DETAILED ACTION
A summary of this action:
Claims 1 and 3-20 have been presented for examination.
This action is Final.
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 .
Response to Arguments
Following Applicants arguments and amendments, and in light of the 2019 Patent Eligibility guidance, the 101 rejection of the Claims is Maintained.
Applicant’s Argument: Applicant’s arguments directed to 101 rejection are based on newly amended subject matter." Here, Applicant argues amended independent claims 1, 8, and 15 are meaningfully limited and not directed to an abstract idea of a mental process or mathematical concept, but to a practical application of a technological process involving a particular machine because Applicant includes the use of a GC-MS allows for detection and quantification of the gas byproducts produced by a well. Thus, the claimed GC-MS is particularly adapted to carry out the claimed processes. Furthermore, Applicant argues the newly proposed claim limitations tie independent claims 1 and 8 to a real-world application that produce a tangible result, which goes beyond merely gathering, analyzing, and outputting data and cannot be performed in the mind.
Examiner’s Response: Applicant respectfully disagrees because independent claims 1, 8, and 15, as drafted, similarly recite a process that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “mass-spectrometer,” “one or more computer processors, and “a non-transitory computer-readable medium,” nothing in the claim element precludes the step from practically being performed in the mind. Accordingly, the limitation similarly recite analyzing the data with a gas-chromatograph equipped with a mass-spectrometer and adjusting an actual well gas rate at each of the wells in the list of wells according to the determined adjusted well gas rate until the assigned target rate percent of the gas byproduct is met, which is an abstract idea and covers mental processes All arguments are addressed in the 101 rejection of the claims below.
Therefore, the 101 rejection of the claims is Maintained.
Following Applicants arguments and amendments, the 103 rejection of the claims is Maintained.
Applicant’s Argument: Applicant’s arguments directed the 103 rejection are based on newly amended subject matter. Here, Applicant argues that none of the cited prior art references are related to optimizing gas byproducts at an individual well level or teaches or suggests a system, method, or computer readable program for optimizing the percent of a gas byproduct in a total gas produced by determining an adjusted well gas rate for each of the wells in a list of wells until the assigned target percent of the gas byproduct is met, as recited in amended independent claims 1, 8, and 15.
Examiner’s Response: Examiner respectfully disagrees because GURPINAR teaches the location of underground deposits of hydrocarbon and Applicant’s newly amended claim limitation of analyzing the data with a gas-chromatograph equipped with a mass-spectrometer is taught by KAWASE, which teaches All arguments are addressed in the 103 rejection of the claims below.
Therefore, the 103 rejection is Maintained.
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 of a mental process or mathematical concept without significantly more.
Step 1: Claims 1 and 3-7 are directed to a method, which is a process and is a statutory category invention. Claims 8-14 are directed to a system, which is a system and is a statutory category invention. Claims 15-20 are directed to a computer-readable program and is interpreted as a non-transitory computer-readable media in light of the written claim limitations because the specification further clarifies that the computer-readable program comprises of computer-readable instructions stored on a non-transitory computer-readable media, which is a manufacture and is a statutory category invention. Therefore, claims 1 and 3-20 are directed to patent eligible categories of invention.
Claim 1
Step 2A, Prong 1: Independent claims 1, 8, and 15, as drafted, similarly recite a process that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “mass-spectrometer,” “one or more computer processors, and “a non-transitory computer-readable medium,” nothing in the claim element precludes the step from practically being performed in the mind. Accordingly, the limitation similarly recite based on the analyzed data, determining, by one or more computer processors, an effect of each well' s contribution percent gas byproduct in a total gas produced at a gas processing facility, wherein the gas processing facility is configured to process the gas collected from the plurality of wells, which is an abstract idea and covers mental processes of assessing the data obtained from one or more computer processors the effect of each well’s contribution to a total gas produced at a gas processing facility, as described in [0004] of the specification, because the claims are derived from Mental Processes based on concepts performed in the human mind or with the aid of pencil and paper or in the alternative Mathematical Concepts using mathematical relationships, mathematical formulas or equations, or mathematical calculations.
Independent claims 1, 8, and 15, as drafted, similarly recite a process that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “mass-spectrometer,” “one or more computer processors, and “a non-transitory computer-readable medium,” nothing in the claim element precludes the step from practically being performed in the mind. Accordingly, the limitation similarly recite analyzing the data with a gas-chromatograph equipped with a mass-spectrometer, which is an abstract idea and covers mental processes of assessing the well sample data at the surface sensor obtained on a gas-chromatograph, as described in [0023] of the specification, because the claims are derived from Mental Processes based on concepts performed in the human mind or with the aid of pencil and paper or in the alternative Mathematical Concepts using mathematical relationships, mathematical formulas or equations, or mathematical calculations,.
Independent claims 1, 8, and 15, as drafted, similarly recite a process that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “mass-spectrometer,” “one or more computer processors, and “a non-transitory computer-readable medium,” nothing in the claim element precludes the step from practically being performed in the mind. Accordingly, the limitation similarly recite based on the identified effect of each well, selecting, by the one or more computer processors, a list of wells from the plurality of wells, which is an abstract idea and covers mental processes of assessing each well identified from a list of wells, as described in [0004] of the specification, because the claims are derived from Mental Processes based on concepts performed in the human mind or with the aid of pencil and paper or in the alternative Mathematical Concepts using mathematical relationships, mathematical formulas or equations, or mathematical calculations.
Independent claims 1, 8, and 15, as drafted, similarly recite a process that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “mass-spectrometer,” “one or more computer processors, and “a non-transitory computer-readable medium,” nothing in the claim element precludes the step from practically being performed in the mind. Accordingly, the limitation similarly recite optimizing, by the one or more computer processors, the percent of the gas byproduct in the total gas produced by determining an adjusted well gas rate for each of the wells in the list of wells, which is an abstract idea and covers mental processes of assessing one or more parameters of interest in the total gas produced and ensure the assigned target rate is met, as described in [0004] of the specification, because the claims are derived from Mental Processes based on concepts performed in the human mind or with the aid of pencil and paper or in the alternative Mathematical Concepts using mathematical relationships, mathematical formulas or equations, or mathematical calculations.
