DETAILED ACTION
The Applicant’s filing, received 01 March 2023, has been fully considered. The following rejections and/or objections constitute the complete set presently being applied to the instant application.
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 the Claims
Claims 1-20 are pending.
Claims 1-20 are rejected.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Foreign application for which benefit is claimed:
INDIA 202211073906, filed 20 December 2022.
Therefore, the effective filing date of the claimed invention is 20 December 2022.
Drawings
The drawings received 01 March 2023 are accepted.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion).
Claim Interpretations
Claims 2, 10, and 12 recite the limitation “a machine learning model trained based at least in part on….” This limitation is interpreted to recite a product-by-process limitation, with the product being the trained machine learning model, and further interpreted to not require the active steps of performing a process of producing the product, i.e., training the model.
Subject matter eligibility evaluation in accordance with MPEP 2106.
Eligibility Step 1: Step 1 of the eligibility analysis asks: Is the claim to a process, machine, manufacture or composition of matter?
Claims 1-10 recite an apparatus comprising at least one processor and at least one non-transitory memory (i.e., a machine or a manufacture); claims 11-19 recite a computer-implemented method (i.e., a process); and claim 20 recites a computer program product comprising at least one non-transitory computer-readable storage medium (i.e., a machine or a manufacture).
Therefore, these claims are encompassed by the categories of statutory subject matter, and thus, satisfy the subject matter eligibility requirements under step 1.
[Step 1: YES]
Eligibility Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in Prong Two whether the recited judicial exception is integrated into a practical application of that exception.
Eligibility Step 2A Prong One: In determining whether a claim is directed to a judicial exception, examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim.
Independent claim 1 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
generate, using a methane emissions intensity prediction model, a methane emissions intensity prediction corresponding to the one or more operational systems and the period of time based at least in part on the one or more projected production parameters, the emissions reduction strategy information, historical operational data associated with the one or more operational systems, and historical emissions data associated with the one or more operational systems (i.e., mental processes and mathematical concepts).
Independent claim 11 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
generating, using a methane emissions intensity prediction model, a methane emissions intensity prediction corresponding to the one or more operational systems and the period of time based at least in part on the one or more projected production parameters, the emissions reduction strategy information, historical operational data associated with the one or more operational systems, and historical emissions data associated with the one or more operational systems (i.e., mental processes and mathematical concepts).
Independent claim 20 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
generate, using a methane emissions intensity prediction model, a methane emissions intensity prediction corresponding to the one or more operational systems and the period of time based at least in part on the one or more projected production parameters, the emissions reduction strategy information, historical operational data associated with the one or more operational systems, and historical emissions data associated with the one or more operational systems (i.e., mental processes and mathematical concepts).
Dependent claims 2-10 and 12-19 further recite the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas, as noted below.
Dependent claim 2 further recites:
the methane emissions intensity prediction model comprises a machine learning model trained based at least in part on the historical operational data and the historical emissions data (i.e., mental processes and mathematical concepts).
Dependent claim 3 further recites:
the one or more projected production parameters include planned operating conditions, planned operating capacity, and/or planned operating modes of the one or more operational systems during the period of time (i.e., mental processes).
Dependent claim 4 further recites:
the historical operational data indicates historical production parameters corresponding to past operation of the one or more operational systems (i.e., mental processes).
Dependent claim 5 further recites:
the historical production parameters include past operating conditions, past operating capacity, and/or past operating modes of the one or more operational systems during the past operation of the one or more operational systems (i.e., mental processes).
Dependent claim 6 further recites:
the historical emissions data indicates methane emissions produced by the one or more operational systems and measured by emissions sensors during the past operation of the one or more operational systems (i.e., mental processes).
Dependent claim 7 further recites:
the methane emissions intensity prediction is generated based at least in part on correlations between the methane emissions of the historical emissions data and the historical production parameters of the historical operational data (i.e., mental processes and mathematical concepts).
Dependent claim 8 further recites:
the methane emissions intensity prediction is generated based at least in part on simulated emissions data associated with the one or more operational systems, the simulated emissions data indicating estimated methane emissions corresponding to simulated production parameters associated with the one or more operational systems (i.e., mental processes and mathematical concepts).
Dependent claim 9 further recites:
the methane emissions intensity prediction is generated based at least in part on correlations between the estimated methane emissions and the simulated production parameters (i.e., mental processes and mathematical concepts).
Dependent claim 10 further recites:
the methane emissions intensity prediction model comprises a machine learning model trained based at least in part on the simulated emissions data (i.e., mental processes and mathematical concepts).
Dependent claim 12 further recites:
the methane emissions intensity prediction model comprises a machine learning model trained based at least in part on the historical operational data and the historical emissions data (i.e., mental processes and mathematical concepts).
Dependent claim 13 further recites:
the one or more projected production parameters include planned operating conditions, planned operating capacity, and/or planned operating modes of the one or more operational systems during the period of time (i.e., mental processes).
