DETAILED ACTION
Receipt of Applicant’s amendment filed 12/15/2025 is acknowledged.
Claims 1, 3, 5, 6, and 12 have been amended.
Claims 2 and 10 have been canceled.
Claims 1, 3-9, 11-12 are pending.
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 .
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the
references as applied to the claims below for the convenience of the applicant. Although
the specified citations are representative of the teachings in the art and are applied to
the specific limitations within the individual claim, other passages and figures may apply
as well. Examiner may also include cited interpretations encompassed within parenthesis, e.g. (Examiner’s interpretation), for clarity. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
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 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.
Response to Arguments
Specification Objections:
Acknowledgement is made of the amended Specification [Pg.16-17 References] to remove hyperlinks. Objections to Specification due to minor informalities are withdrawn.
Claim Objections:
Acknowledgement is made of amended claim 12 to correct minor informalities. Objection to claim 12 is withdrawn.
Claim Rejections under 35 U.S.C. § 112(b):
Acknowledgement is made of amended claim 3 (i.e. to include “SCAL”) to provide claim 4 limitation clarification. Acknowledgement is made of claim 10 cancelation. Previous rejections to claims 1 and 10 under 35 U.S.C. 112(b) are withdrawn.
Claim Rejections under 35 U.S.C. § 101:
Acknowledgement is made of amended independent claims 1, 3 and 6. Applicants arguments have been fully considered, but were not persuasive. Rejections to claims 1, 3-9, and 11-12 are maintained.
Applicant argues [Pg.10 P.2 – Pg.11 P.1] the claimed invention is materially distinguishable from Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016). The Examiner respectfully disagrees.
Per independent claim 1, the invention can be summarized as using a CT scanner to collect data, using the data to derive (calculating/simulating – i.e. using a computer for generic information processing) saturation profiles and other data, inputting the derived data into a machine learning algorithm (i.e. using a computer for generic information processing), collecting more data from the CT scanner, deriving more data (i.e. using a computer for generic information processing), inputting the data into the learned algorithm, and then using the machine learned algorithm to output more data (i.e. again, using a computer for generic information processing). All of which is merely using computers as tools to perform generic information processing.
As shown in Claim Rejections – 35 USC 101 section below, all limitations citing “deriving”, “approximating”, and “calculating” were identified as Mental Process and/or Mathematical Concepts, since each limitation as drafted can practically be performed in the human mind (as shown below) with/without the aid of pen/paper. Thus, Applicant’s argument not persuasive.
Applicant argues [Pg.11 P.2 – Pg.12 P.1] that under Step 2A Prong 1 of the Alice/Mayo framework, the claims do not recite mental processes nor mathematical concepts, therefore independent claims as a whole are not directed to an abstract idea. The Examiner respectfully disagrees.
Independent claim 1 recites the following limitations all identified as Mental Processes per MPEP 2106.04(a)(2). Note: the following limitations are not merely “conceptualized” as Applicant argues, instead the following limitations can practically be performed/calculated by the human mind with/without the aid of pen/paper.
deriving, by a processor, a one-dimensional drainage phase saturation profile from the at least one measured three-dimensional drainage phase saturation profile (Per Applicant’s disclosure (Spec. [P.0037]), “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average”. A person can reasonably evaluate data and then derive/calculate (i.e. mathematical concept) a one-dimensional phase saturation profile, with/without the aid of pen/paper.)
approximating, using the machine learning algorithm executed on the
processor, the predicted three-dimensional imbibition phase saturation profile based on the input; (The use of an algorithm (i.e. mathematical concept) executed on a processor to approximate (i.e. mathematical concept) the predicted 3D imbibition phase saturation level amounts to performing a mental process on a generic computer, since a person can reasonably utilize an algorithm to approximate a multitude of values, such as those within a “3D” saturation profile, with/without the aid of pen and paper. Additionally, per MPEP 2106.04(a)(I)(C), “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. [ ] ” Examples of mathematical calculations recited in a claim include: [ ] v. using an algorithm for determining the optimal number of visits by a business representative to a client”.)
deriving, using a processor, a derived one-dimensional drainage phase saturation profile from the measured three-dimensional drainage phase saturation profile; (Per Applicant’s disclosure (Spec. [P.0037]), “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average”. A person can reasonably evaluate data and then derive/calculate (i.e. mathematical concept) a one-dimensional phase saturation profile, with/without the aid of pen/paper.)
calculating, using the processor, a measured oil-water contact angle in the porous medium, a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium; (The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Also, a person can reasonably calculate (i.e. mathematical concept) cited limitations with/without the aid of pen/paper.)
calculating, using the processor, a simulated one-dimensional drainage phase saturation profile from the simulated three-dimensional drainage phase saturation profile, and a simulated one-dimensional imbibition phase saturation profile from the simulated three-dimensional imbibition phase saturation profile; (Per Applicant’s disclosure (Spec. [P.0051]), “The simulated one-dimensional drainage phase saturation profiles 20s and the simulated one-dimensional imbibition phase saturation profiles 30s are calculated from the simulated three-dimensional drainage phase saturation profile 25s and the simulated three-dimensional imbibition phase saturation profile 35s for the different fraction flow rates using the mathematical average”. A person can reasonably calculate (i.e. mathematical concept) simulated one-dimensional drainage/imbibition phase saturation profiles, with/without the aid of pen/paper. Applicant also discloses (Spec. [P.0024 and 0026]) Fig.2B and Fig.2D as examples of simulated 1D drainage/imbibition phase saturation profiles, which both can reasonably be calculated by a person with/without the aid of pen/paper.)
Additionally, per MPEP 2106.04(a)(2)(III), “Claims can recite a mental process even if they are claimed as being performed on a computer.” Thus, Applicant’s argument not persuasive.
Applicant argues [Pg.12 P.3] that the claims as a whole integrate into a practical application satisfying Step 2A Prong 2 and [Pg.13-14] recite significantly more than the judicial exception under Step 2B of the Alice/Mayo framework. The Examiner respectfully disagrees.
The steps of the subject matter eligibility analysis for products and processes that are to be used during examination for evaluating whether a claim is drawn to patent-eligible subject matter is the following:
Step 1: Determine if the claim is directed to a process, machine, manufacture, or composition of matter. Claims 1, 6-9, and 11-12 are directed to a method, therefore fall within the statutory category of a process. Claims 3-5 are directed to a system, therefore fall within the statutory category of manufacture.
Step 2A (Prong 1): Determine if the claim is directed to a law of nature, a natural phenomenon (product of nature), or an abstract idea. Independent claims 1, 3, and 6 are all directed towards an abstract idea (mental processes and/or mathematical concepts) – see above remarks and 35 USC §101 analysis below.
Step 2A (Prong 2)/Step 2B: Determine if the claim recites additional elements that amount to significantly more than the judicial exception. As shown in 35 USC §101 analysis section below, the additional elements as described in Step 2A Prong 2 are not sufficient to amount to significantly more than the judicial exception because the additional limitations are considered Insignificant Extra-solution Activity (mere data gathering) and/or Mere Instructions to Apply an Exception per MPEP 2106.05(f)/(g).
The additional elements identified (e.g. Claim 1) can be summarized as receiving data (i.e. obtaining, inputting), simulating data, and training an algorithm.
Receiving data amounts to Insignificant Extra-solution Activity (mere data gathering, pre-solution activity) per MPEP 2106.05(g). Simulating data for the purpose of capturing data for a claimed method/process also amounts to mere data gathering. Per MPEP 2106.05(g), “the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional”. Additionally, simulating data is interpreted as numerical simulation (i.e. repetitive calculations) which amounts to Mere Instructions to Apply an Exception per MPEP 2106.05(f). Specifically, this limitation invokes computers or other machinery merely as a tool to perform an existing process, i.e. repetitive calculations, which a person can reasonably perform with/without the aid of pen/paper.
And training a machine learning algorithm amounts to Mere Instructions to Apply an Exception per MPEP 2106.05(f). Specifically, the limitation is directed towards mere instructions to implement an abstract idea on a computer. Additionally, the limitation recites only the idea of a solution or outcome i.e. fails to recite details of how the machine learning algorithm is trained.
Per MPEP 2106.05(d), another consideration when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry. Per MPEP 2106.05(d)(II), The courts have recognized the following applicable computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network (e.g. data gathering), ii. Performing repetitive calculations (e.g. mathematical simulation and training a machine learning algorithm), iii. Electronic recordkeeping, and iv. Storing and retrieving information in memory. Additionally, the training and use of machine learning algorithms are WURC given Applicant’s disclosure “Examples of the machine learning algorithm 130 include, but are not limited to an artificial neural network, a XGBoost-algorithm, a recurrent neural networks or a combination of these.” Spec. [P.0055].
Per MPEP 2106.05(f)(2), “examples where the courts have found the additional elements to be mere instructions to apply an exception, because they do no more than merely invoke computers or machinery as a tool to perform an existing process include... v. Requiring the use of software to tailor information and provide it to the user on a generic computer, Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1370-71, 115 USPQ2d 1636, 1642 (Fed. Cir. 2015). Applicant discloses “The porous media fluid flow simulator 120 can be a proprietary software such as the calculation solutions offered by CMG Computer Modelling Group Ltd.” Spec. [P.0044].
Since the additional elements of receiving data, simulating data, and training an algorithm are directed towards Insignificant Extra-solution Activity and/or Mere Instructions to Apply an Exception, and have been determined to be well understood, routine, conventional activity, claim 1 is directed to an abstract idea without significantly more and is rejected as not patent eligible under 35 U.S.C. 101.
Similar rationale for rejection is provided for remaining independent / dependent claims below.
Claim Rejections under 35 U.S.C. § 103:
Acknowledgement is made of amended claims. Applicant’s arguments have been fully considered but not persuasive. Previous rejections are maintained.
Additionally, significant amendments to claims warrant new grounds of rejection.
See Claim Rejections - 35 U.S.C. § 103 section below.
Applicant argues [Pg.15-16] that primary referenced art, Ni, does not teach or suggest the amended workflow recited in claim 1 and that the secondary reference, Saxena, doesn’t remedy the deficiencies of Ni. The Examiner respectfully disagrees.