Independent claims 1, 8, and 15, as drafted, similarly recite a process that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “mass-spectrometer,” “one or more computer processors, and “a non-transitory computer-readable medium,” nothing in the claim element precludes the step from practically being performed in the mind. Accordingly, the limitation similarly recite adjusting an actual well gas rate at each of the wells in the list of wells according to the determined adjusted well gas rate until the assigned target percent of the gas byproduct is met, which is an abstract idea and covers mental processes of assessing one or more parameters of interest in the total gas produced and ensure the assigned target rate is met, as described in [0004] of the specification, because the claims are derived from Mental Processes based on concepts performed in the human mind or with the aid of pencil and paper or in the alternative Mathematical Concepts using mathematical relationships, mathematical formulas or equations, or mathematical calculations.
Independent claim 8, as drafted, recites a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “mass-spectrometer,” “one or more computer processors, and “a non-transitory computer-readable medium,” nothing in the claim element precludes the step from practically being performed in the mind. Accordingly, the limitation similarly recite an analytical module equipped to obtain and analyze well data from a plurality of wells in a geographical region of interest wherein the analytical model comprises a gas-chromatograph equipped with a mass spectrometer, which is an abstract idea and covers mental processes of assessing an analytical module equipped to obtain well data from a plurality of wells within a geographical region of interest and one or more computer processors, as described in [0004] of the specification, because the claims are derived from Mental Processes based on concepts performed in the human mind or with the aid of pencil and paper or in the alternative Mathematical Concepts using mathematical relationships, mathematical formulas or equations, or mathematical calculations.
Claims 8 and 15, as drafted, are a process that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “mass-spectrometer,” “one or more computer processors, and “a non-transitory computer-readable medium,” nothing in the claim element precludes the step from practically being performed in the mind. Accordingly, the limitation similarly recite one or more computer processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more computer processors perform operations of, which is an abstract idea and covers mental processes of assessing the executable instructions encoded that when executed perform multiple operations, as described in [0004] of the specification, because the claims are derived from Mental Processes based on concepts performed in the human mind or with the aid of pencil and paper or in the alternative Mathematical Concepts using mathematical relationships, mathematical formulas or equations, or mathematical calculations.
Thus, the claims recite the abstract idea of a mental process performed in the human mind, or with the aid of pencil and paper.
Dependent claims 3-7, 9-14, and 16-20 further narrow the abstract ideas, identified in the independent claims. See analysis below.
Step 2A, Prong 2: The judicial exception is not integrated into a practical application. Claim 1 recites the additional limitation “mass-spectrometer,” “one or more computer processors” as in independent claims 8 and 15 and dependent claim 9, 10, 12, 14, 16, and 18, “non-transitory computer-readable medium” as in independent claims 8 and 15 and dependent claims 16-20, “system” as in independent claim 8 and dependent claims 9-14, this limitation does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h). Alternatively, this additional element merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)).
The limitation assigning a target percent of a gas byproduct in a desired gas blend, similarly recited in independent claim 1, only amounts to mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f).
The limitation obtaining a target percent of a gas byproduct in a desired gas blend, similarly recited in independent claims 8 and 15, can be viewed as is insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception is not integrated into a practical application.
The limitation obtaining data analyzed with the gas-chromatograph equipped with the mass-spectrometer related to the gas byproduct for each well, similarly recited in independent claims 8 and 15, can be viewed as is insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception is not integrated into a practical application.
The limitation obtaining data related to the gas byproduct for each well of a plurality of wells in a geographical region of interest, similarly recited in independent claims 1, 8 and 15, can be viewed as is insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception is not integrated into a practical application.
The limitation of “applying the determined correction factor to the blend total parameter value,” similarly recited in claims 5, 12, and 18, this limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception See MPEP 2106.05(f).
Dependent claims 3-7, 9-14, and 16-20 further narrow the abstract ideas, identified in the independent claims, and do not introduce further additional elements for consideration beyond those addressed above. The additional elements have been considered both individually and as an ordered combination in to determine whether they integrate the exception into a practical application. Therefore, the dependent claims do not integrate the claimed invention into a practical application.
Step 2B: The claims do not amount to significantly more. The judicial exception does not amount to significantly more. Claim 1 recites the additional limitation “mass-spectrometer,” “one or more computer processors” as in independent claims 8 and 15 and dependent claim 9, 10, 12, 14, 16, and 18, “non-transitory computer-readable medium” as in independent claims 8 and 15 and dependent claims 16-20, “system” as in independent claim 8 and dependent claims 9-14, this limitation does not amount to significantly more because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h). Alternatively, this additional element merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)).
The limitation assigning a target percent of a gas byproduct in a desired gas blend, similarly recited in independent claim 1, only amounts to mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f) and does not amount to significantly more.
The limitation obtaining a target percent of a gas byproduct in a desired gas blend, similarly recited in independent claims 8 and 15, can be viewed as is insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and does not amount to significantly more. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception does not amount to significantly more.
The limitation obtaining data analyzed with the gas-chromatograph equipped with the mass-spectrometer related to the gas byproduct for each well, similarly recited in independent claims 8 and 15, can be viewed as is insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is does not amount to significantly more. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception does not amount to significantly more.
The limitation obtaining data related to the gas byproduct for each well of a plurality of wells in a geographical region of interest, similarly recited in independent claims 1, 8 and 15, can be viewed as is insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and does not amount to significantly more. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception does not amount to significantly more.
The limitation of “applying the determined correction factor to the blend total parameter value,” similarly recited in claims 5, 12, and 18, this limitation does not amount to significantly more because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception See MPEP 2106.05(f).
Dependent claims 3-7, 9-14, and 16-20 further narrow the abstract ideas, identified in the independent claims, and do not introduce further additional elements for consideration beyond those addressed above. The additional elements have been considered both individually and as an ordered combination in to determine whether they does not amount to significantly more. Therefore, the dependent claims does not amount to significantly more.
