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 .
Status of Claims
The following is a non-final, first office action in response to the communication filed on 01/02/2025. Claims 1—20 are currently pending.
Information Disclosure Statement
Information Disclosure Statement received 01/17/2025 and 06/26/2026 have been reviewed and considered.
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.
Step 1 of the USPTO’s eligibility 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.
Claims 1, 11, and 16 are directed to a method (process), a system (machine or manufacture), and a system (machine or manufacture), respectively. As such, the claims are directed to statutory categories of invention.
If the claim recites a statutory category of invention, the claim requires further analysis in Step 2A. Step 2A of the 2019 Revised Patent SUBJECT Matter Eligibility Guidance is a two-prong inquiry. In Prong One, examiners evaluate whether the claim recites a judicial exception
Claim 1 recites the following abstract ideas:
“monitoring, based on one or more physics-based models, the field data to detect one or more anomalies in the field data” (e.g., mental process and/or mathematical concept); and
“detecting the one or more anomalies in the field data” (e.g., recited as a conditional limitation; however it would be a mental process and/or mathematical concept if positively recited).
Claim 11 recites the following abstract ideas:
“monitoring, based on one or more physics-based models, the field data to detect one or more anomalies in the field data” (e.g., mental process and/or mathematical concept); and
“detecting the one or more anomalies in the field data” (e.g., recited as a conditional limitation; however it would be a mental process and/or mathematical concept if positively recited).
Claim 16 recites the following abstract ideas:
“monitoring, based on one or more physics-based models, the field data to detect one or more anomalies in the field data” (e.g., mental process and/or mathematical concept); and
“detecting the one or more anomalies in the field data” (e.g., recited as a conditional limitation; however it would be a mental process and/or mathematical concept if positively recited).
Under the broadest reasonable interpretation, the above identified limitations cover abstract ideas directed to mental processes, mathematical concepts, and/or combinations thereof. For example, actions such as “monitoring, based on one or more physics-based models, the field data to detect…” and “detecting the one or more anomalies in the field data” constitute processes which may be performed in a human mind with or without the benefit of a mathematical concept or may be directed to a mathematical concept without a mental process.
The MPEP states the following regarding mental processes:
“[t]he courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’… Accordingly, the ‘mental processes’ abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions. A discussion of concepts performed in the human mind, as well as concepts that cannot practically be performed in the human mind and thus are not ‘mental processes’, is provided below with respect to point A.” (MPEP 2106.04(a)(2), Section III).
Furthermore, the MPEP states the following regarding mathematical calculations:
“[a] claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the ‘mathematical concepts’ grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word ‘calculating’ in order to be considered a mathematical calculation. For example, a step of ‘determining’ a variable or number using mathematical methods or ‘performing’ a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.” (MPEP 2106.04(a)(2), Section I, Subsection C).
Accordingly, the above identified limitations are directed to abstract ideas such that claims 1, 11, and 16 recite abstract ideas.
If the claim recites a judicial exception (i.e., an abstract idea enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance, a law of nature, or a natural phenomenon), the claim requires further analysis in Prong Two. In Prong Two, examiners evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
Claim 1 recites additional elements of:
“obtaining, from one or more sensors, field data…” (e.g., extra-solution activity directed to mere/necessary data gathering);
“… a drilling operation of a wellbore…” (e.g., a field of use);
“… wherein the field data comprises drilling data of a drill bit used to drill the wellbore and logging data of the wellbore” (e.g., extra-solution activity directed to selecting data by source or content); and
“sending a warning signal to check the one or more sensors” (e.g., a conditional limitation directed to mere directive to apply the identified judicial exceptions).
Claim 11 recites additional elements of:
“obtaining, from one or more sensors, field data…” (e.g., extra-solution activity directed to mere/necessary data gathering);
“… a drilling operation of a wellbore…” (e.g., a field of use);
“… wherein the field data comprises drilling data of a drill bit used to drill the wellbore and logging data of the wellbore” (e.g., extra-solution activity directed to selecting data by source or content); and
“sending a warning signal to check the one or more sensors” (e.g., a conditional limitation directed to mere directive to apply the identified judicial exceptions).
Claim 16 recites additional elements of:
“one or more computers” (e.g., reciting generic computer elements is equivalent to a mere directive to apply the exception);
“one or more computer memory devices” (e.g., reciting generic computer elements is equivalent to a mere directive to apply the exception);
“obtaining, from one or more sensors, field data…” (e.g., extra-solution activity directed to mere/necessary data gathering);
“… a drilling operation of a wellbore…” (e.g., a field of use);
“… wherein the field data comprises drilling data of a drill bit used to drill the wellbore and logging data of the wellbore” (e.g., extra-solution activity directed to selecting data by source or content); and
“sending a warning signal to check the one or more sensors” (e.g., a conditional limitation directed to mere directive to apply the identified judicial exceptions).
The above identified limitations of claims 1, 11, and 16 constitute additional elements. However, for the reasons identified above, and discussed further below, the additional elements do not impose any meaningful limits on practicing the abstract idea. Accordingly, in combination, the above identified additional elements do not integrate the identified judicial exceptions into a practical application.
