Prosecution Insights
Last updated: October 02, 2026
Application No. 17/577,463

OPTIMIZING HYDROCARBON RECOVERY THROUGH INTEGRATED UTILIZATION OF GEOMECHANICS AND INJECTION/PRODUCTION USING MACHINE LEARNING

Final Rejection §101§103§112
Filed
Jan 18, 2022
Examiner
MORRIS, JOSEPH PATRICK
Art Unit
2188
Tech Center
2100 — Computer Architecture & Software
Assignee
Saudi Arabian Oil Company
OA Round
4 (Final)
48%
Grant Probability
Moderate
5-6
OA Rounds
0m
Est. Remaining
90%
With Interview

Examiner Intelligence

Grants 48% of resolved cases
48%
Career Allowance Rate
13 granted / 27 resolved
-6.9% vs TC avg
Strong +42% interview lift
Without
With
+41.5%
Interview Lift
resolved cases with interview
Typical timeline
4y 2m
Avg Prosecution
24 currently pending
Career history
62
Total Applications
across all art units

Statute-Specific Performance

§101
29.3%
-10.7% vs TC avg
§103
38.0%
-2.0% vs TC avg
§102
13.2%
-26.8% vs TC avg
§112
17.7%
-22.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 27 resolved cases

Office Action

§101 §103 §112
DETAILED ACTION Claims 1-20 are presented for examination. This Office Action is in response to submission of documents on December May 12, 2026. Rejection under 35 U.S.C. 112(b) as being indefinite for failing to point out and distinctly claim what the inventor regards as the invention is withdrawn and a new rejection is asserted. Rejection of claims 1-20 under 35 U.S.C. 101 for being directed to unpatentable subject matter is maintained. Rejection of claims claim 1, 8, and 15 under 35 U.S.C. 103 as being obvious over Batmaz, in view of Ouenes, and Liu is maintained. Rejection of claims 2, 3, 9, 10, 16, and 17 under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Garcia-Teijeiro is maintained. Rejection of claims 4, 11, and 18 under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Shen is maintained. Rejection of claim 5, 12, and 19 under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Boone is maintained. Rejection of claim 6, 13, and 20 under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Shen and Boone is maintained. Rejection of claims 7 and 14 under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Herrera is maintained. Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Arguments Regarding rejection of the claims under 35 U.S.C. 112(b): The limitations that were the subject of the rejection are now clearer as to which of the recited features is compared with other features of the limitation. Thus, as now recited, Examiner interprets the claim to mean that the spatio-temporal relationships between injection and production of the well are analyzed. Further, as another analysis, the fracture growth, a first model of a single well, and a second model of one or more wells are used to analyze geomechanical changes, stress distribution, reservoir geomechanical characteristics, and flow characteristics. These analyses (i.e., the “spatio-temporal relationships,” “geomechanical changes,” “stress distribution,” “reservoir geomechanical characteristics,” and “flow characteristics”) are used in determining “fracture design” and “orientation for optimum recovery of hydrocarbons.” Although the limitation is now clearer and appears to have only one interpretation, if Examiner’s interpretation is not in accordance with the meaning intended by the Applicant, further amendments and/or explanation is encouraged by the Applicant to make the intended meaning clearer. Accordingly, previous rejection of the claims under 35 U.S.C. 112(b) is withdrawn. However, in light of the amendments, a new rejection under 35 U.S.C. 112(b) is asserted (see below). Regarding the rejection of the claims under 35 U.S.C. 101: Applicant asserts that “Claims 1, 8, and 15 are not abstract because they recite specific and unconventional steps for achieving an improved technological result” because “the claimed invention is specifically integrated into a practical application because it recites specific and unconventional steps for achieving an improved technological result.” Response at pg. 10. Regarding this initial assertion, Examiner does not agree that the statement is accurate. Examiner has indicated what portions of the claim recite judicial exceptions. Conversely, Applicant’s argument are instead directed to improving a technology, which is an argument as to why additional elements (i.e., those elements that are not abstract ideas) improve a technology that is performed via abstract ideas. See e.g., MPEP 2106.04, Section II(2): Because a judicial exception is not eligible subject matter, Bilski, 561 U.S. at 601, 95 USPQ2d at 1005-06 (quoting Chakrabarty, 447 U.S. at 309, 206 USPQ at 197 (1980)), if there are no additional claim elements besides the judicial exception, or if the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) (“Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract”); Genetic Techs. Ltd. V. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility “cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself.”). For a claim reciting a judicial exception to be eligible, the additional elements (if any) in the claim must “transform the nature of the claim” into a patent-eligible application of the judicial exception, Alice Corp., 573 U.S. at 217, 110 USPQ2d at 1981, either at Prong Two or in Step 2B. If there are no additional elements in the claim, then it cannot be eligible. The arguments do not address why any of the identified abstract ideas are incorrectly identified. Instead, the arguments are why identified abstract ideas recite a technological improvement, an analysis at Prong 1, Step 2A and directed to the additional elements. In the case of the present claims, this is limited to the “receiving” step, recited computer components, and the “controlling step.” None of these additional elements that are not the recited abstract ideas (i.e., the remainder of the claim) “use the judicial technological improvement in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception,” Response at pg. 12, citing 2019 PEG, p. 19-20, and as further discussed in the rejection, below. With regards to the “controlling” step, Examiner understands the intention of the limitation (the speed and direction of the drilling equipment is dictated by the “optimum stress distribution”). However, the feature is still an idea of a solution, as currently presented. The limitation is missing a meaningful recitation of how the “optimum stress distribution” informs the placement of new wells and subsequent operation. For example, the limitations does not indicate how the adjustments to the drilling equipment is facilitated by “optimum stress distribution,” such as why a particular location of drilling equipment or drilling at a particular speed and direction facilitates an improved well. As a suggestion, in order to better claim the technological improvement in an additional element that recites such an improved well, Examiner suggests amendments that cause the drilling equipment to dig a well in a certain way, performing injection according to the optimized injection, and cause the well to exhibit optimum stress distribution (e.g., cause expanded fractures at predicted locations and of predicted sizes) to result in optimized stress distribution, resulting in hydrocarbon recovery at an optimal level.1 Thus, the claims, as currently presented, include additional elements that do not incorporate the abstract ideas into a practical application and further do not amount to significantly more because the “controlling…” step is an idea of a solution. See MPEP 2106.05(f)(1). Accordingly, the rejection under 35 U.S.C. 101 is maintained. Regarding rejection of the claims under 35 U.S.C. 103: Applicant asserts that the cited prior art, particularly Ouenes, does not teach or suggest at least “determining fracture design and orientation for optimum recovery of hydrocarbons by analyzing spatio-temporal relationships between the injection of the fluids to the reservoir and the production of the fluids from the reservoir and, by analyzing geomechanical changes, the stress distribution, reservoir geomechanical characteristics and flow characteristics using the fracture growth, a first model of a single well and a second model of a plurality of wells as recited in amended claims 1, 8, and 15.” Response at pp. 13-14. As further indicated in the rejection, below, each of the recited features is included in either “determining fracture design” or is an “analysis using spatio-temporal relationships.” The phrase “for optimum recovery of hydrocarbons” does not effectively limit the claim because the remainder of the claim (e.g., “by analyzing spatio-temporal relationships…”) does not effectively claim how the analysis is related to optimally recovering hydrocarbons besides performing some analysis. Thus, by broadest reasonable interpretation, any type of analysis that utilizes “spatio-temporal relationships, ,” “geomechanical changes,” “stress distribution,” “reservoir geomechanical characteristics,” and “flow characteristics” to determine an optimal design for a fracture such that hydrocarbon recovery is increased teaches the limitation. Further, “using the fracture growth,” as the term is defined in the claims (“a predicted propagation behavior of a fracture”), to determine an improved orientation and configuration of fractures is taught by “fracture growth model 179,” as further indicated by the rejection below. Further, Applicant asserts that “Batmaz also fails to teach or suggest ‘determining, using the optimum stress distribution, location of well placement and fracture design comprising orientation and size of fractures to maximize recovery of hydrocarbons,’ as recited in amended claims 1, 8, and 15. Response at pg. 14. Examiner disagrees. First, the “fracture design” is previously determined “by analyzing spatio-temporal relationships between the injection of the fluids to the reservoir and the production of the fluids from the reservoir and, by analyzing geomechanical changes, the stress distribution, reservoir geomechanical characteristics and flow characteristics using the fracture growth, using a first model of a single well and a second model of a plurality of wells.” This analysis, which analyzes those factors that contribute to a “stress distribution” by affecting how the forces change the stress on fractures. Thus, the analysis can include determining a set of factors that create favorable conditions for oil extraction (i.e., an optimum stress distribution). Accordingly, fracture design and well locations that optimize oil production is disclosed by Ouenes: FIGS. 5a-5b are flowcharts of an exemplary method of hydraulic fracture design and completion optimization according to the present invention. Ouenes at [0050]. Further, Liu discloses determining well placement using an analogous process: Moreover, the methods and systems are used to estimate potential production as a function of time at geographical locations where production wells are not drilled yet. Therefore, optimal geographical locations for drilling production wells are determined. Liu at [0022]. Thus, for both the limitations of "determining, using the optimized injection or production and placement of wells, an optimum stress