavor of facies modeling for hydrocarbon drilling applications. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have modified the disclosure of Zhang with the teachings of Algheryafi because some teaching, suggestion, or motivation would have led one having skill in the art to do so in order to arrive at the claimed invention. Zhang discloses a methodology for modeling facies data in subsurface survey area and suggests that the modeling may be used to identify hydrocarbon deposits ((Zhang, Col 2, Lines 19-21) " The resulting geological or reservoir models can then be used 20 for oil field explorations by identifying hydrocarbon deposits in the Earth. "). However, Zhang does not explicitly impart guidance to drill with consideration to the identification of the deposits by the model and only suggests that this may be useful for exploration purposes. Algheryafi explicitly teaches that facies model data may be used as a basis for forming a depositional model ((Algheryafi,¶32) " In some embodiments, a depositional model 160 is generated for the formation 104. This may include a modeling of the formation 104 that indicates locations of different types of rock within the formation 104. For example, a depositional model 160 of the formation 104 may include a three dimensional (3D) grid that maps the types and locations of formation rock across the region that is proximate the well 106. Each of the different type of rocks may be defined by common set of characteristics for the type of rock, such as a given range of density, porosity, or the like. In some embodiments, the depositional model 160 is generated based on facies data 140. ") and for determining drilling parameters for developing a hydrocarbon well, including a well trajectory, as a location for drilling so as to extract hydrocarbons ((Algheryafi,¶46) " In some embodiments, method 200 includes developing a well based on a facies model (block 216). This may include, drilling, completing or producing a hydrocarbon well based on a facies model for the well. "); ((Algheryafi,¶37) "In some embodiments, the modified facies model 164 is used as a basis for determining parameters 170 for the well 106. For example, a well parameter 170 of the horizontal wellbore of the well 106 may be determined based on the modified facies model 164 , and the well 106 may be developed in accordance with the parameter. The well parameter 170 may include, for example, a drilling parameter (e.g., a well trajectory) and the well 106 may be drilled in accordance with the drilling parameter (e.g., the well 106 may be drilled to follow the well trajectory)."); ((Algheryafi,¶2) " A hydrocarbon reservoir is a pool of hydrocarbons (e.g., oil or gas) trapped in a subsurface rock formation. Hydrocarbon wells are often drilled into hydrocarbon reservoirs to extract (or “produce”) the trapped hydrocarbons. These types of wells are typically drilled and operated in a manner to optimize production of hydrocarbons from a reservoir. For example, a reservoir is typically assessed to identify characteristics of the reservoir, the locations and trajectories (or “paths”) of wells to be drilled into the reservoir are determined based on the characteristics, the w ells are drilled into the reservoir in accordance with the locations and trajectories, and the wells are operated to efficiently extract hydrocarbon production from the reservoir. "). By using the facies model of Zhang to determine the presence of hydrocarbon deposits and subsequently using the strategy of Algheryafi of using predictions from a facies model to inform drilling parameters include trajectory and subsequently perform drilling according to such parameters, one having skill would arrive at the claimed invention.
Regarding claim 7, Zhang teaches The method of claim 1, however fails to explicitly teach wherein the subset of wells include cored wells from which facies data are directly measured.