If the additional elements 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 to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
As identified above, claims 1, 11, and 16 recite the additional element of “obtaining, from one or more sensors, field data.” However, this additional element is directed to extra-solution activity constituting mere data gathering which cannot provide for a practical application of the identified judicial exceptions. For example, the MPEP states “[t]he term "extra-solution activity" can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process, e.g., a step of obtaining information about credit card transactions, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps in order to detect whether the transactions were fraudulent.” (MPEP 2106.05(g)). The MPEP further states “[b]elow are examples of activities that the courts have found to be insignificant extra-solution activity: Mere Data Gathering: i. Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989); ii. Testing a system for a response, the response being used to determine system malfunction, In re Meyers, 688 F.2d 789, 794; 215 USPQ 193, 196-97 (CCPA 1982)” (MPEP 2106.05(g)). Accordingly, the limitations directed to the insignificant extra-solution activity of data gathering cannot provide for a practical application of the identified judicial exceptions.
As identified above, claims 1, 11, and 16 recite the additional element of “a drilling operation of a wellbore.” However, this additional element is merely directed to a field of use in which the judicial exceptions are applied which cannot provide for a practical application of the judicial exceptions. For example, the MPEP states “[a]s explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.” (MPEP 2106.05(h)). Accordingly, the limitations which restrict the field of use of the identified judicial exceptions to “a drilling operation of a wellbore” cannot provide for a practical application of the identified judicial exceptions.
As identified above, claims 1, 11, and 16 recite the additional element of “wherein the field data comprises drilling data of a drill bit used to drill the wellbore and logging data of the wellbore.” However, this additional element is directed to extra-solution activity constituting selecting data by source or content which cannot provide for a practical application of the identified judicial exceptions. For example, the MPEP states “[b]elow are examples of activities that the courts have found to be insignificant extra-solution activity:… Selecting a particular data source or type of data to be manipulated: i. Limiting a database index to XML tags, Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d at 1328-29, 121 USPQ2d at 1937;… iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).” (MPEP 2106.05(g)). Accordingly, the limitations directed to the insignificant extra-solution activity of selecting a particular data source cannot provide for a practical application of the identified judicial exceptions.
As identified above, claims 1, 11, and 16 recite the additional element of “sending a warning signal to check the one or more sensors.” Examiner notes this limitation is part of a conditional limitation and does not currently carry any weight in the claim; however, for the sake of completeness the limitation is addressed herein. The limitation directed to sending a warning signal constitutes a mere directive to apply an exception (e.g., “apply it”) which cannot provide for a practical application of the identified judicial exceptions. For example, the MPEP states “[w]hen determining whether a claim simply recites a judicial exception with the words ‘apply it’ (or an equivalent), such as mere instructions to implement an abstract idea on a computer, examiners may consider the following: (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words ‘apply it’. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015). In contrast, claiming a particular solution to a problem or a particular way to achieve a desired outcome may integrate the judicial exception into a practical application or provide significantly more. See Electric Power, 830 F.3d at 1356, 119 USPQ2d at 1743.” (MPEP 2106.05(f)).
With respect to the limitation directed to the warning signal, the limitations of claims 1, 11, and 16 are merely directed to the idea of a solution or outcome and do not properly integrate the judicial exception into a practical application. Examples of limitations which do properly integrate the recited judicial exception into a practical application include the limitations of Diehr. For example, the MPEP states “[i]n contrast, the additional elements in Diamond v. Diehr as a whole provided eligibility and did not merely recite calculating a cure time using the Arrhenius equation ‘in a rubber molding process’. Instead, the claim in Diehr recited specific limitations such as monitoring the elapsed time since the mold was closed, constantly measuring the temperature in the mold cavity, repetitively calculating a cure time by inputting the measured temperature into the Arrhenius equation, and opening the press automatically when the calculated cure time and the elapsed time are equivalent. 450 U.S. at 179, 209 USPQ at 5, n. 5. These specific limitations act in concert to transform raw, uncured rubber into cured molded rubber. 450 U.S. at 177-78, 209 USPQ at 4.” (MPEP 2106.05(h)). Accordingly, the limitations of Diehr which integrated the abstract idea (e.g., calculations using the Arrhenius equation) into a practical application (e.g., opening the press automatically once the calculated cure time and elapsed time are equivalent) provided a more specific application which was directly tied to the outcome of the judicial exception than that of the instant claims. For example, Diehr did not merely state “sending a signal to the press when the calculated cure time and elapsed cure time are equivalent.” Accordingly the limitations of claims 1, 11, and 16 do not provide for a practical application of the judicial exception because the limitations are equivalent to a mere directive to apply the exception.
As identified above, claim 16 recites limitations directed to generic computer components including “one or more computers” and “one or more computer memory devices.” While such limitation constitute additional elements, they do not provide for a practical application of the judicial exceptions because mere recitation of generic computer elements is equivalent to a directive to apply the exception (e.g., “apply it”). For example, the MPEP states “[w]hen determining whether a claim simply recites a judicial exception with the words ‘apply it’ (or an equivalent), such as mere instructions to implement an abstract idea on a computer, examiners may consider the following… (2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, ‘claiming the improved speed or efficiency inherent with applying the abstract idea on a computer’ does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).” (MPEP 2106.05(f), Section 2). Accordingly the limitations of claim 16 does not provide for a practical application of the judicial exception because the limitations are equivalent to a mere directive to apply the exception.
Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e., an inventive concept) to the abstract idea.