Therefore, the claims as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered alone or in combination, do not amount to significantly more than the judicial exception.
As stated in Section I.B. of the December 16, 2014 101 Examination Guidelines, “[t]o be patent-eligible, a claim that is directed to a judicial exception must include additional features to ensure that the claim describes a process or product that applies the exception in a meaningful way, such that it is more than a drafting effort designed to monopolize the exception.”
The dependent claims include the same abstract ideas recited as recited in the independent claims, and merely incorporate additional details that narrow the abstract ideas and fail to add significantly more to the claims.
Dependent claim 3 recites “determining one or more well level constraint criteria;
for each well, determining a blend total parameter value for the gas byproduct; sorting the plurality of wells according to their blend total parameter values to obtain the list of wells; determining if a selected well meets the at least one well level constraint criteria; adjusting the well gas rate of the selected well when the well gas rate meets the at least one well level constraint criteria; determining a new blend total parameter value for each selected well using the adjusted well gas rate; and based on the new blend total parameter value, determining if the assigned target percent of the gas byproduct has been met,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 4 recites wherein the blend total parameter value is determined based on a well level parameter value of the gas byproduct, a well gas rate, and a total gas rate,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 5 recites determining a correction factor for the gas byproduct to correct for different operating conditions between each well and the gas processing facility,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 6 recites “wherein the blend total parameter value is determined
according to the following:
PNG
media_image1.png
83
1201
media_image1.png
Greyscale
,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mathematical Concept.”
Dependent claim 7 recites “sorting the plurality of wells in a descending order based on their blend total parameter values to obtain a first list of wells; increasing the well gas rates of wells in the first list that meet the at least one well level constraint criterion by a value; sorting the plurality of wells in an ascending order based on their blend total parameter values to obtain a second list of wells; and decreasing the well gas rates of wells in the second list that meet the at least one well level constraint criterion by the value,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes,” or in the alternative a Mathematical Concept.”
Dependent claim 9 recites “wherein the one or more computer processors further perform an operation of electronically transmitting the list of wells to a user,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes,” or in the alternative a Mathematical Concept.”
Dependent claim 10 recites “determining at least one well level constraint criterion; for each well, determining a blend total parameter value for the gas byproduct; sorting the plurality of wells according to their blend total parameter values to obtain the list of wells; determining if a selected well meets the at least one well level constraint criteria; adjusting the well gas rate of the selected well when the well gas rate meets the at least one well level constraint criteria; determining a new blend total parameter value for each selected well using the adjusted well gas rate; and based on the new blend total parameter value, determining if the assigned target percent of the gas byproduct has been met,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes,” or in the alternative a “Mathematical Concept.”
Dependent claim 11 recites “wherein the blend total parameter value is determined based on a well level parameter value of the gas byproduct, a well gas rate, and a total gas rate,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes,” or in the alternative a “Mathematical Concept.”
Dependent claim 12 recites “determining a correction factor for the gas byproduct to correct for different operating conditions between each well and the gas processing facility,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 13 recites “wherein the blend total parameter value is determined
according to the following:
PNG
media_image1.png
83
1201
media_image1.png
Greyscale
,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mathematical Concept.”
Dependent claim 14 recites “sorting the plurality of wells in a descending order based on their blend total parameter values to obtain a first list of wells; increasing the well gas rates of wells in the first list that meet the at least one well level constraint criteria by a value; sorting the plurality of wells in a descending order based on their blend total parameter values to obtain a first list of wells; increasing the well gas rates of wells in the first list that meet the at least one well level constraint criterion by a value,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 16 recites “determining at least one well level constraint criteria; for each well, determining a blend total parameter value of the gas byproduct; sorting the plurality of wells according to their blend total parameter values to obtain the list of wells; determining if a selected well meets the at least one well level constraint criteria; adjusting the well gas rate of the selected well when the well gas rate meets the at least one well level constraint criteria; determining a new blend total parameter value for each selected well using the adjusted well gas rate; and based on the new blend total parameter value, determining if the assigned target percent of the gas byproduct has been met,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 17 recites “wherein the blend total parameter value is determined based on a well level parameter value of the gas byproduct, a well gas rate, and a total gas rate,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 18 recites “determining a correction factor for gas byproduct to correct for different operating conditions between each well and the gas processing facility,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 19 recites “wherein the blend total parameter value is determined
according to the following:
PNG
media_image1.png
83
1201
media_image1.png
Greyscale
,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mathematical Concept.”
Dependent claim 20 recites “sorting the plurality of wells m a descending order based on their blend total parameter values to obtain a first list of wells; increasing the well gas rates of wells in the first list that meet the at least one well level constraint criterion by a value; sorting the plurality of wells m an ascending order based on their blend total parameter values to obtain a second list of wells; and decreasing the well gas rates of wells in the second list that meet the at least one well level constraint criterion by the value,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
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.
Claim(s) 1 and 3-20 are rejected under are rejected under 35 U.S.C. 103 as being unpatentable over VAN BERKEL (Blending Optimization of Contaminated Gas in a Miscible Gas flood), herein VAN BERKEL, in view of GURPINAR (US 2005/0149307 A1), herein GURPINAR, in view of CULLICK (US 20070192072 A1), herein CULLICK, and KAWASE (WO 2021220673 A1), herein KAWASE.
Claim 1
Claims 1 is rejected because VAN BERKEL teaches a computer implemented method for gas blend optimization VAN BERKEL ([Abstract] “A new element is a compositional gas blending optimization model in the gas processing facilities.”)
VAN BERKEL does not explicitly teach assigning a target percent of a gas byproduct for one or more parameters of interest in a desired gas blend or obtaining data related to the gas byproduct for each well of a plurality of wells in a geographical region of interest.