distribution for placement of new wells" and "determining, using the optimum stress distribution, location of well placement and fracture design comprising orientation and size of fractures to maximize recovery of hydrocarbons" are taught by at least Ouenes and Liu, Accordingly, rejection of the claims under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes and Liu is maintained. Claim Rejections – 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. In the independent claims, a “fracture design and orientation” is determined “by analyzing spatio-temporal relationships between the injection of the fluids to the reservoir and the production of the fluids from the reservoir and, by analyzing geomechanical changes, the stress distribution, reservoir geomechanical characteristics and flow characteristics using the fracture growth.” However, the claims further recite “determining, using the optimum stress distribution, location of well placement and fracture design comprising orientation and size of fractures to maximize recovery of hydrocarbons.” Thus , it is unclear what is analyzed and/or used in the determination of “fracture design and orientation (which is additionally claimed as part of the ‘fracture design’). Proper correction and/or clarification is required. In any reply, please provide citations to the Specification to illustrate support for amendments and/or clarifications. For purposes of examination, the term “fracture design,” as used in the second instance, is interpreted to mean an optimum fracture design that, upon stress distribution analysis and predicted propagation of fractures, is selected such that it optimizes the production of hydrocarbons. Based on FIG. 31 of the Specification, this is embodied in the definition at Step 3108 and the use of fracture design at Step 3112. Thus, as interpreted, both instances of “fracture design and orientation” are examined as if the second “determining” is not present. Claim Rejections – 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exceptions without significantly more. The claims recite mathematical calculations and mental processes. These judicial exceptions are not integrated into a practical application because the additional elements that are recited in the claims are extra-solution activities that do not integrate the judicial exceptions into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because courts have found that the steps of data gathering and recitations of generic computer component s and ideas of a solution are not significantly more than a judicial exception. Claim 1 Step 1: The claim is directed to a process, falling under one of the four statutory categories of invention. Step 2A, Prong 1: The claim 1 limitations include (bolded for abstract idea identification): Claim 1 Mapping Under Step 2A Prong 1 A computer-implemented method, comprising: receiving stress change correlations over space and time for injection and production of fluids to or from a reservoir; determining, using reservoir geomechanical modeling tools and using the stress change correlations, a stress distribution of the reservoir; determining, using the stress distribution of the reservoir and field-wide geomechanical properties for optimizing treatment, a fracture growth defining, using a fracturing model, a predicted propagation behavior of a fracture in the reservoir; determining fracture design and orientation for optimum recovery of hydrocarbons by analyzing spatio-temporal relationships between the injection of the fluids to the reservoir and the production of the fluids from the reservoir and, by analyzing geomechanical changes, the stress distribution, reservoir geomechanical characteristics and flow characteristics using the fracture growth, a first model of a single well and a second model of a plurality of wells; determining changes in the stress distribution in the reservoir through injection or production of fluids relative to field configurations comprising the single well and the plurality of wells; determining, using the changes in the stress distribution and the fracture design and orientation, an optimized injection or production and placement of wells, comprising using machine learning to adjust injection and production of fluids to or from the reservoir; determining, using the optimum stress distribution, location of well placement fracture design comprising orientation and size of fractures to maximize recovery of hydrocarbons; and controlling drilling equipment for drilling of a new well by using location of well placement and the fracture design, by adjusting drilling parameters comprising a speed and a direction of the drilling equipment. Abstract Idea: Mathematical Calculations Using modeling tools includes performing one or more mathematical calculations or applying mathematical concepts to simulate the behavior of a system. See MPEP § 2106.04(a)(2), Subsection I. Abstract Idea: Mental Process Using a model to determine behavior is a mental process that can be performed by a human and requires observation, evaluation, judgment, and opinion. See MPEP § 2106.04(a)(2), Subsection III. Abstract Idea: Mental Process Determining a design for a well is a mental process that includes observation, evaluation, and judgment, which can be performed by a human with knowledge in the field with the aid of pencil and paper. See e.g., MPEP 2106.04(a)(2), Subsection III. Abstract Idea: Mental Process Determining a change can be performed by a human using observation. For example, a human can review stress distributions and identify when changes to the values exceed a threshold. See e.g., MPEP 