The limitations of claims 2, 12, and 17 function to further define the physics-based models (e.g., directed to an abstract idea) of claims 1, 11, and 16 and therefore are directed to an abstract idea (e.g., mental process and/or mathematical concept). The claims do not recite any limitations which provide for additional elements which function to integrate the abstract ideas into a practical application.
The limitations of claims 3, 13, and 18 function to further define the data set used in association with the above identified abstract ideas and are therefore directed to extra-solution activity constituting selecting data by source or content which cannot provide for a practical application of the identified judicial exceptions. For example, the MPEP states “[b]elow are examples of activities that the courts have found to be insignificant extra-solution activity:… Selecting a particular data source or type of data to be manipulated: i. Limiting a database index to XML tags, Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d at 1328-29, 121 USPQ2d at 1937;… iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).” (MPEP 2106.05(g)). Accordingly, the limitations directed to the insignificant extra-solution activity of selecting a particular data source cannot provide for a practical application of the identified judicial exceptions.
The limitations of claims 4, 14, and 19 function to further define the data set used in association with the above identified abstract ideas and are therefore directed to extra-solution activity constituting selecting data by source or content which cannot provide for a practical application of the identified judicial exceptions. For example, the MPEP states “[b]elow are examples of activities that the courts have found to be insignificant extra-solution activity:… Selecting a particular data source or type of data to be manipulated: i. Limiting a database index to XML tags, Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d at 1328-29, 121 USPQ2d at 1937;… iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).” (MPEP 2106.05(g)). Accordingly, the limitations directed to the insignificant extra-solution activity of selecting a particular data source cannot provide for a practical application of the identified judicial exceptions.
The limitations of claims 5, 15, and 20 function to further define the data set used in association with the above identified abstract ideas and are therefore directed to extra-solution activity constituting selecting data by source or content which cannot provide for a practical application of the identified judicial exceptions. For example, the MPEP states “[b]elow are examples of activities that the courts have found to be insignificant extra-solution activity:… Selecting a particular data source or type of data to be manipulated: i. Limiting a database index to XML tags, Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d at 1328-29, 121 USPQ2d at 1937;… iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).” (MPEP 2106.05(g)). Accordingly, the limitations directed to the insignificant extra-solution activity of selecting a particular data source cannot provide for a practical application of the identified judicial exceptions.
Claims 6, 7, and 9 recite multiple limitations directed to “determining” where making determinations constitutes an abstract idea further comprising either a mental process, a mathematical concept, or combinations thereof. Accordingly the limitations of claims 6, 7, and 9 are directed to an abstract idea for the same reasons as set forth above with respect to claim 1 (e.g., see citations to MPEP 2106.04(a)(2)).
Claims 8 and 10 recites multiple limitations directed to “determining” and “predicting” where making determinations and predictions constitutes an abstract idea further comprising either a mental process, a mathematical concept, or combinations thereof. Accordingly the limitations of claims 8 and 10 are directed to an abstract idea for the same reasons as set forth above with respect to claim 1 (e.g., see citations to MPEP 2106.04(a)(2)).
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 5, 11, 15, 16, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Published US Patent Application to Zhang et al., hereinafter “Zhang” (US 20190323323 A1).
Regarding claim 1, Zhang discloses [a] computer-implemented method, comprising:
obtaining, from one or more sensors (downhole sensors 37 and surface sensors 17), field data measured during a drilling operation (downhole measurements 45 and surface measurements 55; para. [0031], “[d]ownhole measurements 45 may be taken by sensors and tools underground within or around wells 125, along with surface measurements 55 taken at the surface, with such measurements including flow rates, temperature, pressure, fluid composition, hydrocarbon composition, and other various parameters of interest.”) of a wellbore, wherein the field data comprises drilling data of a drill bit used to drill the wellbore and logging data of the wellbore (para. [0042], “[d]ownhole measurements 45 such as from the logging tools 156, performance of the tool or drilling device, data collected by computing device 150, along with surface measurements 55 may be provided to the data aggregator unit 50 along with any surface measurements.”);
monitoring, based on one or more physics-based models (physics-based models 70; para. [0032], “[t]he initial inputs to the physics-based models 70 and data-driven models 75 may be related to an oilfield condition, including collected measured data from downhole measurements 45, surface measurements 55 as well as historical data 60 about an oilfield, or other oilfield related parameters necessary for processing the models, and/or estimated physical and hyper-physical parameters.”), the field data to detect one or more anomalies in the field data (para. [0032], “[a]fter the initial processing by either of the models, the input parameters may include outputs from one or both of the physics-based models 70 and data-driven models 75 to the other of the models. Furthermore, after an output is obtained from one or both of the models, the output can be compared to the measured data from the oilfield.”; para. [0053], “[t]he present disclosure provides for detecting abnormal measured parameters to monitor the status of sensors and equipment. One illustrated embodiment is provided for in flow diagram 400 shown in FIG. 4. In this embodiment, a physics-based model, which may contain sub-models, sets a range for the values.”).
Examiner notes the limitation “in response to detecting the one or more anomalies in the field data, sending a warning signal to check the one or more sensors,” constitutes a conditional limitation and is not required to be performed in order for the claim to be performed. Accordingly the claim is fully rejected without consideration for this limitation.