However, GURPINAR teaches assigning a target percent of a gas byproduct for one or more parameters of interest in a desired gas blend GURPINAR ([0163] “The 'sales & transport constraints' block 42c4 which should be imposed (assigning a target percent of a gas byproduct) over some portion of the field (one or more parameters of interest), include some sort of restriction that is related to existing pipelines and which can be changed for different forecasts. For example, if we were to increase the diameter of the pipe and demanded 500K barrels/day instead of 300K barrels of day, what would be the difference in the long term? In connection with the 'rig & equipment availability' block 42c5, we may be developing a field with a lot more wells and yet we will be drilling the wells in an effort to maintain the production target rate (target percent of a gas byproduct)… In connection with the 'mechanism optimization' block or decision triangle 42cl0, for the 'mechanism' that you have chosen (where the word 'mechanism' is defined as the process that is active in the reservoir, such as whether water or gas (percent of a gas byproduct) is being injected into the reservoir).”) See also GURPINAR ([0166] “A third check is now implemented in the 'by-product disposal needed' decision triangle block 42e8. In this decision triangle block 42e8, do you need any additional byproduct disposal? If yes, take the 'yes' output from decision triangle block 42e8 which leads us to the 'by-product disposal facility' block 42e9. In block 42e9, if, for example, you do produce substantial amounts of water.”) See also GURPINAR ([0021] “As a result of the continual updating of the 'day-today operational plan' from the 'reservoir development plan' in response to the two above referenced measurements taken on a frequent and an infrequent basis, a more precise determination of 'two parameters' is obtained: (1) the location of underground deposits of hydrocarbon (gas byproduct), and (2) the pressure distribution within the subsurface geological formations. When these 'two parameters' are optimized, the following 'further parameters' are also optimized: the number of wells, well completions, well interference, and production plans.”)
GURPINAR also teaches obtaining data related to the gas byproduct for each well of a plurality of wells in a geographical region of interest GURPINAR ([0169] “These are issues (parameters of interest) which will arise depending on: where the reservoir field is located (plurality of wells in a geographical region of interest), whether it is on-shore or off-shore, what kind of government is in place, and the impact these issues have on planning, economic provisions, and the risk (obtaining data related to the gas byproduct) that must be considered when deciding to implement a particular field development plan. These are issues that will be considered separately from main stream technical evaluations. Therefore, the 'environmental considerations' (gas byproduct) must be taken into account when doing risk analysis and economic appraisals. In FIGS. 15A and 15B, four broader categories of 'environmental considerations' (related to gas byproduct) have been identified: the 'special emergency response plans and provisions' block 42d1, the 'pre-construction environmental impact study requirements' block 42d2, the 'interrupted or restricted access to wells/facilities' block 42d3 (each well of a plurality of wells), and the 'government or regulatory approval and audit provisions' block 42d4…In The 'preconstruction environmental impact study requirements' identifies special needs and restrictions (related to gas byproduct) depending on the geographical location (geographical region of interest) and local regulations in effect (which will vary from one location to another). In the 'drilling site selection restrictions' block 42d8, one such restriction is the selection of a drilling site.”) See also GURPINAR ([0021] “As a result of the continual updating of the 'day-today operational plan' from the 'reservoir development plan' in response to the two above referenced measurements taken on a frequent and an infrequent basis, a more precise determination of 'two parameters' is obtained: (1) the location of underground deposits of hydrocarbon, and (2) the pressure distribution within the subsurface geological formations. When these 'two parameters' are optimized, the following 'further parameters' are also optimized: the number of wells, well completions, well interference, and production plans.”) See also GURPINAR ([0021], [0105], [0141], [0147-0148], [Figure 1], [Figure 2], [Figure 15A] and [Figure 15B].)
PNG
media_image2.png
638
983
media_image2.png
Greyscale
GURPINAR Figure 15A Reference
GURPINAR also teaches determining, by one or more computer processors, an effect of each well's contribution to the percent gas byproduct by in a total gas produced at a gas processing facility GURPINAR ([0166] “A third check is now implemented in the 'by-product disposal needed' (effect of each well's contribution to the percent gas byproduct by in a total gas produced) decision triangle block 42e8. In this decision triangle block 42e8, do you need any additional byproduct disposal? If yes, take the 'yes' output from decision triangle block 42e8 which leads us to the 'by-product disposal facility' (gas processing facility) block 42e9.”)
GURPINAR also teaches adjusting an actual well gas rate at each of the wells in the list of wells according to the determined adjusted well gas rate until the assigned target percent of the gas byproduct GURPINAR ([0166] “With respect to block 42e18, if your forecast shows that you do have sufficient volumes (gas rate) from your own site (rate at each of the wells in the list of wells), do you have sufficient capacity (until the assigned target percent of the gas byproduct) to handle those volumes (gas rate)? For example, if in the future the gas rates will be ten times (adjusting an actual well gas rate) what they are today, you can inject a gas today at today's gas rates but, in the future, do you have the ability to inject at ten times that rate (according to the determined adjusted well gas rate)?”) See also GURPINAR ([0162] “Therefore, it is necessary to set up an overlapping system of constraints on the well and reservoir that represent the conditions (the determined adjusted well gas rate) that exist out in the field. Then, allow the model to proceed and forecast, by itself, the following: when you impose these conditions (adjusting an actual well gas rate at each well in the list of wells), these are the kinds of oil and/or gas rates you will achieve.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of GURPINAR with VAN BERKEL as the references deal with a method for gas blend optimization. GURPINAR would modify VAN BERKEL by assigning a target percent of a gas byproduct for one or more parameters of interest in a desired gas blend. The benefits of doing so is used for optimizing an overall performance of a reservoir. (GURPINAR [Abstract]).
The combination of VAN BERKEL and GURPINAR does not explicitly teach based on the analyzed data, determining, by one or more computer processors, an effect of each well's contribution to the percent gas byproduct by in a total gas produced at a gas processing facility, wherein the gas processing facility is configured to process the gas collected from the plurality of wells.