2106.04(a)(2), Subsection III. Abstract Idea: Mathematical Calculations Machine learning techniques include performing one or more mathematical equations and/or functions to generate results. For example, a machine learning model can be constructed and provided with inputs related to changes in stress distributions, and the model can provide injection and production values that can be applied to a well. See MPEP § 2106.04(a)(2), Subsection I. Abstract Idea: Mental Process Determining an optimum stress distribution can include adjusting injection and/or production of a well to maintain optimal conditions for a new well in order to maximize recovery. See e.g., MPEP 2106.04(a)(2), Subsection III. Step 2A, Prong 2: The claim 1 limitations recite (bolded for additional element identification): Claim 1 Mapping Under Step 2A Prong 2 A computer-implemented method, comprising: receiving stress change correlations over space and time for injection and production of fluids to or from a reservoir; determining, using reservoir geomechanical modeling tools and using the stress change correlations, a stress distribution of the reservoir; determining, using the stress distribution of the reservoir and field-wide geomechanical properties for optimizing treatment, a fracture growth defining, using a fracturing model, a predicted propagation behavior of a fracture in the reservoir; determining fracture design and orientation for optimum recovery of hydrocarbons by analyzing spatio-temporal relationships between the injection of the fluids to the reservoir and the production of the fluids from the reservoir and, by analyzing geomechanical changes, the stress distribution, reservoir geomechanical characteristics and flow characteristics using the fracture growth, a first model of a single well and a second model of a plurality of wells; determining changes in the stress distribution in the reservoir through injection or production of fluids relative to field configurations comprising the single well and the plurality of wells; determining, using the changes in the stress distribution and the fracture design and orientation, an optimized injection or production and placement of wells, comprising using machine learning to adjust injection and production of fluids to or from the reservoir; determining, using the optimum stress distribution, location of well placement fracture design comprising orientation and size of fractures to maximize recovery of hydrocarbons; and controlling drilling equipment for drilling of a new well by using location of well placement and the fracture design, by adjusting drilling parameters comprising a speed and a direction of the drilling equipment. Reciting a generic computer to perform one or more judicial exceptions is mere instructions to apply an exception. See MPEP 2106.05(f), Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 112 USPQ2d 1750 (Fed. Cir. 2014); Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016). Receiving data is an extra-solution activity of data gathering and data transmission, which does not integrate the judicial exception into a practical application. See MPEP 2106.05(g), OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). The limitations recite idea of solutions without reciting details as to how a solution to the problem is accomplished. See, e.g., MPEP 2106.05(f)(1), Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015). Step 2B: Regarding Step 2B, the inquiry is whether any of the additional elements (i.e., the elements that are not the judicial exception) amount to significantly more than the recited judicial exception. The extra-solution activity of receiving stress change correlations is well-understood, routine, and conventional and therefore is not significantly more than the recited judicial exceptions. See, e.g., Batmaz, et al. (U.S. Patent No. 10,526,890), disclosing collecting reservoir formation data over time: “As shown, a data audit 901 may be performed to collect data available of the formation being analyzed. For example, data may be collected using a sonic measurement tool or an image logging tool, and data may be collected from, for example, one or more current boreholes drilled in the formation, seismic testing, or one or more offset wells.” Batmaz at col. 11, lines 31-37. Furter, recitation of ideas of a solution have been determined by courts to be insignificantly more than recited judicial exceptions. See, e.g., MPEP 2106.05(f)(1), Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015). Finally, courts have found that claiming generic computer components is insignificantly more than the recited judicial exception. See MPEP 2106.05(f), Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 112 USPQ2d 1750 (Fed. Cir. 2014); Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016). Accordingly, claim 1 is rejected for being directed to unpatentable subject matter. Claim 2 Claim 2 recites generating, for display in a user interface, a plot showing a single well pressure distribution for a single well model. The limitation recites the judicial exception of a mental process because creating a plot can be performed by a human using a pencil and paper. For example, a human can generate a plot by drawing (or using a computer as an aid) plot points that show particular aspects of a well or reservoir formation on a set of Cartesian axes. Accordingly, claim 2 is rejected for being directed to unpatentable subject matter. Claim 3 Claim 3 recites generating, for display in a user interface, a diagram showing a grid investigated for shear strain and shear stress. The limitation recites the