Dependent claim 14 further recites:
the historical operational data indicates historical production parameters corresponding to past operation of the one or more operational systems (i.e., mental processes).
Dependent claim 15 further recites:
the historical production parameters include past operating conditions, past operating capacity, and/or past operating modes of the one or more operational systems during the past operation of the one or more operational systems (i.e., mental processes).
Dependent claim 16 further recites:
the historical emissions data indicates methane emissions produced by the one or more operational systems and measured by emissions sensors during the past operation of the one or more operational systems (i.e., mental processes).
Dependent claim 17 further recites:
the generating of the methane emissions intensity prediction comprises generating the methane emissions intensity prediction based at least in part on correlations between the methane emissions of the historical emissions data and the historical production parameters of the historical operational data (i.e., mental processes and mathematical concepts).
Dependent claim 18 further recites:
the generating of the methane emissions intensity prediction comprises generating the methane emissions intensity prediction based at least in part on simulated emissions data associated with the one or more operational systems, the simulated emissions data indicating estimated methane emissions corresponding to simulated production parameters associated with the one or more operational systems (i.e., mental processes and mathematical concepts).
Dependent claim 19 further recites:
the generating of the methane emissions intensity prediction comprises generating the methane emissions intensity prediction based at least in part on correlations between the estimated methane emissions and the simulated production parameters (i.e., mental processes and mathematical concepts).
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pen and paper (e.g., the historical operational data indicates historical production parameters corresponding to past operation of the one or more operational systems), and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas (e.g., generate, using a methane emissions intensity prediction model, a methane emissions intensity prediction) are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind.
Therefore, claims 1-20 recite an abstract idea.
[Step 2A Prong One: YES]
Eligibility Step 2A Prong Two: In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that when examined as a whole integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A Prong One are not integrated into a practical application because of the reasons noted below.
Dependent claims 2-10 and 12-19 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception.
The additional elements in independent claim 1 include:
at least one processor;
at least one non-transitory memory comprising program code stored thereon; and
receive one or more projected production parameters and emissions reduction strategy information associated with one or more operational systems and corresponding to a period of time, wherein the one or more projected production parameters correspond to planned operation of the one or more operational systems in the period of time, and wherein the emissions reduction strategy information indicates one or more planned methane emissions reduction strategies to be implemented with respect to the one or more operational systems in the period of time (i.e., receive data).
The additional elements in independent claim 11 include:
a computer; and
receiving one or more projected production parameters and emissions reduction strategy information associated with one or more operational systems and corresponding to a period of time, wherein the one or more projected production parameters correspond to planned operation of the one or more operational systems in the period of time, and wherein the emissions reduction strategy information indicates one or more planned methane emissions reduction strategies to be implemented with respect to the one or more operational systems in the period of time (i.e., receiving data).
The additional elements in independent claim 20 include:
at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein; and
receive one or more projected production parameters and emissions reduction strategy information associated with one or more operational systems and corresponding to a period of time, wherein the one or more projected production parameters correspond to planned operation of the one or more operational systems in the period of time, and wherein the emissions reduction strategy information indicates one or more planned methane emissions reduction strategies to be implemented with respect to the one or more operational systems in the period of time (i.e., receive data).
The additional elements of at least one processor (claim 1); a computer (claim 11); at least one non-transitory memory comprising program code stored thereon (claim 1); and at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein (claim 20); invoke a computer and/or computer-related components merely as tools for use in the claimed process, such that they amount to no more than mere instructions to apply the exceptions using a generic computer (MPEP 2106.05(f)), and therefore are not an improvement to computer functionality itself, or an improvement to any other technology or technical field, and thus, do not integrate the judicial exceptions into a practical application (MPEP 2106.04(d)(1)).
The additional element of receive/receiving one or more projected production parameters and emissions reduction strategy information associated with one or more operational systems and corresponding to a period of time, wherein the one or more projected production parameters correspond to planned operation of the one or more operational systems in the period of time, and wherein the emissions reduction strategy information indicates one or more planned methane emissions reduction strategies to be implemented with respect to the one or more operational systems in the period of time (i.e., receive/receiving data) (claims 1, 11, and 20); is merely a pre-solution activity of gathering data for use in the claimed process – a nominal or tangential addition to the claims that does not meaningfully limit the claims, and therefore does not add more than insignificant extra-solution activity to the judicial exceptions (MPEP 2106.05(g)).
Thus, the additionally recited elements merely invoke a computer and/or computer related components as tools; and/or amount to insignificant extra-solution activity; and as such, when all limitations in claims 1-20 have been considered as a whole (i.e., the analysis takes into consideration all the claim limitations and how those limitations interact and impact each other when evaluating whether the exception is integrated into a practical application), the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-20 are directed to an abstract idea (MPEP 2106.04(d)).
