DETAILED ACTION
This office action is in response to application filed on May 17, 2023.
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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 05/17/2023, 02/01/2024, 07/08/2024 and 01/10/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Specification
The disclosure is objected to because of the following informalities:
[0030]: Language “With the possibility of statistical dominance, it is appreciable learning by such manner …” should read “With the possibility of statistical dominance, it is appreciable that learning by such manner …” in order to correct for minor informalities.
[0071]: Language “Appreciably, and as mentioned earlier, the present disclosure contemplates that SSML need not utilize/is not influenced by the effects of completion data” should read “Appreciably, and as mentioned earlier, the present disclosure contemplates that SSML does not utilize/is not influenced by the effects of completion data” in order to correct for minor informalities.
[0104]: Language “(i.e., normalizing the reference signal(s) based on G&G data and/or normalizing the reference signal(s) based on completion data. That is, at least one or normalizing the reference signal(s) based on G&G data and normalizing the reference signal(s) based on completion data)” should read “(i.e., normalizing the reference signal(s) based on G&G data and/or normalizing the reference signal(s) based on completion data. That is, at least one [[or]]of normalizing the reference signal(s) based on G&G data and normalizing the reference signal(s) based on completion data)” in order to correct for minor informalities.
Appropriate correction is required.
Claim Objections
Claim 1 is objected to because of the following informalities:
Claim language should read:
“An apparatus comprising:
a first module configurable to:
at least one of receive at least one input signal and generate the at least one input signal, the at least one input signal including:
geology and geophysics (G&G) based data; and
completion data associable with a structure,
at least one of receive at least one reference signal and generate the at least one reference signal; and
a second module coupled to the first module, the second module configurable to process the at least one input signal and the at least one reference signal by manner of at least one of:
normalizing the at least one reference signal based on the G&G based data, and
normalizing the at least one reference signal based on the completion data,
to produce at least one output signal corresponding to at least one normalized reference signal” in order to provide appropriate antecedence basis.
Appropriate correction is required.
Claim 2 is objected to because of the following informalities:
Claim language should read:
“The apparatus of claim 1 further comprising:
a third module coupled to the second module, the at least one output signal being communicable to the third module from the second module for further transmission from the apparatus to at least one device coupled to the apparatus,
wherein the at least one output signal is receivable by the at least one device for machine-learning based processing” in order to provide appropriate antecedence basis.
Appropriate correction is required.
Claim 3 is objected to because of the following informalities:
Claim language should read:
“The apparatus of claim 1, wherein the at least one output signal is based solely on normalization of the at least one reference signal based on the G&G based data” in order to provide appropriate antecedence basis.
Appropriate correction is required.
Claim 4 is objected to because of the following informalities:
Claim language should read:
“The apparatus of claim 1, wherein the at least one output signal is based solely on normalization of the at least one reference signal based on the completion data” in order to provide appropriate antecedence basis.
Appropriate correction is required.
Claim 5 is objected to because of the following informalities:
Claim language should read:
“The apparatus of claim 1, wherein the at least one reference signal includes production data associable with the structure” in order to provide appropriate antecedence basis.
Appropriate correction is required.
Claim 6 is objected to because of the following informalities:
Claim language should read:
“The apparatus of claim 1, wherein the structure corresponds to .
Appropriate correction is required.
Claim 7 is objected to because of the following informalities:
Claim language should read:
“A processing method suitable for analytics based on at least one of geology and geophysics (G&G) based data and completion data, the processing method comprising:
at least one of generating and receiving at least one input signal, the at least one input signal including at least one of:
the geology and geophysics (G&G) based data; and
the completion data associable with a structure;
at least one of generating and receiving at least one reference signal;
processing the at least one input signal and the at least one reference signal by manner of at least one of:
normalizing the at least one reference signal based on the G&G based data, and
normalizing the at least one reference signal based on the completion data,
to produce at least one output signal corresponding to at least one normalized reference signal” in order to provide appropriate antecedence basis.
Appropriate correction is required.
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 1-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Regarding claim 1, the examiner submits that under Step 1 of the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (see also 2019 Revised Patent Subject Matter Eligibility Guidance) for evaluating claims for eligibility under 35 U.S.C. 101, the claim is to a machine/manufacture, which is one of the statutory categories of invention.
Continuing with the analysis, under Step 2A - Prong One of the test:
the limitation
“the second module configurable to process the input signal and the reference signal by manner of at least one of:
normalizing the reference signal based on G&G data, and
normalizing the reference signal based on completion data,
to produce at least one output signal corresponding to at least one normalized reference signal”
is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mathematical concepts (i.e., normalization) to manipulate data and obtain a result (i.e., at least one output signal corresponding to at least one normalized reference signal; see specification at [0010]-[0012], [0016], [0027]-[0028], [0041], [0048], [0051]-[0058], [0084]-[0085]). Except for the recitation of the extra-solution activities (e.g., source/type of data being evaluated), the particular technological environment or field of use, and the generic computer elements (i.e., second module, see specification at [0041], [0046], [0048]), the limitation in the context of the claim mainly refers to applying mathematical concepts to transform data.