Regarding claim 5, Zhang discloses wherein the logging data comprises logging while drilling (LWD) data of the wellbore obtained during the drilling operation of the wellbore (para. [0039], “[w]ith respect to downhole measurements, logging tools 156 can be integrated into the bottom-hole assembly 152 near the drill bit 148. As the drill bit 148 extends the wellbore 144 through the formations 146, logging tools 156 collect measurements relating to various formation properties as well as the orientation of the tool and various other drilling conditions.”).
Regarding claim 11, Zhang discloses [a] non-transitory computer-readable medium storing one or more instructions executable by a computer system (para. [0076], “[e]mbodiments within the scope of the present disclosure may also include tangible and/or non-transitory computer-readable storage devices for carrying or having computer-executable instructions or data structures stored thereon.”) to perform operations comprising:
obtaining, from one or more sensors (downhole sensors 37 and surface sensors 17), field data measured during a drilling operation (downhole measurements 45 and surface measurements 55; para. [0031], “[d]ownhole measurements 45 may be taken by sensors and tools underground within or around wells 125, along with surface measurements 55 taken at the surface, with such measurements including flow rates, temperature, pressure, fluid composition, hydrocarbon composition, and other various parameters of interest.”) of a wellbore, wherein the field data comprises drilling data of a drill bit used to drill the wellbore and logging data of the wellbore (para. [0042], “[d]ownhole measurements 45 such as from the logging tools 156, performance of the tool or drilling device, data collected by computing device 150, along with surface measurements 55 may be provided to the data aggregator unit 50 along with any surface measurements.”);
monitoring, based on one or more physics-based models (physics-based models 70; para. [0032], “[t]he initial inputs to the physics-based models 70 and data-driven models 75 may be related to an oilfield condition, including collected measured data from downhole measurements 45, surface measurements 55 as well as historical data 60 about an oilfield, or other oilfield related parameters necessary for processing the models, and/or estimated physical and hyper-physical parameters.”), the field data to detect one or more anomalies in the field data (para. [0032], “After the initial processing by either of the models, the input parameters may include outputs from one or both of the physics-based models 70 and data-driven models 75 to the other of the models. Furthermore, after an output is obtained from one or both of the models, the output can be compared to the measured data from the oilfield.”; para. [0053], “[t]he present disclosure provides for detecting abnormal measured parameters to monitor the status of sensors and equipment. One illustrated embodiment is provided for in flow diagram 400 shown in FIG. 4. In this embodiment, a physics-based model, which may contain sub-models, sets a range for the values.”).
Examiner notes the limitation “in response to detecting the one or more anomalies in the field data, sending a warning signal to check the one or more sensors,” constitutes a conditional limitation and is not required to be performed in order for the claim to be performed. Accordingly the claim is fully rejected without consideration for this limitation.
Regarding claim 15, Zhang discloses wherein the logging data comprises logging while drilling (LWD) data of the wellbore obtained during the drilling operation of the wellbore (para. [0039], “[w]ith respect to downhole measurements, logging tools 156 can be integrated into the bottom-hole assembly 152 near the drill bit 148. As the drill bit 148 extends the wellbore 144 through the formations 146, logging tools 156 collect measurements relating to various formation properties as well as the orientation of the tool and various other drilling conditions.”).
Regarding claim 16, Zhang discloses one or more computers (para. [0065], “computing device 1000 includes a processing unit (CPU or processor) 1010 and a system bus 1005 that couples various system components including the system memory 1015 such as read only memory (ROM) 1020 and random access memory (RAM) 1035 to the processor 1010.”); and
one or more computer memory devices interoperably coupled with the one or more computers (para. [0065], “computing device 1000 includes a processing unit (CPU or processor) 1010 and a system bus 1005 that couples various system components including the system memory 1015 such as read only memory (ROM) 1020 and random access memory (RAM) 1035 to the processor 1010.”) and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, cause the computer-implemented system to perform one or more operations comprising (para. [0076], “[e]mbodiments within the scope of the present disclosure may also include tangible and/or non-transitory computer-readable storage devices for carrying or having computer-executable instructions or data structures stored thereon.”):
obtaining, from one or more sensors (downhole sensors 37 and surface sensors 17), field data measured during a drilling operation (downhole measurements 45 and surface measurements 55; para. [0031], “[d]ownhole measurements 45 may be taken by sensors and tools underground within or around wells 125, along with surface measurements 55 taken at the surface, with such measurements including flow rates, temperature, pressure, fluid composition, hydrocarbon composition, and other various parameters of interest.”) of a wellbore, wherein the field data comprises drilling data of a drill bit used to drill the wellbore and logging data of the wellbore (para. [0042], “[d]ownhole measurements 45 such as from the logging tools 156, performance of the tool or drilling device, data collected by computing device 150, along with surface measurements 55 may be provided to the data aggregator unit 50 along with any surface measurements.”);
monitoring, based on one or more physics-based models (physics-based models 70; para. [0032], “[t]he initial inputs to the physics-based models 70 and data-driven models 75 may be related to an oilfield condition, including collected measured data from downhole measurements 45, surface measurements 55 as well as historical data 60 about an oilfield, or other oilfield related parameters necessary for processing the models, and/or estimated physical and hyper-physical parameters.”), the field data to detect one or more anomalies in the field data (para. [0032], “After the initial processing by either of the models, the input parameters may include outputs from one or both of the physics-based models 70 and data-driven models 75 to the other of the models. Furthermore, after an output is obtained from one or both of the models, the output can be compared to the measured data from the oilfield.”; para. [0053], “[t]he present disclosure provides for detecting abnormal measured parameters to monitor the status of sensors and equipment. One illustrated embodiment is provided for in flow diagram 400 shown in FIG. 4. In this embodiment, a physics-based model, which may contain sub-models, sets a range for the values.”).