However, CULLICK teaches teach based on the analyzed data, determining, by one or more computer processors, an effect of each well's contribution to the percent gas byproduct by in a total gas produced at a gas processing facility, wherein the gas processing facility is configured to process the gas collected from the plurality of wells CULLICK ([0006] “the present invention address these issues and others by providing for real-time oil and gas field production optimization using a proxy simulator. One illustrative embodiment includes a method for establishing a base model (based on the analyzed data) of a physical system in one or more physics-based simulators (determining, by one or more computer processor). The physical system may include a reservoir, a well, a pipeline network, and a processing system. The one or more simulators simulate the flow of fluids (an effect of each well' s contribution) in the reservoir, well, pipeline network, and a processing system (total gas produced). The method further includes using a decision management system to define control parameters (percent gas byproduct) of the physical system (gas processing facility) for matching (configured to process the gas collected) with observed data (based on the obtained data).”) See also CULLICK ([0020] “It should be understood that the computer system 2 for practicing embodiments of the invention may also be representative (determining by one or more computer processors) of other computer system configurations, including hand-held devices, multiprocessor systems (one or more computer processors), microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. Embodiments of the invention may also be practiced in distributed computing environments where tasks are performed (based on the analyzed data) by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.”) See also CULLICK ([0014] “Embodiments of the present invention may be generally employed in the operating environment 100 as shown in FIG. 1. The operating environment 100 includes oilfield surface facilities 102 and wells and subsurface flow devices 104. The oilfield surface facilities 102 may include any of a number of facilities typically used in oil and gas field production. These facilities may include, without limitation, drilling rigs, blow out preventers, mud pumps, and the like (an effect of each well's contribution). The wells and subsurface flow devices may include, without limitation, reservoirs, wells, and pipeline networks (and their associated hardware).” See also CULLICK ([0015] “The surface facilities 102 and the wells and subsurface flow devices 104 are in communication with field sensors 106, remote terminal units 108, and field controllers 110, in a manner know to those skilled in the art. The field sensors 106 measure various surface and sub-surface properties of an oilfield (i.e., reservoirs, wells, and pipeline networks) including, but not limited to, oil, gas, and water production rates, water injection, tubing head, and node pressures, valve settings at field, zone, and well levels (effect of each well' s contribution). See also CULLICK ([0003] “Data collected from the periodic measurements is analyzed (data analyzed) and used to make production decisions including optimizing future production.”)
CULLICK also teaches based on the identified effect of each well, selecting, by the one or more computer processors, a list of wells from the plurality of wells CULLICK ([0006] “The method further includes using a decision management system to define control parameters of the physical system for matching with observed data (based on the identified effect of each well). The control parameters may include (selecting, by the one or more computer processors) a valve setting for regulating the flow of water in a reservoir, well, pipeline network, or processing system… The method further includes eliminating the design parameters from the proxy model for which the sensitivities are below a threshold, using an optimizer with the proxy model to determine design parameter value ranges (selecting a list of wells from a plurality of wells based on the identified effect of each well), for the design parameters which were not eliminated from the proxy model, for which outputs from the neural network match observed data, the design parameters which were not eliminated then being designated as selected parameters, placing the selected parameters and their ranges from the proxy model into the decision management system, running the decision management system as a global optimizer to validate the selected parameters in the one or more simulators, and using the proxy model for real time optimization and control decisions with respect to the selected parameters over a future time period.”)
CULLICK also teaches optimizing, by the one or more computer processors, the percent of the gas byproduct in the total gas produced by determining an adjusted well gas rate for each of the wells in the list of wells until the assigned target rate is met CULLICK ([Abstract] “A base model of a reservoir, well, pipeline network, or processing system is established in one or more physical simulators (one or more computer processors).”) See also CULLICK [0037-0038] “Referring now to FIG. 4, a computer generated display of predicted optimal valve settings (percent of the gas byproduct) for a number of wells (each of the wells in the list of wells) which may be used to optimize (until the assigned target rate is met) the production of oil and gas over a future time period (the total gas produced) is shown, according to an illustrative embodiment of the present invention. As can be seen in FIG. 4, a number of graphs 410-490 generated by the DMS application 24 are displayed. Each graph represents a well location of a producing well in a field and an associated valve location for regulating the flow (until the assigned target rate is met) of a fluid ( e.g., water) into the well. For instance, graph 410 is a display of a well with a designation 415 of P1_9L1, where P1_9 is the well designation and L1 is the valve designation indicating the location of a valve in the well (i.e., "location 1").”) See also CULLICK ([Figure 4].)
PNG
media_image3.png
536
836
media_image3.png
Greyscale
CULLICK Figure 4 Reference
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of CULLICK with VAN BERKEL and GURPINAR as the references deal with a method for gas blend optimization. CULLICK would modify VAN BERKEL and GURPINAR by determining, by one or more computer processors, an effect of each well' s contribution to the one or more parameters of interest in a total gas produced at a gas processing facility, wherein the gas processing facility is configured to process the gas collected from the plurality of wells. The benefits of doing so improve decision making in controlling the operation of oil and gas fields by responding to data as the data is being measured. (CULLICK [0002]).
The combination of VAN BERKEL, GURPINAR, and CULLICK does not explicitly teach analyzing the data with a gas-chromatograph equipped with a mass-spectrometer.
However, KAWASE teaches analyzing the data with a gas-chromatograph equipped with a mass-spectrometer KAWASE ([Description] “System for managing multiple analysis data of sample using liquid chromatograph apparatus (LC) such as gas chromatography equipment (GC), liquid chromatograph mass spectrometer (gas-chromatograph equipped with a mass-spectrometer) (LC-MS), etc. Can also be used in gas chromatograph mass spectrometer (GC-MS), scanning electron microscope (SEM), transmission type electron microscope (TEM), energy dispersive X-ray fluorescence analyzer (EDX), wavelength dispersive fluorescent-X-ray-analysis apparatus (WDX), Fourier transform infrared spectrophotometer (FT-IR), photodiode array detector (LC-PDA), liquid chromatograph mass spectrometer, near-infrared spectroscopy apparatus, tension tester, compression tester, etc.”) See also KAWASE ([Description] “The complex analysis data management system 100 according to the present embodiment can be applied to a plurality of analyzer cross-analysis system for cross-sectionally analyzing analysis results (analyzing the data) by a plurality of types of analyzers.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of KAWASE with VAN BERKEL, GURPINAR, and CULLICK as the references deal with a method for gas blend optimization. KAWASE would modify VAN BERKEL, GURPINAR, and CULLICK by analyzing the data with a gas-chromatograph equipped with a mass-spectrometer. The benefits of doing so contribute to the realization of efficient and highly accurate analysis. (KAWASE [Description]). Accordingly, claim 1 is rejected based on the combination of these references.