Algheryafi is relied upon to teach wherein the subset of wells include cored wells from which facies data are directly measured. Vertical wells (as a subset) are associated with core data, whereas horizontal wells are only associated with wireline log data ((Algheryafi, ¶6) " In some embodiments, the vertical wellbore core data is obtained by way of core samples extracted from vertical portions of wellbores of wells that extend into the subsurface formation. The vertical wellbore core data may include, for example, characteristics of the core samples measured in a core laboratory (e.g., at the surface) after extraction of the core. In some embodiments, the wireline log data is obtained by way of downhole logging of wellbores of wells that extend into the subsurface formation. The wireline log data may include, for example, characteristics of rock of the subsurface formation measured in-situ by way of one or more downhole logging tools. The wireline log data may include vertical wireline log data that corresponds to downhole logging of vertical portions of the wellbores of the wells that extend into the subsurface formation, and horizontal wireline log data that corresponds to downhole logging of horizontal portions of the wellbores of the wells that extend into the target interval of the subsurface formation. "). Core data is used to obtain facies data ((Algheryafi,¶8) " Provided in some embodiments is a method of developing a hydrocarbon well that includes the following: obtaining facies data for a subsurface formation, the facies data including: vertical wellbore core data obtained by way of core samples extracted from vertical portions of wellbores of wells that extend into tire subsurface formation, tire vertical wellbore core data including characteristics of the core samples measured in a core laboratory' after extraction of the core; and wireline log data obtained by way of downhole logging of wellbores of wells that extend into the subsurface formation, the wireline log data including characteristics of rock of the subsurface formation measured in-situ by way of a downhole logging tool, the wireline log data including: vertical wireline log data that corresponds to downhole logging of vertical portions of the wellbores of the wells that extend into the subsurface formation; and horizontal wireline log data that corresponds to downhole logging of horizontal portions of the wellbores of the wells that extend into a target interval of the subsurface formation; determining, based on the vertical wellbore core data and the vertical wireline log data, a depositional model of the subsurface formation; determining, based on the facies data, a facies model of a horizontal portion of a wellbore of a hydrocarbon well that extends into the target interval of the subsurface formation, the facies model of the horizontal portion of the wellbore including a predicted facies log that identifies predicted facies of formation rock along a length of the horizontal portion of the wellbore of the hydrocarbon well; [[…]]”) The core data is directly measured in the lab ((Algheryaf,¶4) " The characteristics for different depths may be assembled to generate a core log that identifies characteristics of the formation rock as a function of depth in the wellbore. These characterizations involve a direct inspection of the samples in a laboratory and are generally considered to be reliable and accurate.")
Zhang and Algheryafi are both analogous to the claimed invention because they are both related to the same field of endeavor of facies modeling for hydrocarbon drilling applications. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have modified the disclosure of Zhang with the teachings of Algheryafi because some teaching, suggestion, or motivation would have led one having skill in the art to do so in order to arrive at the claimed invention. Zhang suggests that reservoir measurements may be obtained from core analysis and used for geological modeling purposes but does not particularly distinguish a subset of wells being associated with a cored well ((Zhang, Col 1, Lines 25-30) "Geological modeling and reservoir characterization pro- vide quantitative 3D reservoir models based on available reservoir measurements, such as well log interpretations, experimental results from core analysis, seismic survey and dynamic fluid flow responses from field observations (e.g., historic production data) and pressure change data"). Algheryafi discloses using a multitude of measured data to generate and validate facies logs for facies modeling and development of a horizontal hydrocarbon well (See Algheryafi ¶5). Algheryafi explicitly describes that obtaining core data for horizontal wells may be expensive and difficult to obtain but vertical portions of the wellbore are more apt to have corresponding core data which can be used to build facies logs for the creation of accurate models ((Algheryafi, ¶4) "Although there are numerous existing techniques for determining characteristics of formation rock along the path of a horizontal wellbore, they often suffer from shortcomings. For example, in many instances core samples are extracted from a wellbore during drilling and the cores are assessed in a laboratory to determine characteristics of the formation rock at the corresponding depth. The characteristics for different depths may be assembled to generate a core log that identifies characteristics of the formation rock as a function of depth in the wellbore. These characterizations involve a direct inspection of the samples in a laboratory and are generally considered to be reliable and accurate. Unfortunately, coring can be expensive and difficult to achieve in horizontal portions of wellbores, and, thus, coring may be resowed for assessing vertical portions of wellbores. As a further example, in many instances wireline logging is conducted to determine characteristics of formation rock in-situ. Wireline logging typically includes advancing a logging tool through a wellbore and acquiring measurements along the length of the wellbore to generate a wireline log (or “well log”) that identifies characteristics of the formation rock as a function of depth in the wellbore. Although wireline logs can be reliable and accurate, the level of information may be limited by the sensing technology and the ability to accurately interpret the logging data. Moreover, in the case of a well that is not yet drilled, neither coring nor wireline logging may be possible, and characteristics of the formation rock be predicted based on characteristics of nearby wells and data acquired by way of other assessments of the formation."). Accordingly, because the vertical data is more easily accessible and core data yields high accuracy in terms of ground truth data, it would have been obvious to leverage the vertical core data as anchoring data points for modeling and developing a horizontal well.