Examiner notes the limitation “in response to detecting the one or more anomalies in the field data, sending a warning signal to check the one or more sensors,” constitutes a conditional limitation and is not required to be performed in order for the claim to be performed. Accordingly the claim is fully rejected without consideration for this limitation.
Regarding claim 20, Zhang discloses wherein the logging data comprises logging while drilling (LWD) data of the wellbore obtained during the drilling operation of the wellbore (para. [0039], “[w]ith respect to downhole measurements, logging tools 156 can be integrated into the bottom-hole assembly 152 near the drill bit 148. As the drill bit 148 extends the wellbore 144 through the formations 146, logging tools 156 collect measurements relating to various formation properties as well as the orientation of the tool and various other drilling conditions.”).
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.
Claim(s) 2, 6, 10, 12, and 17 and is/are rejected under 35 U.S.C. 103 as being unpatentable over Published US Patent Application to Zhang et al., hereinafter “Zhang” (US 20190323323 A1) as applied to claims 1, 11, and 16 above, and further in view of Published US Patent Application to Jain et al., hereinafter “Jain” (US 20190345809 A1).
While Zhang discloses physics-based models used for drilling operations (e.g., see physics-based models 70/210/310/405 throughout), Zhang may not explicitly disclose the specific physics-based models recited in claim 2. Jain, which is in the same field of endeavor as the instant application insofar as it is directed models used in drilling operations, teaches the deficient limitations. For example, Jain teaches wherein the one or more physics-based models comprise at least one of a geomechanics model (rock mechanical properties model 304, FIG. 3A), a drill bit wear model (bit mechanics model 318 and bit wear model 320, FIG 3A and FIG. 4B), or a drilling rate of penetration (ROP) model (ROP Limiters Model 322, FIG. 3A and FIG 4B). Furthermore, Jain at para. [0003] teaches “[c]onventional methods of predicting and optimizing bit performance utilize physics-based models during pre-well planning,” which underscores that the above cited physics-based models are conventionally used in wellbore planning.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited physics-based models of Zhang with the specific physics-based models of Jain. The specific physics-based models of Jain where known in the art where the models are described by Jain as being “conventional methods” as identified above. The resulting combination would generate the predictable result of providing for specific physics-based model to describe the performance of the drilling operation.
Regarding claim 6, while Zhang discloses a method of detecting abnormal measured parameters to monitor the status of sensors and equipment using a physics-based model, Zhang may not explicitly tie those determinations to a specific physics-based model such as a geomechanics model. For example, Zhang discloses determining, based on [the physics-based] model and the field data, one or more properties [related to the physics-based model] of the wellbore (para. [0032], “[a]fter the initial processing by either of the models, the input parameters may include outputs from one or both of the physics-based models 70 and data-driven models 75 to the other of the models. Furthermore, after an output is obtained from one or both of the models, the output can be compared to the measured data from the oilfield.”; para. [0054], “the method begins with processing of a physics-based model 405. In this instance, the input into the physics-based model and any sub-models may include estimated hyper-physical parameters, and/or may include measured oilfield conditions or parameters, and/or be outputs from previous physics-based or data-driven models, or other inputs. Real-time measurements 410 in an oilfield are made of various oilfield conditions via various sensors, tools and other data gathering instruments. A physics-based model 405 defines an acceptable range 415 of values for these collected real-time measurements 410.”);
determining that at least one of the one or more properties [related to the physics-based model] of the wellbore is outside a predetermined range (para. [0053], “[t]he present disclosure provides for detecting abnormal measured parameters to monitor the status of sensors and equipment. One illustrated embodiment is provided for in flow diagram 400 shown in FIG. 4. In this embodiment, a physics-based model, which may contain sub-models, sets a range for the values.”; para. [0055], “[o]ut of range values 420 may be considered as incorrect, as not representative of measurements or data that are correct or able to occur in the real world, and so may be indicative of some type of problem. These out of range values 420 are fed to a data-driven model 425. The data driven model 425 may process the frequency, trend and severity of the out of range values 420 for various real world event failures 430 which may result from such values being out of range. These real world event failures may include sensor failures, equipment failures, process failures, among other failures.”)
Zhang further discloses “[a]s the drill bit 148 extends the wellbore 144 through the formations 146, logging tools 156 collect measurements relating to various formation properties as well as the orientation of the tool and various other drilling conditions.” (Zhang, para. [0039]). However, Zhang may not expressly state that the physics-based model which is used is a geomechanical rock model. Jain, which is in the same field of endeavor as the instant application insofar as it is directed models used in drilling operations, teaches the deficient limitations. For example, Jain teaches “[i]n some embodiments, the hybrid model includes one or more physics models, which include drill bit mechanics simulation models (“mechanics models”). The mechanics models include detailed three-dimensional geometry descriptions, rock failure models, cutter wear progression models, cutter fracture criteria, and other phenomena that affect wear and rate of penetration of an earth-boring tool. As will be appreciated by one of ordinary skill in the art, the foregoing models may be developed over a relatively long period of time (e.g., several years) based on theory and laboratory experimentation.” (para. [0028]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited physics-based models of Zhang with the specific physics-based models of Jain. The specific model of Jain would directly replace the generic model of Zhang in the specific workflow of Zhang as provided above. Furthermore, Jain at para. [0003] teaches “[c]onventional methods of predicting and optimizing bit performance utilize physics-based models during pre-well planning,” which underscores that the above cited physics-based models are conventionally used in wellbore planning. The specific physics-based models of Jain where known in the art where the models are described by Jain as being “conventional methods” as identified above. The resulting combination would generate the predictable result of providing for specific physics-based model to describe the performance of the drilling operation as used in the method outlined by Zhang.