As shown in Claim Rejections - 35 U.S.C. § 103 section below, Ni discloses all amended limitations including the prediction of a rock core’s CO2 residual trapping ability (which includes 3D imbibition profiles), obtaining CT scan data, deriving drainage/imbibition saturation profiles from obtained data, simulating data using a fluid flow simulator, calculating parameters, etc., with the exception of training and utilizing a machine learned algorithm in order to predict saturation profiles. Saxena, on the other hand, does disclose training a backpropagation-enabled model (i.e. machine learning algorithm) and then utilizing the trained backpropagation-enabled model to estimate (i.e. approximate) fluid saturation of a porous medium. As disclosed below, it would have been obvious to one of ordinary skill in the art before the Applicant' s effective filling date of the claimed invention to have integrated machine learning, such as disclosed by Saxena, with the drainage / imbibition profile prediction study, as disclosed by Ni, in order “to provide faster, more, and less expensive analysis of hydrocarbon-containing formation rocks to determine key petrophysical characteristics of the rocks.” Saxena [P.0004].
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). Thus, Applicant’s argument not persuasive.
Applicant’s arguments [Pg.16-17] with respect to claim(s) 3-5 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant’s arguments [Pg.17-19] regarding claim(s) 6, 7, 9 and 12 with respect to AlRatrout and Ji-Quan have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. With respect to Ni-Saxena, as described above and in Claim Rejections - 35 U.S.C. § 103 section below, Ni in view of Saxena disclose all amended limitations of claims 6, 7, 9, and 12.
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). Thus, Applicant’s argument not persuasive.
In response to applicant's argument [Pg.19-20] regarding claim 8, that the reference (i.e. Hasem) fails to show certain features of the invention, it is noted that the features upon which applicant relies are not recited in the rejected claim. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Thus, Applicant’s argument not persuasive.
Applicant’s argument [Pg.20-21] with respect to claim 11 has been considered but moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Objections
Claim 1 is objected to because of the following informalities:
Line 4 states “saturation profile (25m) of a core-plug”, which appears to be a copy/paste error from FIG.1B. Examiner suggests re-wording line 4 to state “saturation profile of a core-plug”. The “(25m)” is unnecessary.
Line 24 states “deriving, using a processor, a derived one-dimensional”. The limitation “a derived” is repetitive an unnecessary. Examiner suggests re-wording line 24 to state “deriving, using a processor, a one-dimensional”.
Claim 3 is objected to because of the following informalities:
Line 15 states “deriving, using a processor, a derived one-dimensional”. The limitation “a derived” is repetitive an unnecessary. Examiner suggests re-wording line 15 to state “deriving, using a processor, a one-dimensional”.
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, 3-9 and 11-12 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, is directed to that judicial exception (an abstract idea), as it has not been integrated into a practical application and the claim(s) further do/does not recite significantly more than the judicial exception. Examiner has evaluated the claim(s) under the framework provided in MPEP 2106 and has provided such analysis below.
To determine if a claim is directed to patent ineligible subject matter, the Court
has guided the Office to apply the Alice/Mayo test, which requires:
Step 1. Determining if the claim falls within a statutory category of a Process, Machine, Manufacture, or a Composition of Matter (see MPEP 2106.03);
Step 2A. Determining if the claim is directed to a patent ineligible judicial exception consisting of a law of nature, a natural phenomenon, or abstract idea (MPEP 2106.04);
Step 2A is a two-prong inquiry. MPEP 2106.04(II)(A).
Under the first prong, examiners evaluate whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. Abstract ideas include mathematical concepts, certain methods of organizing human activity, and mental processes. MPEP 2106.04(a)(2).
The second prong is an inquiry into whether the claim integrates a judicial exception into a practical application. MPEP 2106.04(d).
Step 2B. If the claim is directed to a judicial exception, determining if the claim recites limitations or elements that amount to significantly more than the judicial exception. (See MPEP 2106).
Step 1:
Claims 1, 6-9, and 11-12 are directed to a method, as such these claims fall within the statutory category of a process.
Claims 3-5 are directed to a system, as such these claims fall within the statutory category of manufacture.
Step 2A, Prong 1:
The examiner submits that the foregoing claim limitations constitute abstract ideas, as the claims cover Mental Processes and/or Mathematical Concepts, given the broadest reasonable interpretation.
In order to apply Step 2A, a recitation of claims is copied below. The limitations of those claims which describe an abstract idea are bolded.
As per independent claim 1, the claim recites the limitations of:
A computer-implemented method for predicting a three-dimensional imbibition phase saturation profile of a porous rock medium, the method comprising: (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) which are defined as concepts that can practically be performed in the human mind (e.g. observations, evaluations, judgments, opinions), or by a human using pen and paper as a physical aid. Specifically, the claimed limitation is directed towards performing a mental process on a generic computer since a person can reasonably perform the claim limitations with/without the aid of pen and paper. Additionally, to “predict” is inherent to a mental process as it requires observing data, evaluating patterns, making a judgement based on those evaluations, and forming an opinion about the outcome.)
deriving, by a processor, a one-dimensional drainage phase saturation profile from the at least one measured three-dimensional drainage phase saturation profile (As drafted and under its broadest reasonable interpretation, in light of the Specification, this limitation amounts to Mental Processes (MPEP 2106.04 (a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Per Applicant’s disclosure (Spec. [P.0037]), “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average”. A person can reasonably evaluate data and then derive/calculate (i.e. mathematical concept) a one-dimensional phase saturation profile, with/without the aid of pen/paper.)
and approximating, using the machine learning algorithm executed on the
processor, the predicted three-dimensional imbibition phase saturation profile based on the input; (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106(a)(2)(I)). Specifically, the use of an algorithm (i.e. mathematical concept) executed on a processor to approximate (i.e. mathematical concept) the predicted 3D imbibition phase saturation level amounts to performing a mental process on a generic computer, since a person can reasonably utilize an algorithm to approximate a multitude of values, such as those within a “3D” saturation profile, with/without the aid of pen and paper. Additionally, per MPEP 2106.04(a)(I)(C), “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. [ ] ” Examples of mathematical calculations recited in a claim include: [ ] v. using an algorithm for determining the optimal number of visits by a business representative to a client”.)
deriving, using a processor, a derived one-dimensional drainage phase saturation profile from the measured three-dimensional drainage phase saturation profile; (As drafted and under its broadest reasonable interpretation, in light of the Specification, this limitation amounts to Mental Processes (MPEP 2106.04 (a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Per Applicant’s disclosure (Spec. [P.0037]), “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average”. A person can reasonably evaluate data and then derive/calculate (i.e. mathematical concept) a one-dimensional phase saturation profile, with/without the aid of pen/paper.)
calculating, using the processor, a measured oil-water contact angle in the porous medium, a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium; (As drafted and under its broadest reasonable interpretation, in light of the Specification, this limitation amounts to Mental Processes (MPEP 2106.04 (a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Also, a person can reasonably calculate (i.e. mathematical concept) cited limitations with/without the aid of pen/paper.)
calculating, using the processor, a simulated one-dimensional drainage phase saturation profile from the simulated three-dimensional drainage phase saturation profile, and a simulated one-dimensional imbibition phase saturation profile from the simulated three-dimensional imbibition phase saturation profile; (As drafted and under its broadest reasonable interpretation, in light of the Specification, this limitation amounts to Mental Processes (MPEP 2106.04 (a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Per Applicant’s disclosure (Spec. [P.0051]), “The simulated one-dimensional drainage phase saturation profiles 20s and the simulated one-dimensional imbibition phase saturation profiles 30s are calculated from the simulated three-dimensional drainage phase saturation profile 25s and the simulated three-dimensional imbibition phase saturation profile 35s for the different fraction flow rates using the mathematical average”. A person can reasonably calculate (i.e. mathematical concept) simulated one-dimensional drainage/imbibition phase saturation profiles, with/without the aid of pen/paper. Applicant also discloses (Spec. [P.0024 and 0026]) Fig.2B and Fig.2D as examples of simulated 1D drainage/imbibition phase saturation profiles, which both can reasonably be calculated by a person with/without the aid of pen/paper.)
Step 2A, Prong 2:
As per claim 1, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present Insignificant Extra-solution Activity and/or Mere Instructions to Apply an Exception. In particular, the claim recites the additional limitations:
obtaining, from a detection device, comprising a medical-CT-core-flooding apparatus, at least one three-dimensional drainage phase-saturation profile (25m) of a core-plug measured during a drainage core-flooding experiment on the core-plug, and inputting the at least one measured three-dimensional drainage phase saturation profile into a machine learning algorithm; and inputting the derived one-dimensional drainage phase saturation profile into the machine learning algorithm; obtaining, from the detection device, at least one one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug and inputting the at least one measured one-dimensional imbibition phase saturation profile into the machine learning algorithm; obtaining, from a detection device comprising a medical-CT-core-flooding apparatus, a three-dimensional drainage phase-saturation profile of a core-plug measured during a drainage core-flooding experiment on the core-plug; obtaining, from the detection device, a one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug; feeding the measured three-dimensional drainage phase saturation profile, the derived one-dimensional drainage phase saturation profile, the measured one-dimensional imbibition phase saturation profile, the measured oil- water contact angle, the calculated synthetic values for the relative permeability, the calculated synthetic values for the capillary pressure, and a rock heterogeneity state into a porous media fluid flow simulator; (The additional elements amount to Insignificant Extra-solution Activity (mere data gathering, pre-solution activity) per MPEP 2106.05(g). The 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. The limitations of “obtaining” data from detection devices, “inputting” data into the machine learning algorithm, and “feeding” data into a flow simulator all amount to mere data gathering / pre-solution activity.)
simulating, using the porous media fluid flow simulator, a simulated three- dimensional drainage phase saturation profile and a simulated three-dimensional imbibition phase saturation profile; (The additional element amounts to Insignificant Extra-Solution Activity (mere data gathering) per MPEP 2106.05(g) and/or Mere Instructions to Apply an Exception per MPEP 2106.05(f). “Simulating” saturation profiles for the purpose of capturing input data for the training algorithm is interpreted as mere data gathering. The limitation is also directed towards mere instructions to implement an abstract idea (i.e. mental processes and/or mathematical concepts) on a computer.)
and training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one-dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, the machine learning algorithm. (The additional element amounts to Mere Instructions to Apply an Exception per MPEP 2106.05(f). Specifically, the limitation is directed towards mere instructions to implement an abstract idea (i.e. predicting a three-dimensional imbibition phase saturation profile) on a computer. Additionally, the limitation recites only the idea of a solution or outcome i.e. fails to recite details of how the machine learning algorithm is trained.)
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considered as an ordered combination and as a whole. Per MPEP 2106.05(g), “the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional” and per MPEP 2106.05(f)(1), “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".
Step 2B:
For step 2B of the analysis, the Examiner must consider whether each claim limitation individually or as an ordered combination amounts to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same.