Claim 8
Claim 8 is rejected because it is the system embodiment of claim 1, with similar limitations to claim 1, and is such rejected using the same reasoning found in claim 1.
VAN BERKEL does not explicitly teach an analytical module equipped to obtain and analyze well data from a plurality of wells in a geographical region of interest.
However, GURPINAR teaches an analytical module equipped to obtain well data from a plurality of wells in a geographical region of interest ([0024] “It is a further object of the present invention to disclose a method of managing a fluid and/or gas reservoir (an analytical module equipped to obtain well data), where the generating step (b) for generating an initial reservoir development plan from the initial reservoir characterization (well data from a plurality of wells)includes (b 1) performing either a numerical model studies step or an analytical model studies (analytical module) step, (b2) generating a production and reserves forecast (equipped to obtain well data from a plurality of wells) in response to the numerical model studies or the analytical model studies, (b3) generating facilities requirements from the production and reserves forecast, (b4) considering environmental issues (geographical region of interest) in response to the development and depletion strategies determined during step (al), (bS) performing an economics and risk analysis study while taking into account the environmental considerations (geographical region of interest), the production and reserves forecast (obtain well data from a plurality of wells), and the facilities requirements, and (b6) producing an optimized development plan in response to and in view of the economics and risk analysis.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of GURPINAR with VAN BERKEL as the references deal with a method for gas blend optimization. GURPINAR would modify VAN BERKEL by an analytical module equipped to obtain well data from a plurality of wells in a geographical region of interest. The benefits of doing so is used for optimizing an overall performance of a reservoir. (GURPINAR [Abstract]).
The combination of VAN BERKEL and GURPINAR does not explicitly teach one or more computer processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more computer processors perform operations.
However, CULLICK teaches one or more computer processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more computer processors perform operations CULLICK ([0007] “The computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process. The computer program product may also be a propagated signal on a carrier readable by a computing system and encoding a computer program of instructions for executing a computer process.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of CULLICK with VAN BERKEL and GURPINAR as the references deal with a method for gas blend optimization. CULLICK would modify VAN BERKEL and GURPINAR by determining, wherein one or more computer processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more computer processors perform operations. The benefits of doing so improve decision making in controlling the operation of oil and gas fields by responding to data as the data is being measured. (CULLICK [0002]). Accordingly, claim 8 is rejected based on the combination of these references.
Claim 15
Claim 15 is rejected because it is the non-transitory computer-readable media embodiment of claims 1 and 8, with similar limitations to claims 1 and 8, and is such rejected using the same reasoning found in claims 1 and 8.
Claim 9
Claim 9 is rejected because it is the system embodiment of claim 8, with similar limitations to claim 8, and is such rejected using the same reasoning found in claim 8.
GURPINAR also teaches wherein the one or more computer processors further perform an operation of electronically transmitting the list of wells to a user GURPINAR ([0007] “The system (one or more computer processors) provides the ability to predict the future flow profile of multiple wells (the list of wells) and to monitor and control the fluid or gas flow from either the formation into the wellbore, or from the wellbore to the surface. The control system is also capable of receiving and transmitting data (further perform an operation of electronically transmitting the list of wells) from multiple remote locations such as inside the borehole, to or from other platforms (to a user), or from a location away from any well site.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of GURPINAR with VAN BERKEL as the references deal with a method for gas blend optimization. GURPINAR would modify VAN BERKEL by one or more computer processors further perform an operation of electronically transmitting the list of wells to a user. The benefits of doing so is used for optimizing an overall performance of a reservoir. (GURPINAR [Abstract]). Accordingly, claim 9 is rejected based on the combination of these references.
Claim 3
Claim 3 is rejected because the combination of VAN BERKEL, GURPINAR, CULLICK, and KAWASE teaches claim 1.
VAN BERKEL teaches determining a new blend total parameter value for each selected well using the adjusted well gas rate VAN BERKEL ([Abstract] “new element is a compositional gas blending (determining a new blend) optimization model in the gas processing facilities. This is the main source of non-convexity and non-linearity in the overall optimization model and requires a choice of local and global optimizers to uncover high quality (total parameter value for each selected well) solutions. What optimizer to use depends on the structure and targets of the gas blending (determining a new blend total parameter value) problem. The produced oil and gas rates could be 10-20% below (using the adjusted well gas rate) the optimum, especially when using local optimizers like SLP and SQP.”)
VAN BERKEL also teaches based on the new blend total parameter value, determining if the assigned target percent of gas byproduct has been met VAN BERKEL ([Base Case Scenarios | pdf page 5 of 10] “Another scenario is to split the injection gas stream in two or three separate gas streams (based on the new blend) to study the effect of injecting gas with different compositions (based on the new blend) in each reservoir, see e.g. the abstracted gas blending models in Figures 4 and 5. Here mole weight constraints and targets are defined to achieve an optimum composition (determining if the assigned target percent of the gas byproduct) suitable for different reservoirs, given the available gas and its composition (based on the new blend total parameter value).”)
VAN BERKEL does not explicitly teach determining at least one well level constraint criterion determining at least one well level constraint criterion; for each well, determining a blend total parameter value; sorting the plurality of wells according to their blend total parameter values to obtain the list of wells; determining if a selected well meets the at least one well level constraint criterion; adjusting the well gas rate of the selected well when the well gas rate meets the at least one well level constraint criterion.