Examiner notes the limitation “in response to determining that at least one of the one or more properties of rock formation of the wellbore is outside the predetermined range, determining that at least one of the one or more anomalies exists in the field data,” constitutes a conditional limitation and is not required to be performed in order for the claim to be performed. Accordingly the claim is fully rejected without consideration for this limitation.
Regarding claim 10, while Zhang discloses a method of detecting abnormal measured parameters to monitor the status of sensors and equipment using a physics-based model, Zhang may not explicitly tie those determinations to a specific physics-based model such as a geomechanics model. For example, Zhang discloses predicting, based on the [physics-based model] and the drilling data of the drill bit, [an output of the physics-based model] (para. [0032], “[a]fter the initial processing by either of the models, the input parameters may include outputs from one or both of the physics-based models 70 and data-driven models 75 to the other of the models. Furthermore, after an output is obtained from one or both of the models, the output can be compared to the measured data from the oilfield.”; para. [0054], “the method begins with processing of a physics-based model 405. In this instance, the input into the physics-based model and any sub-models may include estimated hyper-physical parameters, and/or may include measured oilfield conditions or parameters, and/or be outputs from previous physics-based or data-driven models, or other inputs. Real-time measurements 410 in an oilfield are made of various oilfield conditions via various sensors, tools and other data gathering instruments. A physics-based model 405 defines an acceptable range 415 of values for these collected real-time measurements 410.”);
determining that a difference between the [output of the physics-based model] and a measured [drilling operational parameter] in the drilling data is more than a predetermined threshold (para. [0053], “[t]he present disclosure provides for detecting abnormal measured parameters to monitor the status of sensors and equipment. One illustrated embodiment is provided for in flow diagram 400 shown in FIG. 4. In this embodiment, a physics-based model, which may contain sub-models, sets a range for the values.”; para. [0055], “[o]ut of range values 420 may be considered as incorrect, as not representative of measurements or data that are correct or able to occur in the real world, and so may be indicative of some type of problem. These out of range values 420 are fed to a data-driven model 425. The data driven model 425 may process the frequency, trend and severity of the out of range values 420 for various real world event failures 430 which may result from such values being out of range. These real world event failures may include sensor failures, equipment failures, process failures, among other failures.”)
Zhang further discloses “[a]s the drill bit 148 extends the wellbore 144 through the formations 146, logging tools 156 collect measurements relating to various formation properties as well as the orientation of the tool and various other drilling conditions.” (Zhang, para. [0039]). However, Zhang may not expressly state that the physics-based model which is used is a rate of penetration drilling model. Jain, which is in the same field of endeavor as the instant application insofar as it is directed models used in drilling operations, teaches the deficient limitations. For example, Jain teaches “the prediction system 129 may generate predictive ROP and wear models based on offset well data and physics data and utilizing physics model and machine-learning techniques.” (Jain, para. [0032]). Jain further discusses the rate of penetration model at para. [0035]—[0037] along with FIGs. 3A and 4B.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited physics-based models of Zhang with the specific physics-based models of Jain. The specific model of Jain would directly replace the generic model of Zhang in the specific workflow of Zhang as provided above. Furthermore, Jain at para. [0003] teaches “[c]onventional methods of predicting and optimizing bit performance utilize physics-based models during pre-well planning,” which underscores that the above cited physics-based models are conventionally used in drilling operations. The specific physics-based models of Jain where known in the art where the models are described by Jain as being “conventional methods” as identified above. The resulting combination would generate the predictable result of providing for specific physics-based model to describe the performance of the drilling operation as used in the method outlined by Zhang.
Examiner notes the limitation “in response to determining that the difference between the predicted drilling ROP and the measured drilling ROP in the drilling data is more than the predetermined threshold, determining that at least one of the one or more anomalies exists in the field data,” constitutes a conditional limitation and is not required to be performed in order for the claim to be performed. Accordingly the claim is fully rejected without consideration for this limitation.
While Zhang discloses physics-based models used for drilling operations (e.g., see physics-based models 70/210/310/405 throughout), Zhang may not explicitly disclose the specific physics-based models recited in claim 12. Jain, which is in the same field of endeavor as the instant application insofar as it is directed models used in drilling operations, teaches the deficient limitations. For example, Jain teaches wherein the one or more physics-based models comprise at least one of a geomechanics model (rock mechanical properties model 304, FIG. 3A), a drill bit wear model (bit mechanics model 318 and bit wear model 320, FIG 3A and FIG. 4B), or a drilling rate of penetration (ROP) model (ROP Limiters Model 322, FIG. 3A and FIG 4B). Furthermore, Jain at para. [0003] teaches “[c]onventional methods of predicting and optimizing bit performance utilize physics-based models during pre-well planning,” which underscores that the above cited physics-based models are conventionally used in wellbore planning.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited physics-based models of Zhang with the specific physics-based models of Jain. The specific physics-based models of Jain where known in the art where the models are described by Jain as being “conventional methods” as identified above. The resulting combination would generate the predictable result of providing for specific physics-based model to describe the performance of the drilling operation.