The additional elements as described in Step 2A Prong 2 are not sufficient to amount to significantly more than the judicial exception because the additional limitations are considered directed towards Insignificant Extra-solution Activity (mere data gathering, pre-solution activity) and/or Mere Instructions to Apply an Exception per MPEP 2106.05(g)/(f).
As mentioned within Step 2A Prong 2, per MPEP 2106.05(g), “the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional”. Per MPEP 2106.05(d)(II), The courts have recognized the following (applicable) computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network (e.g. data gathering), ii. Performing repetitive calculations (e.g. mathematical simulation and training the machine learning algorithm), iii. Electronic recordkeeping, and iv. Storing and retrieving information in memory.
For the foregoing reasons, claim 1 is directed to an abstract idea without significantly more and is rejected as not patent eligible under 35 U.S.C. 101.
Step 2A, Prong 1 (Claim 3):
The examiner submits that the foregoing claim limitations constitute abstract ideas, as the claims cover Mental Processes and/or Mathematical Concepts, given the broadest reasonable interpretation.
In order to apply Step 2A, a recitation of claims is copied below. The limitations of those claims which describe an abstract idea are bolded.
As per independent claim 3, the claim recites the limitations of:
A measurement system for predicting a three-dimensional imbibition phase saturation profile for imbibition of a porous rock medium, the system comprising: (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) which are defined as concepts that can practically be performed in the human mind (e.g. observations, evaluations, judgments, opinions), or by a human using pen and paper as a physical aid. Specifically, the claimed limitation is directed towards performing a mental process on a generic computer since a person can reasonably perform the claim limitation with/without the aid of pen and paper. Additionally, to “predict” is inherent to a mental process as it requires observing data, evaluating patterns, making a judgement based on those evaluations, and forming an opinion about the outcome.)
deriving, using a processor, a derived one-dimensional drainage phase saturation profile from the measured three-dimensional drainage phase saturation profile; (As drafted and under its broadest reasonable interpretation, in light of the Specification, this limitation amounts to Mental Processes (MPEP 2106.04 (a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Per Applicant’s disclosure (Spec. [P.0037]), “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average”. A person can reasonably evaluate data and then derive/calculate (i.e. mathematical concept) a one-dimensional phase saturation profile, with/without the aid of pen/paper.)
calculating, using the processor, a measured oil-water contact angle in the porous medium, a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium; (As drafted and under its broadest reasonable interpretation, in light of the Specification, this limitation amounts to Mental Processes (MPEP 2106.04 (a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Also, a person can reasonably calculate (i.e. mathematical concept) cited limitations with/without the aid of pen/paper.)
calculating, using the processor, a simulated one-dimensional drainage phase saturation profile from the simulated three-dimensional drainage phase saturation profile, and a simulated one-dimensional imbibition phase saturation profile from the simulated three-dimensional imbibition phase saturation profile; (As drafted and under its broadest reasonable interpretation, in light of the Specification, this limitation amounts to Mental Processes (MPEP 2106.04 (a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Per Applicant’s disclosure (Spec. [P.0051]), “The simulated one-dimensional drainage phase saturation profiles 20s and the simulated one-dimensional imbibition phase saturation profiles 30s are calculated from the simulated three-dimensional drainage phase saturation profile 25s and the simulated three-dimensional imbibition phase saturation profile 35s for the different fraction flow rates using the mathematical average”. A person can reasonably calculate (i.e. mathematical concept) simulated one-dimensional drainage/imbibition phase saturation profiles, with/without the aid of pen/paper. Applicant also discloses (Spec. [P.0024 and 0026]) Fig.2B and Fig.2D as examples of simulated 1D drainage/imbibition phase saturation profiles, which both can reasonably be calculated by a person with/without the aid of pen/paper.)
deriving, by the processor, a one-dimensional drainage phase saturation profile from the at least one measured three-dimensional drainage phase saturation profile (As drafted and under its broadest reasonable interpretation, in light of the Specification, this limitation amounts to Mental Processes (MPEP 2106.04 (a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Per Applicant’s disclosure (Spec. [P.0037]), “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average”. A person can reasonably evaluate data and then derive/calculate (i.e. mathematical concept) a one-dimensional phase saturation profile, with/without the aid of pen/paper.)
approximating, using the machine learning algorithm executed on the processor, the predicted three-dimensional imbibition phase saturation profile based on the input. (“(As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a computer and/or Mathematical Concepts (MPEP 2106(a)(2)(I)). Specifically, the use of an algorithm (i.e. mathematical concept) executed on a processor to approximate (i.e. mathematical concept) the predicted 3D imbibition phase saturation level amounts to performing a mental process on a generic computer, since a person can reasonably perform the claimed limitation with/without the aid of pen and paper. Additionally, per MPEP 2106.04(a)(I)(C), “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. [ ] ” Examples of mathematical calculations recited in a claim include: [ ] v. using an algorithm for determining the optimal number of visits by a business representative to a client”.)
Step 2A, Prong 2 (Claim 3):
As per claim 3, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present Insignificant Extra-Solution Activity and/or Mere Instructions to Apply an Exception. In particular, the claim recites the additional limitations:
a processor, for executing at least one of a special core analysis laboratory (SCAL) porous media fluid flow simulator and a machine learning algorithm; (The additional claim limitations amount to Mere Instructions to Apply an Exception (MPEP 2106.05(f)). MPEP 2106.05(f) states the 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.)
a memory, connected to the processor, for storing items of SCAL data of a target core plug on at least one of an oil-water contact angle, a relative permeability, and a capillary pressure (The additional claim limitations amount to Mere Instructions to Apply an Exception (MPEP 2106.05(f)). MPEP 2106.05(f) states the 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.)
and a detection device comprising a medical-CT-core-flooding apparatus for determining the SCAL data; (The additional claim limitations amount to Mere Instructions to Apply an Exception (MPEP 2106.05(f)). MPEP 2106.05(f) states the 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.)
wherein the machine learning algorithm has been trained by: obtaining, from a detection device comprising a medical-CT-core-flooding apparatus, a three-dimensional drainage phase-saturation profile of a core-plug measured during a drainage core-flooding experiment on the core-plug; obtaining, from the detection device, a one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug; feeding the measured three-dimensional drainage phase saturation profile, the derived one-dimensional drainage phase saturation profile, the measured one- dimensional imbibition phase saturation profile, the measured oil-water contact angle, the calculated synthetic values for the relative permeability, the calculated synthetic values for the capillary pressure, and a rock heterogeneity state into a porous media fluid flow simulator; (The additional elements amount to Insignificant Extra-solution Activity (mere data gathering, pre-solution activity) per MPEP 2106.05(g). The 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. The limitations of “obtaining” data from detection devices and “feeding” data into a flow simulator all amount to mere data gathering / pre-solution activity.)
simulating, using the porous media fluid flow simulator, a simulated three- dimensional drainage phase saturation profile and a simulated three-dimensional imbibition phase saturation profile; (The additional element amounts to Insignificant Extra-Solution Activity (mere data gathering) per MPEP 2106.05(g) and/or Mere Instructions to Apply an Exception per MPEP 2106.05(f). “Simulating” saturation profiles for the purpose of capturing input data for the training algorithm is interpreted as mere data gathering. The limitation is also directed towards mere instructions to implement an abstract idea (i.e. mental processes and/or mathematical concepts) on a computer.)
and training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one- dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, the machine learning algorithm; (The additional element amounts to Mere Instructions to Apply an Exception per MPEP 2106.05(f). Specifically, the limitation is directed towards mere instructions to implement an abstract idea (i.e. predicting a three-dimensional imbibition phase saturation profile) on a computer. Additionally, the limitation recites only the idea of a solution or outcome i.e. fails to recite details of how the machine learning algorithm is trained.)
so that the machine learning algorithm performs a method for predicting the three-dimensional imbibition phase saturation profile of the porous rock medium comprising: obtaining, from the detection device, at least one three-dimensional drainage phase-saturation profile of the core-plug measured during a drainage core-flooding experiment on the core-plug and inputting the at least one measured three-dimensional drainage phase saturation profile into the machine learning algorithm; and inputting the derived one-dimensional drainage phase saturation profile into the machine learning algorithm; obtaining, from the detection device, at least one one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug and inputting the at least one measured one-dimensional imbibition phase saturation profile into the machine learning algorithm; (The additional elements amount to Insignificant Extra-solution Activity (mere data gathering, pre-solution activity) per MPEP 2106.05(g). The 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. The limitations of “obtaining” data from detection devices and “inputting” data into the machine learning algorithm amount to mere data gathering / pre-solution activity.)
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considered as an ordered combination and as a whole. Per MPEP 2106.05(g), “the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional” and per MPEP 2106.05(f)(1), “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".
Step 2B (Claim 3):
For step 2B of the analysis, the Examiner must consider whether each claim limitation individually or as an ordered combination amounts to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same.
The additional elements as described in Step 2A Prong 2 are not sufficient to amount to significantly more than the judicial exception because the additional limitations are considered directed towards Insignificant Extra-solution Activity (mere data gathering, pre-solution activity) and/or Mere Instructions to Apply an Exception per MPEP 2106.05(g)/(f).
As mentioned within Step 2A Prong 2, per MPEP 2106.05(g), “the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional”. Per MPEP 2106.05(d)(II), The courts have recognized the following (applicable) computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network (e.g. data gathering), ii. Performing repetitive calculations (e.g. mathematical simulation and training the machine learning algorithm), iii. Electronic recordkeeping, and iv. Storing and retrieving information in memory.
For the foregoing reasons, claim 3 is directed to an abstract idea without significantly more and is rejected as not patent eligible under 35 U.S.C. 101.
Step 2A, Prong 1 (Claim 6):
The examiner submits that the foregoing claim limitations constitute abstract ideas, as the claims cover Mental Processes and/or Mathematical Concepts, given the broadest reasonable interpretation.
In order to apply Step 2A, a recitation of claims is copied below. The limitations of those claims which describe an abstract idea are bolded.