However, GURPINAR teaches determining at least one well level constraint criterion GURPINAR ([0089] “In FIG. 3, block 24A, the Geological Model 23 flows into the fluid flow simulator of block 31 which has a series of constraints (constraint criterion), block 32, applied thereto. Presumably, the fluid flow simulator 31 has been calibrated or history matched. Therefore, the fluid flow simulator 31, having the constraints 32 as an input, will produce a production forecast (determining at least one well level constraint criterion), block 34. The production forecast 34 also include: the facilities that have been added, the wells that have been drilled, and associated capital and operating costs which then flow into the Economic Modeling Package, block 35. From the Economic Modeling Package 35, the results obtained from the Economic Modeling Package 35 are examined, in the Optimization Criterion block 36, to determine how that case performed economically against your criteria (determining at least one well level constraint criterion) for selecting an economic process (which might include present value, rate of return, or a combination of the two, and risk). From the Optimization Criterion block 36, you would propose a method of changing the Development Plan in the Optimization Method block 37.”)
GURPINAR also teaches for each well, determining a blend total parameter value GURPINAR ([0159] “From the 'historic well performance trends' of block 42b3, you can also map, in the 'map displays of well performance indicators' block 42b7, several performance indicators such as peak well rates (for each well) or the total volumes of fluids (determining a blend total parameter value) produced from different well sites in order to examine which areas of a reservoir field are better or worse than average or better or worse than their companions.”)
GURPINAR also teaches sorting the plurality of wells according to their blend total parameter values to obtain the list of wells GURPINAR ([0035] “identifying any potential infill well opportunities (sorting the plurality of wells to obtain the list of wells) reflecting any opportunities to drill any infill wells (according to their blend total parameter values), (bl.6) if the disagreement does exist and there is total conformance, determining, in a volumetric and material balance fluids in place estimates step, how the well performance trends (according to their blend total parameter values) balance out with estimates of fluids in place and pressure support from material balance calculations, (bl.7) in response to the well production (according to their blend total parameter values) decline characteristics generating during the establishing step (bl.2),”)
GURPINAR also teaches determining if a selected well meets the at least one well level constraint criterion GURPINAR ([0029] “determining, in a relative permeability and capillary pressure saturation model (determining if a selected well meets), the flow characteristics of oil and gas and water when all exist simultaneously (at least one well level constraint criterion) in a reservoir (a4.10) investigating, in a single well or reservoir 'sector model', specific reservoir mechanisms (determining if a selected well meets) and the impact the mechanisms have (at least one well level constraint criterion) on a full field model design,.”)
GURPINAR also teaches adjusting the well gas rate of the selected well when the well gas rate meets the at least one well level constraint criterion GURPINAR ([0166] “With respect to block 42e18, if your forecast shows that you do have sufficient volumes from your own site, do you have sufficient capacity to handle those volumes? For example, if in the future the gas rates will be ten times what they are today (when the well gas rate meets the at least one well level constraint criterion), you can inject a gas today (adjusting the well gas rate of the selected well) at today's gas rates but, in the future, do you have the ability to inject at ten times that rate? If, in block 42e18, you do not have sufficient capacity, take the 'no' output from block 42e18 which leads us to the 'injectant treating expansion' block 42e19.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of GURPINAR with VAN BERKEL as the references deal with a method for gas blend optimization. GURPINAR would modify VAN BERKEL by adjusting the well gas rate of the selected well when the well gas rate meets the at least one well level constraint criterion. The benefits of doing so is used for optimizing an overall performance of a reservoir. (GURPINAR [Abstract]). Accordingly, claim 3 is rejected based on the combination of these references.
Claim 10
Claim 10 is rejected because it is the system embodiment of claim 3, with similar limitations claim 3, and is such rejected using the same reasoning found in claim 3.
Claim 16
Claim 16 is rejected because it is the non-transitory computer-readable media embodiment of claim 3, with similar limitations claim 3, and is such rejected using the same reasoning found in claim 3.
Claim 4
Claim 4 is rejected because the combination of VAN BERKEL, GURPINAR, CULLICK, and KAWASE teaches claim 3.
VAN BERKEL teaches wherein the blend total parameter value is determined based on a well level parameter value of the gas byproduct, a well gas rate, and a total gas rate VAN BERKEL ([Abstract] “The surface facilities 102 and the wells and subsurface flow devices 104 are in communication with field sensors 106, remote terminal units 108, and field controllers 110, in a manner know to those skilled in the art. The field sensors 106 measure various surface and sub-surface properties (blend total parameter value) of an oilfield (i.e., reservoirs, wells (well gas rate), and pipeline networks) including, but not limited to, oil, gas (total gas rate), and water production rates (well level parameter value), water injection, tubing head, and node pressures, valve settings at field, zone, and well levels (well level parameter value). In one embodiment of the invention, the field sensors 106 are capable of taking continuous measurements in an oilfield and communicating data in real-time to the remote terminal units 108.”) See also VAN BERKEL ([Base case scenarios] “The first gas injection project that obtained its Final Investment Decision (FID) has been studied in detail using different scenarios. This is a gas flood of two reservoirs and primary depletion of all the others. The produced gas is split into a sales gas and a single injection gas stream (well level parameter value), with the latter enriched by the CO2 and H2S (gas byproduct) separated from the sales gas. The small amount of richer gas produced in the 2nd to 5th stage separators is also added to the injection stream. A detailed surface facilities model in HFPT is shown in Figure 6. The gas blending model resembles the abstracted model with the single gas injection stream, see Figure 3.”)
Claim 11
Claim 11 is rejected because it is the system embodiment of claim 4, with similar limitations claim 4, and is such rejected using the same reasoning found in claim 4.
Claim 17
Claim 17 is rejected because it is the non-transitory computer-readable media embodiment of claim 4, with similar limitations claim 4, and is such rejected using the same reasoning found in claim 4.
Claim 5
Claim 5 is rejected because the combination of VAN BERKEL, GURPINAR, CULLICK, and KAWASE teaches claim 3.