While Zhang discloses physics-based models used for drilling operations (e.g., see physics-based models 70/210/310/405 throughout), Zhang may not explicitly disclose the specific physics-based models recited in claim 17. Jain, which is in the same field of endeavor as the instant application insofar as it is directed models used in drilling operations, teaches the deficient limitations. For example, Jain teaches wherein the one or more physics-based models comprise at least one of a geomechanics model (rock mechanical properties model 304, FIG. 3A), a drill bit wear model (bit mechanics model 318 and bit wear model 320, FIG 3A and FIG. 4B), or a drilling rate of penetration (ROP) model (ROP Limiters Model 322, FIG. 3A and FIG 4B). Furthermore, Jain at para. [0003] teaches “[c]onventional methods of predicting and optimizing bit performance utilize physics-based models during pre-well planning,” which underscores that the above cited physics-based models are conventionally used in wellbore planning.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited physics-based models of Zhang with the specific physics-based models of Jain. The specific physics-based models of Jain where known in the art where the models are described by Jain as being “conventional methods” as identified above. The resulting combination would generate the predictable result of providing for specific physics-based model to describe the performance of the drilling operation.
Claim(s) 3, 4, 13, 14, 18, and 19 and is/are rejected under 35 U.S.C. 103 as being unpatentable over Published US Patent Application to Zhang et al., hereinafter “Zhang” (US 20190323323 A1) as applied to claims 1, 11, and 16 above, and further in view of Published US Patent Application to Vempati et al., hereinafter “Vempati” (US 20190226333 A1).
Regarding claim 3, Zhang at para. [0042] discloses “[d]ownhole measurements 45 such as from the logging tools 156, performance of the tool or drilling device, data collected by computing device 150, along with surface measurements 55 may be provided to the data aggregator unit 50 along with any surface measurements.” However, Zhang may not explicitly disclose the specific drilling device data recited in claim 3. Vempati, which is in the same field of endeavor as the instant application insofar as it is directed to systems and methods used in drilling operations teaches the deficient limitation. For example, Vempati teaches wherein the drilling data of the drill bit comprises at least one of revolutions per minute (RPM) data, rate of penetration (ROP) data, weight on bit (WOB) data, or torque on bit (TOB) data (Vempati, para. [0021], “[t]he sensors 140 of the drill bit 116 may include one or more sensors that provide information relating to drilling parameters of the drill bit 116 in the subterranean formation 118 including, but not limited to, weight-on-bit (WOB), torque rotational speed of the drill bit 116 (revolutions per minute or RPM), rate of penetration (ROP) of the drill bit 116 into the formation 118, pressure, temperature, mechanical specific energy, and differential pressure.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited data related to the drilling device as provided by Zhang with the specific drilling device data as provided by Vempati. The measured drilling features Vempati where known in the art as described by Vempati and the combination would generate the predictable result of providing for specific drilling parameters to describe the performance of the drilling device.
Regarding claim 4, Zhang states that logging data related to formation properties from logging tools used in the drill string may provide data to the process of Zhang. For example, Zhang discloses “[w]ith respect to downhole measurements, logging tools 156 can be integrated into the bottom-hole assembly 152 near the drill bit 148. As the drill bit 148 extends the wellbore 144 through the formations 146, logging tools 156 collect measurements relating to various formation properties as well as the orientation of the tool and various other drilling conditions.” (Zhang, para. [0039]). However, Zhang may not expressly state the specific logging features recited in claim 4. Vempati, which is in the same field of endeavor as the instant application insofar as it is directed to systems and methods used in drilling operations teaches the deficient limitation. For example, Vempati teaches wherein the logging data of the wellbore comprises at least one of Gamma, porosity (“[t]he sensors 140 of the drill bit 116 may also include one or more sensors that provide information relating to the formation 118 penetrated by the drilling assembly 114 (e.g., formation parameters) including sensors generally known as measurement-while-drilling (MWD) sensors or logging-while-drilling (LWD) sensors for measuring lithology, permeability, porosity, rock strength, and other geological characteristics of the formation 118 surrounding the borehole 102.” (Vempati, para. [0021]), density, or resistivity of rock formation of the wellbore.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited logging data as provided by Zhang with the specific logging data as provided by Vempati. The measured formation features Vempati where known in the art as described by Vempati and the combination would generate the predictable result of providing for specific logging/formation parameters to describe the subterranean formation.
Regarding claim 13, Zhang at para. [0042] discloses “[d]ownhole measurements 45 such as from the logging tools 156, performance of the tool or drilling device, data collected by computing device 150, along with surface measurements 55 may be provided to the data aggregator unit 50 along with any surface measurements.” However, Zhang may not explicitly disclose the specific drilling device data recited in claim 13. Vempati, which is in the same field of endeavor as the instant application insofar as it is directed to systems and methods used in drilling operations teaches the deficient limitation. For example, Vempati teaches wherein the drilling data of the drill bit comprises at least one of revolutions per minute (RPM) data, rate of penetration (ROP) data, weight on bit (WOB) data, or torque on bit (TOB) data (Vempati, para. [0021], “[t]he sensors 140 of the drill bit 116 may include one or more sensors that provide information relating to drilling parameters of the drill bit 116 in the subterranean formation 118 including, but not limited to, weight-on-bit (WOB), torque rotational speed of the drill bit 116 (revolutions per minute or RPM), rate of penetration (ROP) of the drill bit 116 into the formation 118, pressure, temperature, mechanical specific energy, and differential pressure.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited data related to the drilling device as provided by Zhang with the specific drilling device data as provided by Vempati. The measured drilling features Vempati where known in the art as described by Vempati and the combination would generate the predictable result of providing for specific drilling parameters to describe the performance of the drilling device.