[Step 2A Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
Dependent claims 2-10 and 12-19 do not recite any elements in addition to the judicial exception(s).
The additional elements recited in independent claims 1, 11, and 20 are identified above, and carried over from Step 2A Prong Two along with their conclusions for analysis at Step 2B. Any additional element or combination of elements that was considered to be insignificant extra-solution activity at Step 2A Prong Two was re-evaluated at Step 2B, because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant; and all additional elements and combination of elements were evaluated to determine whether any additional elements or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP 2106.05(d).
The additional elements of at least one processor (claim 1); a computer (claim 11); at least one non-transitory memory comprising program code stored thereon (claim 1); and at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein (claim 20); and receive/receiving data (claims 1, 11, and 20); are conventional computer components and/or functions (see MPEP at 2106.05(b) and 2106.05(d)(II) regarding conventionality of computer components and computer processes).
Therefore, when taken alone (i.e., individually), all additional elements in claims 1-20 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as an ordered combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-20 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)).
[Step 2B: NO]
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Leerbeck et al. (“Short-term forecasting of CO2 emission intensity in power grids by machine learning.” Applied Energy, 2020, vol. 277, no. 115527, pp. 1-13) and MacKay et al. (“Methane emissions from upstream oil and gas production in Canada are underestimated.” Scientific Reports, 2021, vol. 11:8041, pp. 1-8, and Supplementary Materials, pp. 1-15).
Independent claims 1, 11, and 20 are directed to a computer-implemented method for using a predictive model to generate a methane emissions intensity prediction corresponding to one or more operational systems and a period of time based on data comprising historical operational data and historical emissions data.
Dependent claims 2-10 and 12-19 further define the attributes of the data used in the predictive model, and the attributes of the model itself.
Leerbeck et al. is directed to using machine learning to forecast the CO2 emission intensities in electrical power grids with the aim of enabling flexible electricity demand.
MacKay et al. is directed to measuring fugitive and vented methane emission intensities across major oil and gas producing regions in Canada.
Regarding independent claims 1, 11, and 20, Leerbeck et al. shows a machine learning methodology for short-term (24 h ahead) forecasting with uncertainty margins (95% prediction intervals) of both the average and marginal CO2 emission intensities (see page 2, col. 2, para. 1), wherein the forecasts can be used by flexible consumers (with electric cars, heat pumps, etc.) to schedule for optimal electricity usage, i.e., minimizing CO2 emissions (page 2, col. 2, para. 3), wherein the response variable (average and marginal CO2 emission intensity) is modelled using explanatory variables such as power generation, demand, import, and weather conditions (page 2, col. 2, para. 4).
Regarding independent claims 1, 11, and 20, Leerbeck et al. does not show using a machine learning model to generate a methane emissions intensity prediction.
Regarding independent claims 1, 11, and 20, MacKay et al. shows a methane emissions intensity analysis that expressed estimates using two ratios: (1) Average megajoule emitted per megajoule produced (MJ/MJ), and (2) grams of CO2 equivalent emitted per megajoule produced (gCO2e/MJ), and gathering aggregated production data databases in order to calculate the average energy produced per day at all measured sites (page 6, paras. 2-5).
Regarding dependent claims 2, 10, and 12, Leerbeck et al. further shows training the predictive model (page 5, col. 2, Section 4.1.).
Regarding dependent claims 3-5 and 13-15, Leerbeck et al. further shows a dataset comprised of a large number (473) of explanatory variables such as power production (Abstract).
Regarding dependent claims 8, 9, 18, and 19, Leerbeck et al. further shows using simulated explanatory variables, all with a certain degree of correlation to a simulated response variable (Fig. 6).
Regarding dependent claims 6, 7, 16, and 17, MacKay et al. further shows using aggregated site-level emission data (page 4, paras. 4-5).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Leerbeck et al. by incorporating methods for generating a methane emissions intensity predictive analysis, as shown by MacKay et al. and discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Leerbeck et al. with the methods of MacKay et al., because MacKay et al. shows methods for using production data to calculate methane emissions intensities. This modification would have had a reasonable expectation of success given that Leerbeck et al. shows a methodology for using predictive models to forecast CO2 emission intensity, and MacKay et al. shows methods for calculating methane emission intensities, which could be incorporated into Leerbeck’s predictive model.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of copending Application No. 18/176,780 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because instant claims 1-20 are directed to a method for using a machine learning model for generating a prediction of methane emissions intensity using emissions data, and reference claims 1-20 are directed a method for using a machine learning model for generating a prediction of a fugitive leak using emissions data.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Conclusion
No claims are allowed.
This Office action is a Non-Final action. A shortened statutory period for reply to this action is set to expire THREE MONTHS from the mailing date of this application.
Inquiries
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/S.W.B./Examiner, Art Unit 1687
/Joseph Woitach/Primary Examiner, Art Unit 1687
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