As per independent claim 6, the claim recites the limitations of:
A computer-implemented method for training a machine learning algorithm for predicting three-dimensional imbibition phase saturation profile for imbibition of a porous rock medium, the method comprising: (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) which are defined as concepts that can practically be performed in the human mind (e.g. observations, evaluations, judgments, opinions), or by a human using pen and paper as a physical aid. Specifically, the claimed limitation is directed towards performing a mental process on a generic computer since a person can reasonably perform the claim limitation with/without the aid of pen and paper. Additionally, to “predict” is inherent to a mental process as it requires observing data, evaluating patterns, making a judgement based on those evaluations, and forming an opinion about the outcome.)
deriving, using a processor, a derived one-dimensional drainage phase saturation profile from a measured three-dimensional drainage phase saturation profile; (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) since a person can reasonably derive a saturation profile from another measured saturation profile with/without the aid of pen and paper. Specifically, this limitation amounts to performing a mental process on a computer.)
calculating, using the processor and a measured oil-water contact angle in the porous medium, a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium; (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) and/or Mathematical Concepts (MPEP 2106(a)(2)(I)). For instance, using a processor to calculate (i.e. mathematical concept) a plurality of synthetic values and a capillary pressure amounts to performing a mental process on a generic computer, since a person can reasonably perform the claimed limitation with/without the aid of pen and paper.)
calculating, using the processor, a simulated one-dimensional drainage phase saturation profile from the simulated three-dimensional drainage phase saturation profile, and a simulated one-dimensional imbibition phase saturation profile from the simulated three-dimensional imbibition phase saturation profile; (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) and/or Mathematical Concepts (MPEP 2106(a)(2)(I)). For instance, using a processor to calculate (i.e. mathematical concept) a saturation profile from another saturation profile amounts to performing a mental process on a generic computer, since a person can reasonably perform the claimed limitation with/without the aid of pen and paper.)
Step 2A, Prong 2 (Claim 6):
As per claim 6, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present Insignificant Extra-solution Activity and/or Mere Instructions to Apply an Exception. In particular, the claim recites the additional limitations:
obtaining, from a detection device comprising a medical-CT-core-flooding apparatus, a three-dimensional drainage phase-saturation profile of a core-plug measured during a drainage core-flooding experiment on the core-plug; obtaining, from the detection device, a one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug; feeding a measured three-dimensional drainage phase saturation profile, the derived one-dimensional drainage phase saturation profile, a measured one-dimensional imbibition phase saturation profile, the measured oil- water contact angle, the calculated synthetic values for the relative permeability, the calculated synthetic values for the capillary pressure, and a rock heterogeneity state into a porous media fluid flow simulator; (The additional elements amount to Insignificant Extra-solution Activity (mere data gathering, pre-solution activity) per MPEP 2106.05(g). The 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. The limitations of “obtaining” data from detection devices and “feeding” data into the fluid flow simulator amount to mere data gathering / pre-solution activity.)
simulating, using the porous media fluid flow simulator, a simulated three-dimensional drainage phase saturation profile and a simulated three-dimensional imbibition phase saturation profile; (The additional element amounts to Insignificant Extra-Solution Activity (mere data gathering) per MPEP 2106.05(g) and/or Mere Instructions to Apply an Exception per MPEP 2106.05(f). “Simulating” saturation profiles for the purpose of capturing input data for the training algorithm is interpreted as mere data gathering. The limitation is also directed towards mere instructions to implement an abstract idea (i.e. mental processes and/or mathematical concepts) on a computer.)
and training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one-dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, a machine learning algorithm. (The additional element amounts to Mere Instructions to Apply an Exception per MPEP 2106.05(f). Specifically, the limitation is directed towards mere instructions to implement an abstract idea (i.e. predicting a three-dimensional imbibition phase saturation profile) on a computer. Additionally, the limitation recites only the idea of a solution or outcome i.e. fails to recite details of how the machine learning algorithm is trained.)
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considered as an ordered combination and as a whole. Per MPEP 2106.05(g), “the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional” and per MPEP 2106.05(f)(1), “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".
Step 2B (Claim 6):
For step 2B of the analysis, the Examiner must consider whether each claim limitation individually or as an ordered combination amounts to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same.
The additional elements as described in Step 2A Prong 2 are not sufficient to amount to significantly more than the judicial exception because the additional limitations are considered directed towards Insignificant Extra-solution Activity (mere data gathering, pre-solution activity) and/or Mere Instructions to Apply an Exception per MPEP 2106.05(f)/(g).
As mentioned within Step 2A Prong 2, per MPEP 2106.05(g), “the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional”. Per MPEP 2106.05(d)(II), The courts have recognized the following (applicable) computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network (e.g. data gathering), ii. Performing repetitive calculations (e.g. mathematical simulation and training the machine learning algorithm), iii. Electronic recordkeeping, and iv. Storing and retrieving information in memory.
For the foregoing reasons, claim 6 is directed to an abstract idea without significantly more and is rejected as not patent eligible under 35 U.S.C. 101.
Claim 2 has been canceled.
Claim 4, the measurement system of claim 3, further discloses, the SCAL-data is used in reservoir simulation models for a prediction of oil and gas field behavior. The analysis of the parent claim is incorporated. The additional limitation elaborates on the simulator data disclosed in Claim 3 (from which this claim depends), therefore further elaborating Mere Instructions to Apply an Exception (MPEP 2106.05(f)) and/or Insignificant Extra-Solution Activity (mere data gathering) per MPEP 2106.05(g). Additionally, this limitation is directed towards Field of Use and Technological Environment (MPEP 2106.05(h) since the use of the data is limited to a particular environment (i.e. reservoir simulation models of oil and gas field). Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 5, the measurement system of claim 3, further discloses the detection device comprises at least one of a linear X-Ray scanner or a Gamma Ray scanner. The analysis of the parent claim is incorporated. The additional limitation is directed towards Field of Use and Technological Environment (MPEP 2106.05(h)). Specifically, the limitation amounts to generally linking the use of a judicial exception to a particular technological environment (i.e. limited to specific types of scanners/equipment). Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 7, the computer-implemented method of claim 6, further discloses measuring a three-dimensional drainage phase saturation profile using an in-situ core flooding monitoring tool comprising a CT-scanner. The analysis of the parent claim is incorporated. The additional limitation amounts to Mere Instructions to Apply an Exception (MPEP 2106.05(f)). Specifically, the limitation amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer or other machinery to perform an existing process, since the claim fails to recite details of how a solution to a problem (i.e. measuring a three-dimensional drainage phase saturation profile) is accomplished. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 8, the computer-implemented method of claim 6, further discloses measuring fluid properties of a crude oil. The analysis of the parent claim is incorporated. The additional limitation amounts to Mere Instructions to Apply an Exception (MPEP 2106.05(f)). Specifically, the limitation amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer or other machinery as a tool to perform an existing process, since the claim fails to recite details of how a solution to a problem (i.e. measuring fluid properties) is accomplished. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 9, the computer-implemented method of claim 6, further discloses identifying a sister plug for the selected core plug. The analysis of the parent claim is incorporated. The additional limitation amounts to performing a mental processes on a computer (MPEP 2106.04(a)(2)(III)), since a person can reasonably identify a sister plug with/without the aid of pen and paper. Additionally, to “identify” is inherent to mental processes since it requires observation, evaluation, and judgement. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 10 has been canceled.
Claim 11, the computer-implemented method of claim 6, further discloses measuring an oil-water contact angle in the porous medium using at least one of analytical or experimental techniques. The additional limitation amounts to performing a mental processes on a computer (MPEP 2106.04(a)(2)(III)), since a person can reasonably measure an oil-water angle by analytical or experimental technique with/without the aid of pen and paper. Additionally, to “analyze” or “experiment” is inherent to mental processes since it requires observation, evaluation, and judgement. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 12, the computer-implemented method of claim 6, further discloses wherein determining the rock heterogeneity state comprises using a medical CT scanner. The analysis of the parent claim is incorporated. The additional limitation amounts to Mere Instructions to Apply an Exception (MPEP 2106.05(f)). Specifically, the limitation amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer or other machinery as a tool to perform an existing process, since the claim fails to recite details of how a solution to a problem (i.e. determining a rock heterogeneity) is accomplished. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham V. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that
are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are
summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or
nonobviousness.
Claims 1, 6-7, 9 and 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Ni, Hailun, Maartje Boon, Charlotte Garing, and Sally M. Benson. "Predicting CO2 residual trapping ability based on experimental petrophysical properties for different sandstone types." International Journal of Greenhouse Gas Control 86 (2019): 158-176. (hereinafter referred to as “Ni”) in view of SAXENA et al. US Pub. No. 2023/0137288 A1 (hereinafter referred to as “Saxena”).
Regarding claim 1, Ni discloses, A computer-implemented method for predicting a three-dimensional imbibition phase saturation profile of a porous rock medium, the method comprising: (“the first question that this study will focus on is how the CO2 residual trapping ability differs for different sandstone types and how we can make better predictions about a sandstone rock core’s CO2 residual trapping ability.” Ni [Pg.159 Col.2 P.2]. CO2 residual trapping ability is interpreted to include 3D imbibition phase saturation profile due to the following disclosure: “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner” Ni [Pg.160 Col.1 P.last], “CO2 saturation values are calculated at the core (mean saturation), slice (1D saturation profile), and voxel (3D saturation map) levels” Ni [Pg.162 Col.2 Sec.2.2.3])
obtaining, from a detection device, comprising a medical-CT-core-flooding apparatus, at least one three-dimensional drainage phase-saturation profile (25m) of a core-plug measured during a drainage core-flooding experiment on the core-plug, (“In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks.” Ni [Pg.160 Col.1 P.2]. The core flooding experiments are interpreted to include at least one 3D drainage phase saturation profile because “From the 3D CO2 saturation maps for both drainage and imbibition shown in Fig. 8, it can be observed that during imbibition the CO2 saturation maps are much more homogeneous than those during drainage” Ni [Pg.165 Col.2 P.3])
deriving, by a processor, a one-dimensional drainage phase saturation profile from the at least one measured three-dimensional drainage phase saturation profile (“The 1D slice-average [i.e. derived by a processor] CO2 saturation profiles along the length of the core and the 3D CO2 saturation maps are shown in Fig. 8” Ni [Pg.165 Sec.3.3 P.1]. Reference to “slice-average” is interpreted to mean “derived” due to Applicant’s disclosure “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average of the three-dimensional drainage phase saturation at each circular cross (i.e. slice)” Spec. [P.0037]. Also see Fig.8 [Pg.158] below.)