Claim 5 is rejected because VAN BERKEL teaches determining a correction factor for the gas byproduct to correct for different operating conditions between each well and the gas processing facility and applying the determined correction factor to the blend total parameter value VAN BERKEL ([Introduction] “A large number of gas and oil fields (between each well and the gas processing facility) are contaminated (gas byproduct) by significant amounts of CO2 and H2S (determining a correction factor). Separation of CO2 and H2S from the hydrocarbon gas stream is expensive and leads to disposal problems. However, one way to use these contaminants is to re-inject them back into the oil reservoirs (applying the determined a correction factor) for enhanced oil recovery (to correct for different operating conditions) (EOR) by miscible gas flooding, which can result in very high recovery factors. Depending on the requirements of individual reservoirs for miscible conditions, the extracted H2S and CO2 (gas byproduct) can be blended in various ratios (blend total parameter value) with produced sour hydrocarbon gas (gas byproduct).”)
Claim 12
Claim 12 is rejected because it is the system embodiment of claim 5, with similar limitations claim 5, and is such rejected using the same reasoning found in claim 5.
Claim 18
Claim 18 is rejected because it is the non-transitory computer-readable media embodiment of claim 5, with similar limitations claim 5, and is such rejected using the same reasoning found in claim 5.
Claim 6
Claim 6 is rejected because the combination of VAN BERKEL, GURPINAR, and CULLICK teaches claim 4.
VAN BERKEL does not explicitly teach the blend total parameter value is determined according to the following:
PNG
media_image4.png
77
1046
media_image4.png
Greyscale
However, GURPINAR teaches the blend total parameter value is determined according to the following:
PNG
media_image4.png
77
1046
media_image4.png
Greyscale
GURPINAR ([0166] “With respect to block 42e18, if your forecast shows that you do have sufficient volumes (well level parameter value) from your own site, do you have sufficient capacity (total gas rate) to handle those volumes? For example, if in the future the gas rates (well gas rate) will be ten times what they are today, you can inject a gas (well level parameter value) today at today's gas rates (well gas rates) but, in the future, do you have the ability to inject at ten times (total gas rate) that rate?
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of GURPINAR with VAN BERKEL as the references deal with a method for gas blend optimization. GURPINAR would modify VAN BERKEL by calculating a blend total parameter based on gas rates, total gas rates, and well level parameter values. The benefits of doing so is used for optimizing an overall performance of a reservoir. (GURPINAR [Abstract]). Accordingly, claim 6 is rejected based on the combination of these references.
Claim 13
Claim 13 is rejected because it is the system embodiment of claim 6, with similar limitations claim 6, and is such rejected using the same reasoning found in claim 6.
Claim 19
Claim 19 is rejected because it is the non-transitory computer-readable media embodiment of claim 6, with similar limitations claim 6, and is such rejected using the same reasoning found in claim 6.
Claim 7
Claim 7 is rejected because the combination of VAN BERKEL, GURPINAR, and CULLICK teaches claim 3.
VAN BERKEL teaches sorting the plurality of wells in a descending order based on their blend total parameter values to obtain a first list of wells VAN BERKEL ([Field Case | pdf page 2 of 10] “In 2006, compositional HFPT was greatly improved by simplifying input options, by using network optimizers that can handle gas blending problems in distribution networks, and by incorporating compositional decline curves for suitable reservoirs under primary depletion, removing redundant full field MoReS reservoir models. Also, all the scripting language was removed. This made the tool much easier to use, fully auditable, thereby guaranteeing a high level of quality assurance, and very suitable for long-term planning and forecasting.
VAN BERKEL also teaches increasing the well gas rates of wells in the first list that meet the at least one well level constraint criterion by a value VAN BERKEL ([Base Case Scenarios | pdf page 5 of 10] “Oil production rates of the various reservoirs are shown in Figure 7. When a reservoir is gas flooded, the oil production increases and remains high for some period.”)
VAN BERKEL does not explicitly teach sorting the plurality of wells in an ascending order based on their blend total parameter values to obtain a second list of wells or decreasing the well gas rates of wells in the second list that meet the at least one well level constraint criterion by the value.
However, GURPINAR teaches sorting the plurality of wells in an ascending order based on their blend total parameter values to obtain a second list of wells; GURPINAR ([0035] “(bl.3) from the historic well performance trends, mapping, in map displays of well performance indicators (sorting the plurality of wells in an ascending order), several performance indicators such as the total volumes of fluids (based on their blend total parameter values) at different well sites (to obtain a second list of wells) in order to examine which areas of a reservoir field are better or worse than average or better or worse than their companions wells at the different well sites.”)
GURPINAR also teaches decreasing the well gas rates of wells in the second list that meet the at least one well level constraint criterion by the value GURPINAR ([0035] “(bl.2) from plots of production trends (in the second list) in the historic well performance trends, establishing a set of decline characteristics (decreasing the well gas rates of wells) or a set of productivity characteristics (at least one well level constraint criterion by the value) of the reservoir field thereby generating well production decline characteristics which forecasts future performance trends from existing wells.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of GURPINAR with VAN BERKEL as the references deal with a method for gas blend optimization. GURPINAR would modify VAN BERKEL by decreasing the well gas rates of wells in the second list that meet the at least one well level constraint criterion by the value. The benefits of doing so is used for optimizing an overall performance of a reservoir. (GURPINAR [Abstract]). Accordingly, claim 7 is rejected based on the combination of these references.
Claim 14
Claim 14 is rejected because it is the system embodiment of claim 7, with similar limitations claim 7, and is such rejected using the same reasoning found in claim 7.
Claim 20
Claim 20 is rejected because it is the non-transitory computer-readable media embodiment of claim 7, with similar limitations claim 7, and is such rejected using the same reasoning found in claim 7
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARTIN K VU whose telephone number is (703)756-5944. The examiner can normally be reached 7:30 am to 4:30 pm M-F.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Renee Chavez can be reached on 571-270-1104. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/M.K.V./Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186
Prosecution Insights