Therefore, the claim recites a judicial exception under Step 2A - Prong One of the test.
Furthermore, under Step 2A - Prong Two of the test, this judicial exception is not integrated into a practical application. In particular, the additional elements recited in the claim:
“An apparatus comprising:
a first module configurable to:
at least one of receive at least one input signal and generate at least one input signal, the input signal including:
geology and geophysics (G&G) based data; and
completion data associable with a structure,
at least one of receive at least one reference signal and generate at least one reference signal; and
a second module coupled to the first module”
add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see specification at [0041], [0046]-[0050]) (see MPEP 2106.05(f)); and
generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)) and/or add extra-solution activities (e.g., mere data gathering, source/type of data to be manipulated) (see MPEP 2106.05(g)).
Accordingly, these additional elements, when considered individually and in combination, do not integrate the judicial exception into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considering the claim as a whole. The claim is directed to a judicial exception under Step 2A of the test.
Additionally, under Step 2B of the test, the claim does not include additional elements that, when considered individually and in combination, are sufficient to amount to significantly more than the judicial exception because the additional elements:
append generic computer components (i.e., An apparatus comprising: a first module and a second module coupled to the first module, see specification at [0041], [0046]-[0050]) used to facilitate the application of the abstract idea (i.e., mere computer implementation), which as indicated in the MPEP: “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 provide significantly more” (see MPEP 2106.05(f), item 2) and “Courts have held computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking)” (see MPEP 2106.05(d), section II);
generally link the use of the judicial exception to a particular technological environment or field of use (e.g., geology, geophysics), which as indicated in the MPEP: “As 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” (see MPEP 2106.05(h)); and
recite extra-solution activities (i.e., mere data gathering by selecting a particular data source/type to be manipulated) using elements (i.e., An apparatus comprising: a first module and a second module coupled to the first module) specified at a high level of generality, which as indicated in the MPEP: “Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more” (see MPEP 2106.05(b), section III).
The claim, when considered as a whole, does not provide significantly more under Step 2B of the test.
Based on the analysis, the claim is not patent eligible.
Similarly, independent claim 7 is directed to a judicial exception (abstract idea) without significantly more as explained above with regards to claim 1.
With regards to the dependent claims they are also directed to the non-statutory subject matter because:
they just extend the abstract idea of the independent claims by additional limitations (Claims 3-4), that under the broadest reasonable interpretation in light of the specification, cover performance of the limitations using mathematical concepts, and
the additional elements recited in the dependent claims, when considered individually and in combination, add extra-solution activities (e.g., mere data gathering/transmission using a data type or source) and/or append generic computer components (Claims 2 and 5-6), which as indicated in the Office’s guidance does not integrate the judicial exception into a practical application (Step 2A – Prong Two) and/or does not provide significantly more (Step 2B).
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 7 is rejected under 35 U.S.C. 102(a)(1) and 35 U.S.C. 102(a)(2) as being anticipated by Anderson (US 20170364795 A1), hereinafter ‘Anderson’.
Regarding claim 7.
Anderson discloses:
A processing method suitable for analytics based on at least one of geology and geophysics (G&G) based data and completion data ([0002], [0011]: a Petroleum Analytics Learning Machine (or PALM) method is used for maximizing production from wells based on geology, geophysics and completion data (see also [0061], [0063])), the method comprising:
at least one of generating and receiving at least one input signal, the input signal including at least one of: geology and geophysics (G&G) based data; and completion data associable with a structure ([0004]-[0005], [0011]: a System Integration Database (SID) receives data from field devices, the data including geology, geophysics and completion data (see also [0061], [0063]));
at least one of generating and receiving at least one reference signal ([0004]-[0005], [0011]: the System Integration Database (SID) receives data from field devices, the data including production data (see also [0064]));
processing the input signal and the reference signal by manner of at least one of: normalizing the reference signal based on G&G data, and normalizing the reference signal based on completion data, to produce at least one output signal corresponding to at least one normalized reference signal ([0005], [0011]: data including production data is retrieved, compared and combined into a uniform data repository using normalization based on unique identifiers which include geology, geophysics and completion data (see also [0072] regarding production data being normalized by flow days and for perforated lateral length)).
Claim Rejections - 35 USC § 103
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.
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.
Claims 1-6 are rejected under 35 U.S.C. 103 as being unpatentable over Anderson, in view of Romero (US 20120253681 A1), hereinafter ‘Romero’.
Regarding claim 1.