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230
391
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Greyscale
obtaining, from the detection device, at least one one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug (“The 1D slice-average CO2 saturation profiles along the length of the core and the 3D CO2 saturation maps are shown in Fig. 8” Ni [Pg.165 Sec.3.3 P.1]. The 1D slice-average is interpreted to include at least one measured 1D imbibition phase saturation profile. The saturation profiles are interpreted to be measured during an imbibition core-flooding experiment because “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks.” Ni [Pg.160 Col.1 P.2]) and
and approximating, , the predicted three-dimensional imbibition phase saturation profile based on the input (“both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples [ ] From
each experiment we extract multiple parameters, including the mean and standard deviation of the porosity field, the permeability field, and the CO2 saturation field, as well as variogram ranges [i.e. approximates] and different parameters that represent a rock core’s degree of mesoscale heterogeneity. These parameters were then correlated with both the Land and the linear trapping coefficients in order to infer which parameters best predict a sandstone core’s residual trapping ability” Ni [Pg.160 Col.1 P.2]. Residual trapping ability is interpreted to include 3D imbibition phase saturation profile because “CO2 saturation values are calculated at the core (mean saturation), slice (1D saturation profile), and voxel (3D saturation map) levels” Ni [Pg.162 Col.2 Sec.2.2.3])
obtaining, from a detection device comprising a medical-CT-core-flooding apparatus, a three-dimensional drainage phase-saturation profile of a core-plug measured during a drainage core-flooding experiment on the core-plug (see Ni [Pg.160 Col.1 P.2] above);
deriving, using a processor, a derived one-dimensional drainage phase saturation profile from the measured three-dimensional drainage phase saturation profile; (See Ni [Pg.165 Sec.3.3 P.1] above)
calculating, using the processor, a measured oil-water contact angle in the porous medium (“the voxel-level permeability field is derived using the extended iterative permeability method in Kraus’s work [ ] Krause’s permeability method first calculates an initial-guess permeability map using Eq. (7) based on the Leverett-J capillary pressure scaling relationship,
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media_image2.png
52
489
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where
k
i
and
i
are the voxel-level permeability and porosity values,
S
w
,
i
is the voxel-level water saturation,
P
-
c
(
S
w
) is the equilibrium capillary pressure within each slice as a function of saturation,
J
(
S
w
,
i
) is the Leverett-J function evaluated at each voxel’s water saturation value, and finally
σ
CO2/
w
a
t
e
r
and
θ
CO2/
w
a
t
e
r
are the CO2/water interfacial tension and contact angle respectively” Ni [Pg.163 Col.1 P.1]), a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium; (“We measure capillary pressure curves with a mercury porosimeter [ ] The measurements are performed on small plugs extracted from sections of sandstone rock cut from the cores used for the core flooding experiments [ ] The capillary pressure curves are shown in Fig. 2, and the least-square best-fit Brooks-Corey coefficients are shown in Table 2 [ ] All the parameters in Table 2 are then obtained by directly fitting the Brooks-Corey model to the corrected capillary pressure curves.” Ni [Pg.162 Col.1 Sec.2.2.1]. The Brooks-Corey coefficients are interpreted as a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium due to Applicant’s disclosure, “A plurality of synthetic values for the relative permeability 80 and a capillary pressure 90 of the selected core plug 50 are calculated in step S170. This calculating is done using mathematical methods such as but not limited to Brooks-Corey, LET and modified Corey models that are available in literature to define the capillary pressure and relative permeability curves.” Spec. [P.0042])
obtaining, from the detection device, a one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug; (See Ni [Pg.165 Sec.3.3 P.1] above.)
feeding the measured three-dimensional drainage phase saturation profile, the derived one-dimensional drainage phase saturation profile, the measured one-dimensional imbibition phase saturation profile, the measured oil-water contact angle, the calculated synthetic values for the relative permeability, and a rock heterogeneity state (“three parameters for measuring the degree of mesoscale heterogeneity are computed for each core sample” Ni [Pg.158 Col.2 P.1]) into a porous media fluid flow simulator; (Ni [Pg.167 Fig.6] discloses simulated permeability, porosity, and CO2 saturation maps, implying all disclosed parameters have been fed into a porous media fluid flow simulator.)
simulating, using the porous media fluid flow simulator (“The Stanford University General Purpose Research Simulator (GPRS), which has the capability to simulate capillary heterogeneity effects, is used for the simulations.” Ni [Pg.163 Col.1 P.3]), a simulated three- dimensional drainage phase saturation profile and a simulated three-dimensional imbibition phase saturation profile; (“voxel-level permeability values are not directly obtainable from CT image analysis. Rather, the voxel-level permeability field is derived using the extended iterative permeability method [ ] The extended iterative permeability method uses numerical simulations to simulate each core flooding experiment” Ni [Pg.163 Col.1 P.1-2]. Voxel-level permeability values are interpreted as three-dimensional saturation profiles and each core flooding experiment is interpreted to include drainage and imbibition phase saturations because “both drainage and imbibition core flooding experiments were conducted [ ] each experiment we extract multiple parameters, including [ ] the permeability field, and
the CO2 saturation field, as well as variogram ranges and different parameters that represent a rock core’s degree of mesoscale heterogeneity.” Ni [Pg.160 Col.1 P.2])
calculating, using the processor, a simulated one-dimensional drainage phase saturation profile from the simulated three-dimensional drainage phase saturation profile, and a simulated one-dimensional imbibition phase saturation profile from the simulated three-dimensional imbibition phase saturation profile; (“By inputting the core-averaged, slice-averaged [i.e. derived from 3D profiles], and voxel-level CT numbers into Eq. (5), the porosity values for the entire core (mean porosity), for each individual slice along the length of the core (one-dimensional (1D) porosity profile), and for each coarsened voxel inside the core (three-dimensional (3D) porosity map) are calculated respectively... As with the porosity measurements, CO2 saturation values are calculated at the core (mean saturation), slice (1D saturation profile), and voxel (3D saturation map) levels.” Ni [Pg.162 Sec.2.2.2 - 2.2.3]. The calculated saturated values are interpreted to include imbibition and drainage because “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner” Ni [Pg.160 Col.1 P.2]. Also, “sliced average” is interpreted to mean one-dimensional profiles are calculated from three-dimension profiles due to Applicant’s disclosure “The one-dimensional drainage phase [also includes imbibition phase. See Spec. [P.0045]] saturation profile 25d is calculated in Step S140 as a mathematical average of the three-dimensional drainage phase saturation at each circular cross section along the core plug” Spec. [P.0037])
Ni fails to specifically disclose inputting data (i.e. phase saturation profiles) into a machine learning algorithm and approximating, using the machine learning algorithm executing on a processor, and training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one-dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, the machine learning algorithm.
On the other hand, analogous art by Saxena discloses inputting [data (i.e. phase saturation profiles)] into a machine learning algorithm, and training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one-dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, the machine learning algorithm (“the trained model [i.e. machine learning algorithm] is produced by providing [i.e. inputting] a training set of images of rock, segmenting the images into a plurality of labeled voxels, the plurality of labeled voxels representing pore spaces and solid material in the rock, and using the labeled voxels to train a model via backpropagation. The training set of images of rock may include, for example, 2D projection images obtained from a pore-scale imaging technology, 3D images reconstructed from 2D projection images, synthetic 2D images, synthetic 3D images, and combinations thereof [ ] Examples of backpropagation-enabled processes include, without limitation, artificial intelligence, machine learning, and deep learning [ ] The backpropagation-enabled process may be supervised, semi-supervised, unsupervised or a combination thereof” Saxena [P.0021-23]) and approximating, using the machine learning algorithm executing on a processor (“a backpropagation-enabled method for estimating [i.e. approximating] the fluid saturation of rock from a 3D image of rock. A backpropagation-enabled trained model [i.e. machine learning algorithm] is applied to a 3D image to segment the 3D image of rock” Saxena [P.0020])
Ni and Saxena are analogous art as they both relate to predicting petrophysical parameters associated with a porous medium. Ni discloses a study that conducted “CO2/water core flooding experiments at reservoir conditions on nine core samples with different degrees and types of heterogeneity to find the best petrophysical properties for predicting sandstone CO2 residual trapping ability. We are able to extract petrophysical
properties such as porosity, permeability, degree of mesoscale heterogeneity, and spatial correlation lengths of petrophysical property fields in different directions using a CT scanner.” Ni [Pg.158 Abstract], which is analogous to the claimed invention, although doesn’t utilize a machine learning algorithm. Saxena, on the other hand, discloses an invention related to estimating fluid saturation in hydrocarbon-bearing rocks using digital rock physics. Its intended application is to provide a faster, more accurate, and cost-effective method for determining fluid saturation from 3D images of rock samples obtained from hydrocarbon formations. The method aims to overcome limitations of conventional laboratory measurements and image resolution constraints by correcting for sub-resolution pore volumes and applying backpropagation-enabled segmentation models (i.e. machine learning algorithms) to improve fluid saturation estimation for reservoir evaluation and management.
Therefore, it would have been obvious to one of ordinary skill in the art before the
Applicant' s effective filling date of the claimed invention to have integrated machine learning, such as disclosed by Saxena, with the drainage / imbibition profile prediction study, as disclosed by Ni, in order “to provide faster, more, and less expensive analysis of hydrocarbon-containing formation rocks to determine key petrophysical characteristics of the rocks.” Saxena [P.0004].
Claim 2 has been canceled.
Regarding independent claim 6, Ni discloses, A computer-implemented method for predicting three-dimensional imbibition phase saturation profile for imbibition of a porous rock medium, the method comprising: (“the first question that this study will focus on is how the CO2 residual trapping ability differs for different sandstone types and how we can make better predictions about a sandstone rock core’s CO2 residual trapping ability.” Ni [Pg.159 Col.2 P.2]. CO2 residual trapping ability is interpreted to include 3D imbibition phase saturation profile due to the following disclosure: “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner” Ni [Pg.160 Col.1 P. last], “CO2 saturation values are calculated at the core (mean saturation), slice (1D saturation profile), and voxel (3D saturation map) levels” Ni [Pg.162 Col.2 Sec.2.2.3])
obtaining, from a detection device comprising a medical-CT-core-flooding apparatus, a three-dimensional drainage phase-saturation profile of a core-plug measured during a drainage core-flooding experiment on the core-plug; (“In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks.” Ni [Pg.160 Col.1 P.2]. The core flooding experiments are interpreted to include at least one 3D drainage phase saturation profile because “From the 3D CO2 saturation maps for both drainage and imbibition shown in Fig. 8, it can be observed that during imbibition the CO2 saturation maps are much more homogeneous than those during drainage” Ni [Pg.165 Col.2 P.3])
deriving, using a processor, a derived one-dimensional drainage phase saturation profile from a measured three-dimensional drainage phase saturation profile; (“The 1D slice-average [i.e. derived] CO2 saturation profiles along the length of the core and the 3D CO2 saturation maps are shown in Fig. 8” Ni [Pg.165 Sec.3.3 P.1]. Reference to “slice-average” is interpreted to mean “derived” due to Applicant’s disclosure “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average of the three-dimensional drainage phase saturation at each circular cross [i.e. slice]” Spec. [P.0037]. Also see Fig.8 [Pg.158] below.)