Regarding claim 10, Zhang teaches The system of claim 9, as stated previously and further discloses a system with drilling capabilities further comprising a drill, wherein the operations further comprise: ((Zhang, Col 5, Lines 12-13) " Also, measurements may be taken during drilling and/or tripping and/or sliding. "; ((Zhang, Col 4, Lines 66-67 and Col 5, Lines 1-2) " Although logging device 100 illustrated herein is shown to be a wireline logging tool, it should be noted that other tools such as a logging while drilling tool may be used in connection with various implementations described herein. ").
However Zhang does not explicitly disclose drilling, at the location in the subsurface region, a well using the drill.
In the same manner as claim 3, Algheryafi is relied upon to disclose the limitation. The rationale is not restated, for brevity, and substantially mirrors the rationale given for claim 3, except with respect to independent claim 8 and intervening claim 9.
Regarding claim 14, Zhang teaches The system of claim 8, as stated previously. The remaining limitation wherein the subset of wells include cored wells from which facies data are directly measured is substantially similar to that recited in claim 7 but with respect to independent claim 8. The rationale follows that provided for claim 7 and is not restated, for brevity.
Regarding claim 17, Zhang teaches The one or more non-transitory computer-readable media of claim 16, the operations further comprising: as stated previously. Zhang is not relied upon to teach:
generating a control signal based on the determined location in the subsurface region; and
region based on the control signal, controlling drilling of a well at the location in a subsurface.
However, Algheryafi teaches generating a control signal based on the determined location in the subsurface region; and((Algheryafi,¶37) “ In some embodiments, the modified facies model 164 is used as a basis for determining parameters 170 for the well 106. For example, a well parameter 170 of the horizontal wellbore of the well 106 may be determined based on the modified facies model 164 , and the well 106 may be developed in accordance with the parameter. The well parameter 170 may include, for example, a drilling parameter (e.g., a well trajectory) and the well 106 may be drilled in accordance with the drilling parameter (e.g., the well 106 may be drilled to follow the well trajectory).").
region based on the control signal, controlling drilling of a well at the location in a subsurface. ((Algheryafi,¶25) "The well 106 may include a wellbore 120 and a well control system (“control system”) 122, The control system 122 may control various operations of the well 106, such as well drilling operations, well completion operations, well production operations, or well and formation testing and monitoring operations. In some embodiments, the control system 122 includes a computer system that is the same as or similar to that of computer system 1000 described with regard to at least FIG. 7."); ((Algheryafi,¶38) "A well operator, such as a control module of the control system 122 (or well personnel), may develop the reservoir 102 based on the well pararneter(s) 170. For example, a control module of the control system 122 (or well personnel) may develop the reservoir 102 by controlling a well drilling, completion or production system to drill, complete or produce the well 106, respectively."); ((Algheryafi,¶46) "For example, developing a well based on a facies model may include the control system 122 determining a well parameter 170 of the horizontal portion 132 of the wellbore 120 of the well 106 based on the modified predicted facies model 164’, and developing the well 106 in accordance with the parameter.").
The rationale to combine references follows that as given for claim 3 and is not restated for brevity.
Conclusion
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/E.G.L./ Examiner, Art Unit 2187
/EMERSON C PUENTE/ Supervisory Patent Examiner, Art Unit 2187
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