Anderson discloses:
An apparatus (Figs. 1-2, item 1000 – “PALM system”; [0051]: A Petroleum Analytics Learning Machine (or PALM) system is used for maximizing production from wells (see [0002])) comprising:
a first module (Figs. 1-2, item 1300 – “SID”; [0004], [0051]: a System Integration Database (SID) is part of the PALM system) configurable to:
at least one of receive at least one input signal and generate at least one input signal, the input signal including: geology and geophysics (G&G) based data; and completion data associable with a structure ([0004]-[0005], [0011]: the System Integration Database (SID) receives data from field devices, the data including geology, geophysics and completion data (see also [0061], [0063])),
at least one of receive at least one reference signal and generate at least one reference signal ([0004]-[0005], [0011]: the System Integration Database (SID) receives data from field devices, the data including production data (see also [0064])); and
a second module (Figs. 1-2, item 1300 – ‘SID’; [0004], [0051]: the System Integration Database (SID) is part of the PALM system), the second module configurable to process the input signal and the reference signal by manner of at least one of: normalizing the reference signal based on G&G data, and normalizing the reference signal based on completion data to produce at least one output signal corresponding to at least one normalized reference signal ([0005], [0011]: data including production data is retrieved, compared and combined into a uniform data repository using normalization based on unique identifiers which include geology, geophysics and completion data (see also [0072] regarding production data being normalized by flow days and for perforated lateral length)).
Anderson does not explicitly disclose (see italic text):
a second module coupled to the first module.
Romero teaches:
“In accordance with another embodiment of the present invention, a corresponding system is provided processing seismic data corresponding to a subsurface area of interest. The system includes a data source containing the seismic data, and a computer processor in communication with the data source for processing the seismic data. The processor includes computer readable media having computer readable code for executing the steps of determining, from the seismic data, a first amplitude attribute map at a first image depth; determining, from the seismic data, a second amplitude attribute map at a second image depth; normalizing each of the first and second amplitude attribute maps; determining a ratio map based on a ratio of the normalized first and second amplitude attribute maps; scaling the ratio map to generate a scale factor map; and applying the scale factor map to the seismic data to compensate for effects of shallow over burden attenuation” ([0007]: a system for processing seismic data includes a data source (analogous to first module) containing the seismic data and a processor (analogous to second module) in communication with the data source (analogous to second module coupled to the first module) for processing the seismic data, the processing including normalization of data (see also [0023]-[0024])).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Anderson in view of Romero to incorporate the second module coupled to the first module, in order to provide a robust and flexible system that accesses/stores different field information using a first component (i.e., first module) and performs analysis of the data using a second component (i.e., second module).
Regarding claim 2.
Anderson in view of Romero discloses all the features of claim 1 as described above.
Anderson further discloses:
a third module (Figs. 1-2, item 1400 – “PALM Machine Learning Optimizer”; [0051]: a machine learning optimizer is part of the PALM system) coupled to the second module (see Figs. 1-2), the output signal being communicable to the third module from the second module ([0005]: normalized data is processed to identify importance weights (see also Abstract, [0053])) for further transmission from the apparatus to at least one device (Figs. 1-2, item 1200 – “MAP Subsystems”; [0004], [0051]: machine analytics products subsystems retrieve integrated data from the SID (see Fig. 2 implying data transmission going through PALM Machine Learning Optimizer)) coupled to the apparatus (see Figs. 1-2),
wherein the output signal is receivable by the device for machine-learning based processing ([0004]: MAP subsystems perform machine learning on the integrated data for production optimization).
Regarding claim 3.
Anderson in view of Romero discloses all the features of claim 1 as described above.
Anderson further discloses:
the output signal is based solely on normalization of the reference signal based on G&G data ([0011]: data including production data is retrieved, compared and combined into a uniform data repository using normalization based on at least one unique identifier which includes geology and geophysics data, which implies using only geology and geophysics data for normalization).
Regarding claim 4.
Anderson in view of Romero discloses all the features of claim 1 as described above.
Anderson further discloses:
the output signal is based solely on normalization of the reference signal based on completion data ([0011]: data including production data is retrieved, compared and combined into a uniform data repository using normalization based on at least one unique identifier which includes completion data, which implies using only completion data for normalization).
Regarding claim 5.
Anderson in view of Romero discloses all the features of claim 1 as described above.
Anderson further discloses:
the reference signal includes production data associable with the structure ([0005], [0009], [0011]: the System Integration Database (SID) receives data from field devices, the data including production data from wells (see also [0002] and [0064])).
Regarding claim 6.
Anderson in view of Romero discloses all the features of claim 1 as described above.
Anderson further discloses:
the structure corresponds to a completed structure such as a completed oil-well ([0005], [0009], [0011]: the System Integration Database (SID) receives data from field devices, the data including production data from oil wells (see [0002]), which implies the wells to be completed (see also [0022], [0064], [0077] and [0083])).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Maerten; Frantz et al., US 20120072188 A1, STRESS AND FRACTURE MODELING USING THE PRINCIPLE OF SUPERPOSITION
Reference discloses stress and fracturing model using the principle of superposition.
Zhou; Hui et al., US 20210123343 A1, INTEGRATED MACHINE LEARNING FRAMEWORK FOR OPTIMIZING UNCONVENTIONAL RESOURCE DEVELOPMENT
Reference discloses transforming raw reservoir data including geology data, completion data and production data into uncorrelated data for application of performance analytics using machine learning for developing an unconventional reservoir.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LINA CORDERO whose telephone number is (571)272-9969. The examiner can normally be reached 9:30 am - 6:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, ANDREW SCHECHTER can be reached at 571-272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/LINA CORDERO/Primary Examiner, Art Unit 2857
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