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calculating, using the processor, a measured oil-water contact angle in the porous medium (“the voxel-level permeability field is derived using the extended iterative permeability method in Kraus’s work [ ] Krause’s permeability method first calculates an initial-guess permeability map using Eq. (7) based on the Leverett-J capillary pressure scaling relationship,
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52
489
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where
k
i
and
i
are the voxel-level permeability and porosity values,
S
w
,
i
is the voxel-level water saturation,
P
-
c
(
S
w
) is the equilibrium capillary pressure within each slice as a function of saturation,
J
(
S
w
,
i
) is the Leverett-J function evaluated at each voxel’s water saturation value, and finally
σ
CO2/
w
a
t
e
r
and
θ
CO2/
w
a
t
e
r
are the CO2/water interfacial tension and contact angle respectively” Ni [Pg.163 Col.1 P.1]), a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium; (“We measure capillary pressure curves with a mercury porosimeter [ ] The measurements are performed on small plugs extracted from sections of sandstone rock cut from the cores used for the core flooding experiments [ ] The capillary pressure curves are shown in Fig. 2, and the least-square best-fit Brooks-Corey coefficients are shown in Table 2 [ ] All the parameters in Table 2 are then obtained by directly fitting the Brooks-Corey model to the corrected capillary pressure curves.” Ni [Pg.162 Col.1 Sec.2.2.1]. The Brooks-Corey coefficients are interpreted as a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium due to Applicant’s disclosure, “A plurality of synthetic values for the relative permeability 80 and a capillary pressure 90 of the selected core plug 50 are calculated in step S170. This calculating is done using mathematical methods such as but not limited to Brooks-Corey, LET and modified Corey models that are available in literature to define the capillary pressure and relative permeability curves.” Spec. [P.0042])
obtaining, from the detection device, a one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug; (“The 1D slice-average CO2 saturation profiles along the length of the core and the 3D CO2 saturation maps are shown in Fig. 8” Ni [Pg.165 Sec.3.3 P.1]. The 1D slice-average is interpreted to include at least one measured 1D imbibition phase saturation profile. The saturation profiles are interpreted to be measured during an imbibition core-flooding experiment because “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks.” Ni [Pg.160 Col.1 P.2])
feeding the measured three-dimensional drainage phase saturation profile, the derived one-dimensional drainage phase saturation profile, the measured one-dimensional imbibition phase saturation profile, the measured oil-water contact angle, the calculated synthetic values for the relative permeability, and a rock heterogeneity state (“three parameters for measuring the degree of mesoscale heterogeneity are computed for each core sample” Ni [Pg.158 Col.2 P.1]) into a porous media fluid flow simulator; (Ni [Pg.167 Fig.6] discloses simulated permeability, porosity, and CO2 saturation maps, implying all discloses parameters have been fed into a porous media fluid flow simulator.)
simulating, using the porous media fluid flow simulator (“The Stanford University General Purpose Research Simulator (GPRS), which has the capability to simulate capillary heterogeneity effects, is used for the simulations.” Ni [Pg.163 Col.1 P.3]), a simulated three- dimensional drainage phase saturation profile and a simulated three-dimensional imbibition phase saturation profile; (“voxel-level permeability values are not directly obtainable from CT image analysis. Rather, the voxel-level permeability field is derived using the extended iterative permeability method [ ] The extended iterative permeability method uses numerical simulations to simulate each core flooding experiment” Ni [Pg.163 Col.1 P.1-2]. Voxel-level permeability values are interpreted as three-dimensional saturation profiles and each core flooding experiment is interpreted to include drainage and imbibition phase saturations because “both drainage and imbibition core flooding experiments were conducted [ ] each experiment we extract multiple parameters, including [ ] the permeability field, and
the CO2 saturation field, as well as variogram ranges and different parameters that represent a rock core’s degree of mesoscale heterogeneity.” Ni [Pg.160 Col.1 P.2])
calculating, using the processor, a simulated one-dimensional drainage phase saturation profile from the simulated three-dimensional drainage phase saturation profile, and a simulated one-dimensional imbibition phase saturation profile from the simulated three-dimensional imbibition phase saturation profile; (“By inputting the core-averaged, slice-averaged [i.e. derived from 3D profiles], and voxel-level CT numbers into Eq. (5), the porosity values for the entire core (mean porosity), for each individual slice along the length of the core (one-dimensional (1D) porosity profile), and for each coarsened voxel inside the core (three-dimensional (3D) porosity map) are calculated respectively [ ] As with the porosity measurements, CO2 saturation values are calculated at the core (mean saturation), slice (1D saturation profile), and voxel (3D saturation map) levels.” Ni [Pg.162 Sec.2.2.2 - 2.2.3]. The calculated saturated values are interpreted to include imbibition and drainage because “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner” Ni [Pg.160 Col.1 P.2]. Also, “sliced average” is interpreted to mean one-dimensional profiles are calculated from three-dimension profiles due to Applicant’s disclosure “The one-dimensional drainage phase [also includes imbibition phase. See Spec. [P.0045]] saturation profile 25d is calculated in Step S140 as a mathematical average of the three-dimensional drainage phase saturation at each circular cross section along the core plug” Spec. [P.0037])
.
Ni fails to specifically disclose A computer-implemented method for training a machine learning algorithm, and training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one-dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, a machine learning algorithm.
However, analogous art Saxena discloses A computer-implemented method for training a machine learning algorithm, and training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one-dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, a machine learning algorithm. (“the trained model [i.e. machine learning algorithm] is produced by providing [i.e. inputting] a training set of images of rock, segmenting the images into a plurality of labeled voxels, the plurality of labeled voxels representing pore spaces and solid material in the rock, and using the labeled voxels to train a model via backpropagation. The training set of images of rock may include, for example, 2D projection images obtained from a pore-scale imaging technology, 3D images reconstructed from 2D projection images, synthetic 2D images, synthetic 3D images, and combinations thereof [ ] Examples of backpropagation-enabled processes include, without limitation, artificial intelligence, machine learning, and deep learning [ ] The backpropagation-enabled process may be supervised, semi-supervised, unsupervised or a combination thereof” Saxena [P.0021-23])
Ni and Saxena are analogous art as they both relate to predicting petrophysical parameters associated with a porous medium. Ni discloses “In this study, we conduct CO2/water core flooding experiments at reservoir conditions on nine core samples with different degrees and types of heterogeneity to find the best petrophysical properties for predicting sandstone CO2 residual trapping ability. We are able to extract petrophysical
properties such as porosity, permeability, degree of mesoscale heterogeneity, and spatial correlation lengths of petrophysical property fields in different directions using a CT scanner.” Ni [Pg.158 Abstract], and Saxena discloses an invention related to estimating fluid saturation in hydrocarbon-bearing rocks using digital rock physics. Its intended application is to provide a faster, more accurate, and cost-effective method for determining fluid saturation from 3D images of rock samples obtained from hydrocarbon formations. The method aims to overcome limitations of conventional laboratory measurements and image resolution constraints by correcting for sub-resolution pore volumes and applying backpropagation-enabled segmentation models to improve fluid saturation estimation for reservoir evaluation and management.
Therefore, it would have been obvious to one of ordinary skill in the art before the
Applicant' s effective filling date of the claimed invention to have integrated machine learning, such as disclosed by Saxena, with the drainage / imbibition profile prediction study, as disclosed by Ni, in order “to provide faster, more, and less expensive analysis of hydrocarbon-containing formation rocks to determine key petrophysical characteristics of the rocks.” Saxena [P.0004].
Regarding claim 7, Ni in view of Saxena disclose the computer-implemented method of claim 6, Ni further discloses, measuring a three-dimensional drainage phase saturation profile using an in-situ core flooding monitoring tool comprising a CT-scanner. (“both drainage and imbibition core flooding experiments were conducted using a medical CT scanner [ ] From each experiment we extract multiple parameters, including [ ] the CO2 saturation field” Ni [Pg.160 Col.1 P.2]. The CO2 saturation field is interpreted to include a three-dimensional drainage phase saturation profile because “From the 3D CO2 saturation maps for both drainage and imbibition shown in Fig. 8, it can be observed that during imbibition the CO2 saturation maps are much more homogeneous than those during drainage” Ni [Pg.165 Col.2 P.3])
Regarding claim 9, Ni in view of Saxena disclose the computer-implemented method of claim 6, Ni further discloses, further comprising: identifying a sister plug for the selected core plug. (“The measurements are performed on small plugs extracted from sections of sandstone rock cut from the cores used for the core flooding experiments.” Ni [Pg.162 Sec.2.2.1]. The small plugs are interpreted as “sister plug” due to Applicant’s disclosure “The sister plug 55 is a sample that is extracted from the subsurface area” Spec. [P.0036])
Claim 10 has been canceled.
Regarding claim 11, Ni in view of Saxena disclose the computer-implemented method of claim 6, Ni further discloses measuring an oil-water contact angle in the porous medium using at least one of analytical or experimental techniques. (“the voxel-level permeability field is derived using the extended iterative permeability method in Kraus’s work [ ] Krause’s permeability method first calculates an initial-guess permeability map using Eq. (7) based on the Leverett-J capillary pressure scaling relationship,
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52
489
media_image2.png
Greyscale
where
k
i
and
i
are the voxel-level permeability and porosity values,
S
w
,
i
is the voxel-level water saturation,
P
-
c
(
S
w
) is the equilibrium capillary pressure within each slice as a function of saturation,
J
(
S
w
,
i
) is the Leverett-J function evaluated at each voxel’s water saturation value, and finally
σ
CO2/
w
a
t
e
r
and
θ
CO2/
w
a
t
e
r
are the CO2/water interfacial tension and contact angle respectively” Ni [Pg.163 Col.1 P.1])
Regarding claim 12, Ni in view of Saxena disclose the computer-implemented method of claim 6, Ni further discloses, wherein determining the rock heterogeneity state comprises using a medical CT scanner. (“both drainage and imbibition core flooding experiments were conducted using a medical CT scanner [ ] From each experiment we extract multiple parameters, including [ ] different parameters that represent a rock core’s degree of mesoscale heterogeneity.” Ni [Pg.160 Col.1 P.2])
Claims 3-5 are rejected under 35 U.S.C. 103 as being unpatentable over Ni in view of Saxena, in further view of Hurley et al. US Patent No. 9134457 B2 (hereinafter referred to as “Hurley”).