Regarding claim 14, Zhang states that logging data related to formation properties from logging tools used in the drill string may provide data to the process of Zhang. For example, Zhang discloses “[w]ith respect to downhole measurements, logging tools 156 can be integrated into the bottom-hole assembly 152 near the drill bit 148. As the drill bit 148 extends the wellbore 144 through the formations 146, logging tools 156 collect measurements relating to various formation properties as well as the orientation of the tool and various other drilling conditions.” (Zhang, para. [0039]). However, Zhang may not expressly state the specific logging features recited in claim 14. Vempati, which is in the same field of endeavor as the instant application insofar as it is directed to systems and methods used in drilling operations teaches the deficient limitation. For example, Vempati teaches wherein the logging data of the wellbore comprises at least one of Gamma, porosity (“[t]he sensors 140 of the drill bit 116 may also include one or more sensors that provide information relating to the formation 118 penetrated by the drilling assembly 114 (e.g., formation parameters) including sensors generally known as measurement-while-drilling (MWD) sensors or logging-while-drilling (LWD) sensors for measuring lithology, permeability, porosity, rock strength, and other geological characteristics of the formation 118 surrounding the borehole 102.” (Vempati, para. [0021]), density, or resistivity of rock formation of the wellbore.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited logging data as provided by Zhang with the specific logging data as provided by Vempati. The measured formation features Vempati where known in the art as described by Vempati and the combination would generate the predictable result of providing for specific logging/formation parameters to describe the subterranean formation.
Regarding claim 18, Zhang at para. [0042] discloses “[d]ownhole measurements 45 such as from the logging tools 156, performance of the tool or drilling device, data collected by computing device 150, along with surface measurements 55 may be provided to the data aggregator unit 50 along with any surface measurements.” However, Zhang may not explicitly disclose the specific drilling device data recited in claim 18. Vempati, which is in the same field of endeavor as the instant application insofar as it is directed to systems and methods used in drilling operations teaches the deficient limitation. For example, Vempati teaches wherein the drilling data of the drill bit comprises at least one of revolutions per minute (RPM) data, rate of penetration (ROP) data, weight on bit (WOB) data, or torque on bit (TOB) data (Vempati, para. [0021], “[t]he sensors 140 of the drill bit 116 may include one or more sensors that provide information relating to drilling parameters of the drill bit 116 in the subterranean formation 118 including, but not limited to, weight-on-bit (WOB), torque rotational speed of the drill bit 116 (revolutions per minute or RPM), rate of penetration (ROP) of the drill bit 116 into the formation 118, pressure, temperature, mechanical specific energy, and differential pressure.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited data related to the drilling device as provided by Zhang with the specific drilling device data as provided by Vempati. The measured drilling features Vempati where known in the art as described by Vempati and the combination would generate the predictable result of providing for specific drilling parameters to describe the performance of the drilling device.
Regarding claim 19, Zhang states that logging data related to formation properties from logging tools used in the drill string may provide data to the process of Zhang. For example, Zhang discloses “[w]ith respect to downhole measurements, logging tools 156 can be integrated into the bottom-hole assembly 152 near the drill bit 148. As the drill bit 148 extends the wellbore 144 through the formations 146, logging tools 156 collect measurements relating to various formation properties as well as the orientation of the tool and various other drilling conditions.” (Zhang, para. [0039]). However, Zhang may not expressly state the specific logging features recited in claim 19. Vempati, which is in the same field of endeavor as the instant application insofar as it is directed to systems and methods used in drilling operations teaches the deficient limitation. For example, Vempati teaches wherein the logging data of the wellbore comprises at least one of Gamma, porosity (“[t]he sensors 140 of the drill bit 116 may also include one or more sensors that provide information relating to the formation 118 penetrated by the drilling assembly 114 (e.g., formation parameters) including sensors generally known as measurement-while-drilling (MWD) sensors or logging-while-drilling (LWD) sensors for measuring lithology, permeability, porosity, rock strength, and other geological characteristics of the formation 118 surrounding the borehole 102.” (Vempati, para. [0021]), density, or resistivity of rock formation of the wellbore.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the generically recited logging data as provided by Zhang with the specific logging data as provided by Vempati. The measured formation features Vempati where known in the art as described by Vempati and the combination would generate the predictable result of providing for specific logging/formation parameters to describe the subterranean formation.
Subject Matter not Rejected Under Prior Art Rejection
Claims 7—9 are not rejected under the above provided prior art rejections; however, claims 7—9 are rejected under 35 U.S.C. 101 for being directed to an abstract idea.
Conclusion
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/U.L.N./Examiner, Art Unit 3676
/TARA SCHIMPF/Supervisory Patent Examiner, Art Unit 3676
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