Regarding independent claim 3, Ni discloses, a three-dimensional imbibition phase saturation profile for imbibition of a porous rock medium (“the first question that this study will focus on is how the CO2 residual trapping ability differs for different sandstone types and how we can make better predictions about a sandstone rock core’s CO2 residual trapping ability.” Ni [Pg.159 Col.2 P.2]. CO2 residual trapping ability is interpreted to include 3D imbibition phase saturation profile due to the following disclosure: “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner” Ni [Pg.160 Col.1 P. last], “CO2 saturation values are calculated at the core (mean saturation), slice (1D saturation profile), and voxel (3D saturation map) levels” Ni [Pg.162 Col.2 Sec.2.2.3]),
and a detection device comprising a medical-CT-core-flooding apparatus for determining the SCAL data; (“both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks. From each experiment we extract multiple parameters, including the mean and standard deviation of the porosity field, the permeability field, and the CO2 saturation field, as well as variogram ranges and different parameters that represent a rock core’s degree of mesoscale heterogeneity.” Ni [Pg.160 Col.1 P.2], “The drainage relative permeability curves are computed from the first-stage core flooding experimental results” Ni [Pg.162 Sec.2.2.4]. Relative permeability curves are interpreted as SCAL data per Applicant’s disclosure “SCAL-data includes for example, capillary pressure and relative permeability curves of the rock samples.” Spec. [P.0003])
obtaining, from a detection device comprising a medical-CT-core-flooding apparatus, a three-dimensional drainage phase-saturation profile of a core-plug measured during a drainage core-flooding experiment on the core-plug; (“In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks.” Ni [Pg.160 Col.1 P.2]. The core flooding experiments are interpreted to include at least one 3D drainage phase saturation profile because “From the 3D CO2 saturation maps for both drainage and imbibition shown in Fig. 8, it can be observed that during imbibition the CO2 saturation maps are much more homogeneous than those during drainage” [Pg.165 Col.2 P.3])
deriving, using a processor, a derived one-dimensional drainage phase saturation profile from the measured three-dimensional drainage phase saturation profile; (“The 1D slice-average [i.e. derived by a processor] CO2 saturation profiles along the length of the core and the 3D CO2 saturation maps are shown in Fig. 8” Ni [Pg.165 Sec.3.3 P.1]. Reference to “slice-average” is interpreted to mean “derived” due to Applicant’s disclosure “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average of the three-dimensional drainage phase saturation at each circular cross [i.e. slice]” Spec. [P.0037]. Also see Fig.8 [Pg.158] below.)
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391
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calculating, using the processor, a measured oil-water contact angle in the porous medium (“the voxel-level permeability field is derived using the extended iterative permeability method in Kraus’s work [ ] Krause’s permeability method first calculates an initial-guess permeability map using Eq. (7) based on the Leverett-J capillary pressure scaling relationship,
PNG
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52
489
media_image2.png
Greyscale
where
k
i
and
i
are the voxel-level permeability and porosity values,
S
w
,
i
is the voxel-level water saturation,
P
-
c
(
S
w
) is the equilibrium capillary pressure within each slice as a function of saturation,
J
(
S
w
,
i
) is the Leverett-J function evaluated at each voxel’s water saturation value, and finally
σ
CO2/
w
a
t
e
r
and
θ
CO2/
w
a
t
e
r
are the CO2/water interfacial tension and contact angle respectively” Ni [Pg.163 Col.1 P.1]), a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium; (“We measure capillary pressure curves with a mercury porosimeter [ ] The measurements are performed on small plugs extracted from sections of sandstone rock cut from the cores used for the core flooding experiments [ ] The capillary pressure curves are shown in Fig. 2, and the least-square best-fit Brooks-Corey coefficients are shown in Table 2 [ ] All the parameters in Table 2 are then obtained by directly fitting the Brooks-Corey model to the corrected capillary pressure curves.” Ni [Pg.162 Col.1 Sec.2.2.1]. The Brooks-Corey coefficients are interpreted as a plurality of synthetic values for a relative permeability of the porous medium and a capillary pressure of the porous medium due to Applicant’s disclosure, “A plurality of synthetic values for the relative permeability 80 and a capillary pressure 90 of the selected core plug 50 are calculated in step S170. This calculating is done using mathematical methods such as but not limited to Brooks-Corey, LET and modified Corey models that are available in literature to define the capillary pressure and relative permeability curves.” Spec. [P.0042])
obtaining, from the detection device, a one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug; (“The 1D slice-average CO2 saturation profiles along the length of the core and the 3D CO2 saturation maps are shown in Fig. 8” Ni [Pg.165 Sec.3.3 P.1]. The 1D slice-average is interpreted to include at least one measured 1D imbibition phase saturation profile. The saturation profiles are interpreted to be measured during an imbibition core-flooding experiment because “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks.” Ni [Pg.160 Col.1 P.2]))
feeding the measured three-dimensional drainage phase saturation profile, the derived one-dimensional drainage phase saturation profile, the measured one- dimensional imbibition phase saturation profile, the measured oil-water contact angle, the calculated synthetic values for the relative permeability, the calculated synthetic values for the capillary pressure, and a rock heterogeneity state (“three parameters for measuring the degree of mesoscale heterogeneity are computed for each core sample” Ni [Pg.158 Col.2 P.1]) into a porous media fluid flow simulator; (Ni [Pg.167 Fig.6] discloses simulated permeability, porosity, and CO2 saturation maps, implying all discloses parameters have been fed into a porous media fluid flow simulator.)
simulating, using the porous media fluid flow simulator (“The Stanford University General Purpose Research Simulator (GPRS), which has the capability to simulate capillary heterogeneity effects, is used for the simulations.” Ni [Pg.163 Col.1 P.3]), a simulated three- dimensional drainage phase saturation profile and a simulated three-dimensional imbibition phase saturation profile; (“voxel-level permeability values are not directly obtainable from CT image analysis. Rather, the voxel-level permeability field is derived using the extended iterative permeability method [ ] The extended iterative permeability method uses numerical simulations to simulate each core flooding experiment” Ni [Pg.163 Col.1 P.1-2]. Voxel-level permeability values are interpreted as three-dimensional saturation profiles and each core flooding experiment is interpreted to include drainage and imbibition phase saturations because “both drainage and imbibition core flooding experiments were conducted [ ] each experiment we extract multiple parameters, including [ ] the permeability field, and
the CO2 saturation field, as well as variogram ranges and different parameters that represent a rock core’s degree of mesoscale heterogeneity.” Ni [Pg.160 Col.1 P.2])
calculating, using the processor, a simulated one-dimensional drainage phase saturation profile from the simulated three-dimensional drainage phase saturation profile, and a simulated one-dimensional imbibition phase saturation profile from the simulated three-dimensional imbibition phase saturation profile; (“By inputting the core-averaged, slice-averaged [i.e. derived from 3D profiles], and voxel-level CT numbers into Eq. (5), the porosity values for the entire core (mean porosity), for each individual slice along the length of the core (one-dimensional (1D) porosity profile), and for each coarsened voxel inside the core (three-dimensional (3D) porosity map) are calculated respectively... As with the porosity measurements, CO2 saturation values are calculated at the core (mean saturation), slice (1D saturation profile), and voxel (3D saturation map) levels.” Ni [Pg.162 Sec.2.2.2 - 2.2.3]. The calculated saturated values are interpreted to include imbibition and drainage because “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner” Ni [Pg.160 Col.1 P.2]. Also, “sliced average” is interpreted to mean one-dimensional profiles are calculated from three-dimension profiles due to Applicant’s disclosure “The one-dimensional drainage phase [also includes imbibition phase. See Spec. [P.0045]] saturation profile 25d is calculated in Step S140 as a mathematical average of the three-dimensional drainage phase saturation at each circular cross section along the core plug” Spec. [P.0037]) and
obtaining, from the detection device, at least one three-dimensional drainage phase-saturation profile of the core-plug measured during a drainage core-flooding experiment on the core-plug (“In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks.” Ni [Pg.160 Col.1 P.2]. The core flooding experiments are interpreted to include at least one 3D drainage phase saturation profile because “From the 3D CO2 saturation maps for both drainage and imbibition shown in Fig. 8, it can be observed that during imbibition the CO2 saturation maps are much more homogeneous than those during drainage” Ni [Pg.165 Col.2 P.3]) and
;
deriving, by a processor, a one-dimensional drainage phase saturation profile from the at least one measured three-dimensional drainage phase saturation profile (“The 1D slice-average [i.e. derived by a processor] CO2 saturation profiles along the length of the core and the 3D CO2 saturation maps are shown in Fig. 8” Ni [Pg.165 Sec.3.3 P.1]. Reference to “slice-average” is interpreted to mean “derived” due to Applicant’s disclosure “The one-dimensional drainage phase saturation profile 25d is calculated in Step S140 as a mathematical average of the three-dimensional drainage phase saturation at each circular cross [i.e. slice]” Spec. [P.0037]. Also see Fig.8 [Pg.158] below.)
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Greyscale
;
obtaining, from the detection device, at least one one-dimensional imbibition phase saturation profile measured during an imbibition core-flooding experiment on the core-plug (“The 1D slice-average CO2 saturation profiles along the length of the core and the 3D CO2 saturation maps are shown in Fig. 8” Ni [Pg.165 Sec.3.3 P.1]. The 1D slice-average is interpreted to include at least one measured 1D imbibition phase saturation profile. The saturation profiles are interpreted to be measured during an imbibition core-flooding experiment because “In this study, both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples covering five different types of sandstone rocks.” Ni [Pg.160 Col.1 P.2]) and
;
and approximating, , the predicted three-dimensional imbibition phase saturation profile based on the input (“both drainage and imbibition core flooding experiments were conducted using a medical CT scanner on nine sandstone core samples [ ] From
each experiment we extract multiple parameters, including the mean and standard deviation of the porosity field, the permeability field, and the CO2 saturation field, as well as variogram ranges [i.e. approximates] and different parameters that represent a rock core’s degree of mesoscale heterogeneity. These parameters were then correlated with both the Land and the linear trapping coefficients in order to infer which parameters best predict a sandstone core’s residual trapping ability” Ni [Pg.160 Col.1 P.2]. Residual trapping ability is interpreted to include 3D imbibition phase saturation profile because “CO2 saturation values are calculated at the core (mean saturation), slice (1D saturation profile), and voxel (3D saturation map) levels” Ni [Pg.162 Col.2 Sec.2.2.3])
Ni fails to specifically disclose a measurement system comprising: a processor for executing at least one of a special core analysis laboratory (SCAL) porous media fluid flow simulator and a machine learning algorithm, a memory, connected to the processor, for storing items of SCAL data of a target core plug on at least one of an oil-water contact angle, a relative permeability, and a capillary pressure, inputting data (i.e. phase saturation profiles) into a machine learning algorithm and approximating, using the machine learning algorithm executed on a processor, and training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one-dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, the machine learning algorithm.
However, Saxena discloses so that the machine learning algorithm performs a method for predicting the three-dimensional imbibition phase saturation profile of the porous rock medium (The Examiner interprets this limitation to mean using a trained model (i.e. trained machine learning algorithm) to predict porous rock saturation profiles. Saxena discloses “A backpropagation-enabled trained model can be used [ ] to estimate the fluid saturation” [Abstract]. Ni, as shown above, discloses predicting 3D imbibition phase saturation.), inputting [data (i.e. phase saturation profiles)] into a machine learning algorithm, training, using the simulated one-dimensional drainage phase saturation profile, the simulated three-dimensional drainage phase saturation profile, the simulated one-dimensional imbibition phase saturation profile, and the simulated three-dimensional imbibition phase saturation profile, the machine learning algorithm (“the trained model [i.e. machine learning algorithm] is produced by providing [i.e. inputting] a training set of images of rock, segmenting the images into a plurality of labeled voxels, the plurality of labeled voxels representing pore spaces and solid material in the rock, and using the labeled voxels to train a model via backpropagation. The training set of images of rock may include, for example, 2D projection images obtained from a pore-scale imaging technology, 3D images reconstructed from 2D projection images, synthetic 2D images, synthetic 3D images, and combinations thereof [ ] Examples of backpropagation-enabled processes include, without limitation, artificial intelligence, machine learning, and deep learning [ ] The backpropagation-enabled process may be supervised, semi-supervised, unsupervised or a combination thereof” Saxena [P.0021-23]) and
approximating, using the machine learning algorithm executing on a processor (“a backpropagation-enabled method for estimating [i.e. approximating] the fluid saturation of rock from a 3D image of rock. A backpropagation-enabled trained model [i.e. machine learning algorithm] is applied to a 3D image to segment the 3D image of rock” Saxena [P.0020])
Ni and Saxena are analogous art as they both relate to predicting petrophysical parameters associated with a porous medium. Ni discloses a study that conducted “CO2/water core flooding experiments at reservoir conditions on nine core samples with different degrees and types of heterogeneity to find the best petrophysical properties for predicting sandstone CO2 residual trapping ability. We are able to extract petrophysical
properties such as porosity, permeability, degree of mesoscale heterogeneity, and spatial correlation lengths of petrophysical property fields in different directions using a CT scanner.” Ni [Pg.158 Abstract], which is analogous to the claimed invention, although doesn’t utilize a machine learning algorithm. Saxena, on the other hand, discloses an invention related to estimating fluid saturation in hydrocarbon-bearing rocks using digital rock physics. Its intended application is to provide a faster, more accurate, and cost-effective method for determining fluid saturation from 3D images of rock samples obtained from hydrocarbon formations. The method aims to overcome limitations of conventional laboratory measurements and image resolution constraints by correcting for sub-resolution pore volumes and applying backpropagation-enabled segmentation models (i.e. machine learning algorithms) to improve fluid saturation estimation for reservoir evaluation and management.
Therefore, it would have been obvious to one of ordinary skill in the art before the
Applicant' s effective filling date of the claimed invention to have integrated machine learning, such as disclosed by Saxena, with the drainage / imbibition profile prediction study, as disclosed by Ni, in order “to provide faster, more, and less expensive analysis of hydrocarbon-containing formation rocks to determine key petrophysical characteristics of the rocks.” Saxena [P.0004].
Ni and Saxena fail to specifically disclose a measurement system comprising: a processor for executing at least one of a special core analysis laboratory (SCAL) porous media fluid flow simulator and a machine learning algorithm, a memory, connected to the processor, for storing items of SCAL data of a target core plug on at least one of an oil-water contact angle, a relative permeability, and a capillary pressure.
However, analogous art Hunley discloses a measurement system for predicting (“Numerical SCAL predicted from REV's [representative element volumes] of these models can be used to populate interwell-scale digital rock models.” Hurley [Col.10 Ln.7]), comprising: a processor for executing at least one of a special core analysis laboratory (SCAL) porous media fluid flow simulator (“Effective properties computed from flow simulations at the interwell scale are used to populate full-field scale models” Hurley [Col.7 Ln.15]) and a machine learning algorithm (“neural networks can be used to distribute facies along the length” Hurley [Col.14 Ln.49]),
a memory, connected to the processor (“Processing center 150 also includes a storage system 142” Hurley [Col.6 Ln.25]), for storing items of SCAL data of a target core plug (“processing center 150 also receives many other types of data used in multiscale digital rock modeling, such as core analysis data and surface seismic data” Hurley [Col.6 Ln.30-33]) on at least one of an oil-water contact angle, a relative permeability, and a capillary pressure (“For each petrophysical facies, porosity, permeability, capillary pressure, and relative permeability curves are provided by pore-scale numerical SCAL” Hurley [Col.14 Ln.2-4]).
Hurley is analogous art as it relates to digitally characterizing and predicting petrophysical parameters associated with a porous medium. Hurley discloses a patent which “relates to methods for characterizing three-dimensional (3D) samples of reservoir rock. More particularly, this patent specification relates to upscaling digital rock modeling data.” Hurley [Col.1 Ln.35-38]. Therefore, it would have been obvious to one of ordinary skill in the art before the Applicant's effective filling date of the claimed invention to have integrated a measurement system (e.g. processor/memory), such as disclosed by Hurley, with the drainage / imbibition profile prediction study, as disclosed by Ni, in order “to improve flow simulations” Hurley [Abstract].
Regarding claim 4, Ni in view of Saxena in further view of Hurley disclose the measurement system of claim 3, although Ni fails to specifically disclose wherein: the SCAL-data is used in reservoir simulation models for a prediction of oil and gas field behavior.
However, Hurley discloses, wherein: the SCAL-data is used in reservoir simulation models for a prediction of oil and gas field behavior. (“Numerical SCAL predicted from REV's of these models can be used to populate interwell-scale digital rock models” Hurley [Col.10 Ln.7-9], “A major goal of full-field scale digital rock modeling is to build static models of the reservoir” Hurley [Col.10 Ln.32])
It would have been obvious to one of ordinary skill in the art before the Applicant's effective filling date of the claimed invention to have integrated the usage of SCAL-data in reservoir simulation models, such as disclosed by Hurley, with Ni’s drainage / imbibition profile prediction study, in order to build “a digital representation of a reservoir that incorporates all characteristics pertaining to its ability to store and produce hydrocarbons. ” Hurley [Col.1 Ln.42].
Regarding claim 5, Ni in view of Saxena in further view of Hurley disclose the measurement system of claim 3, Ni further discloses, wherein: the detection device comprises at least one of a linear X-Ray scanner or a Gamma Ray scanner (“For all of the sandstone rock samples used in this study, capillary pressure, porosity, permeability, CO2 saturation, and CO2 residual trapping measurements are extracted from core flooding experiments conducted using a medical CT scanner (General Electric Hi-Speed x-ray CT).” Ni [Pg.160 Col.2 Sec.2.2])
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Ni, in view of Saxena, in further view of Hasem et al. US Patent No. 6941804 B2 (hereinafter referred to as “Hasem”).
Regarding claim 8, Ni in view of Saxena disclose the computer-implemented method of claim 6, but fail to specifically disclose, measuring fluid properties of a crude oil.
However, analogous art Hasem discloses measuring fluid properties of a crude oil. (“Further, at each location a pressure-build no test was conducted, a sample of the hydrocarbon reservoir fluid was taken, and the PVT properties of the sample were measured in a laboratory under reservoir conditions.” Hasem [Col.2 Ln.55-60]. Hydrocarbon reservoir fluid is interpreted as crude oil.).
Hasem is analogous art as it relates to hydrocarbon properties, specifically in determining in situ PVT properties of hydrocarbon (i.e. crude oil). Hasem discloses “The present invention relates to determining the PVT properties of a hydrocarbon reservoir fluid, where PVT is an acronym used to refer to pressure, volume and temperature. PVT properties are gas-oil ratio, API gravity, viscosity, saturation pressure, formation volume factor, molecular weight, density and oil compressibility” Hasem [Col.1 Ln.9-14].
Therefore, it would have been obvious to one of ordinary skill in the art before the
Applicant' s effective filling date of the claimed invention to have combined measuring in situ fluid properties (i.e. crude oil), as Hasem discloses, with the teachings of Ni-Saxena since “It is of great importance to know the PVT properties of the reservoir fluid as soon as possible, preferably directly after a well has been drilled. Knowing such information allows for the adjustment of the design of the production and surface equipment to take into account the actual PVT properties.” Hasem [Col.1 Ln.26].
Conclusion
The prior art made of record, listed on form PTO-892, and not relied upon is
considered pertinent to applicant's disclosure:
Tembely, M., and A. AlSumaiti. "Deep learning for a fast and accurate prediction of complex carbonate rock permeability from 3D micro-CT images’ Abu Dhabi International Petroleum Exhibition & Conference." (2019). “Within a supervised learning framework, algorithms based on linear regression, gradient boosting, support vector regression, and convolutional neural networks are applied to predict porous rock petrophysical properties from 3D micro-CT images” [Abstract]
De Prisco et al. (Method For Simulating Fractional Multi-phase/multi-component Flow Through Porous Media – US Patent No US 9183326 B2). “A method for computing or estimating fractional, multi-phase/multi-component flow through a porous medium employing a 3D digital representation of a porous medium and a computational fluid dynamics method to calculate flow rates, pressures, saturations, internal velocity vectors and other flow parameters is described” [Abstract].
Zhao, Bochao, et al. "A hybrid approach for the prediction of relative permeability using machine learning of experimental and numerical proxy SCAL data." SPE Journal 25.05 (2020): 2749-2764. “we identify Euler number [ ] and saturation as first-order predictors of relative permeability and develop a reliable correlation between them using machine learning of experimental special core analysis (SCAL) data and pore network simulation results.” [Abstract]
Janssens, Nick, Marijke Huysmans, and Rudy Swennen. "Computed tomography 3D super-resolution with generative adversarial neural networks: Implications on unsaturated and two-phase fluid flow." Materials 13.6 (2020): 1397.
Alpak, F. O., S. Berg, and I. Zacharoudiou. "Prediction of fluid topology and relative permeability in imbibition in sandstone rock by direct numerical simulation." Advances in Water Resources 122 (2018): 49-59.
Applicant’s amendment necessitated the new ground(s) of rejection presented in this Office Action. Accordingly, THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ANTHONY CHAVEZ/ Examiner, Art Unit 2187
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186
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