judicial exception of a mental process because creating a diagram can be performed by a human using a pencil and paper. For example, a human can generate a diagram by drawing (or using a computer as an aid) a visual representation of data points that indicate particular aspects of a well or reservoir formation. Accordingly, claim 3 is rejected for being directed to unpatentable subject matter. Claim 4 Claim 4 recites comprising generating, for display in a user interface, a three-dimensional (3D) plot showing different phenomena of shear strain between a toe and a heel of a well within an IJ direction. The limitation recites the judicial exception of a mental process because creating a plot can be performed by a human using a pencil and paper. For example, a human can generate a plot by drawing (or using a computer as an aid) plot points that show particular aspects of a well or reservoir formation on a set of Cartesian axes. Accordingly, claim 4 is rejected for being directed to unpatentable subject matter. Claim 5 Claim 5 recites generating, for display in a user interface, a plot showing a gas saturation distribution of a parent well and a child well. The limitation recites the judicial exception of a mental process because creating a plot can be performed by a human using a pencil and paper. For example, a human can generate a plot by drawing (or using a computer as an aid) plot points that show particular aspects of a well or reservoir formation on a set of Cartesian axes. Accordingly, claim 5 is rejected for being directed to unpatentable subject matter. Claim 6 Claim 6 recites generating, for display in a user interface, a 3D plot of shear strain in a parent well and a child well. The limitation recites the judicial exception of a mental process because creating a plot can be performed by a human using a pencil and paper. For example, a human can generate a plot by drawing (or using a computer as an aid) plot points that show particular aspects of a well or reservoir formation on a set of Cartesian axes. Accordingly, claim 6 is rejected for being directed to unpatentable subject matter. Claim 7 Claim 7 recites generating, for display in a user interface, a 3D plot of shear stress in a parent well and a child well. The limitation recites the judicial exception of a mental process because creating a plot can be performed by a human using a pencil and paper. For example, a human can generate a plot by drawing (or using a computer as an aid) plot points that show particular aspects of a well or reservoir formation on a set of Cartesian axes. Accordingly, claim 7 is rejected for being directed to unpatentable subject matter. Claim 8 Claim 8 recites a non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising a method that is substantially the same as the method of claim 1. The limitation of a non-transitory, computer-readable medium is a recitation of generic computer components, which courts have found to be insignificantly more than the recited exception and further do not integrate the exception into a practical application. Accordingly, for at least the same reasons as claim 1, claim 8 is rejected under 35 U.S.C. 101 for being directed to unpatentable subject matter. Claims 9-14 Claims 9-14 recite substantially the same imitations as claims 2-7. Accordingly, for at least the same reasons as claims 2-7, claims 9-14 are rejected under 35 U.S.C. 101 for being directed to unpatentable subject matter. Claim 15 Claim 15 recites a computer-implemented system, comprising: one or more processors; and a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors, the programming instructions instructing the one or more processors to perform operations comprising a method that is substantially the same as the method of claim 1. The limitation of one or more processors and a non-transitory, computer-readable medium are recitations of generic computer components, which courts have found to be insignificantly more than the recited exception and further do not integrate the exception into a practical application. Accordingly, for at least the same reasons as claim 1, claim 15 is rejected under 35 U.S.C. 101 for being directed to unpatentable subject matter. Claims 16-20 Claims 16-20 recite substantially the same imitations as claims 2-6. Accordingly, for at least the same reasons as claims 2-6, claims 16-20 are rejected under 35 U.S.C. 101 for being directed to unpatentable subject matter. Claim Rejections – 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. Claims 1, 8, and 15 are rejected under 35 U.S.C. 103 as being obvious over Batmaz, et al., (U.S. Patent No. 10,526,890, hereinafter “Batmaz”), in view of Ouenes (U.S. Patent Pub. No. 2017/0145793, hereinafter “Ouenes”) and Liu, et al., (U.S. Patent Pub. No. 2021/0124087, hereinafter “Liu”). Claim 1 Batmaz discloses: receiving stress change correlations over space and time for injection and production of fluids to or from a reservoir; An example of a workflow for calculating stresses in a formation according to embodiments of the present disclosure is shown in FIG. 9, which may be used for calculating principle stresses of a borehole. As shown, a data audit 901 may be performed to collect data available of the formation being analyzed. For example, data may be collected using a sonic measurement tool or an image logging tool, and data may be collected from, for example, one or more current boreholes drilled in the formation, seismic testing, or one or more offset wells. Batmaz at col. 11, lines 28-37. As new information accumulates, such as from additional data acquired in wellbores after or while drilling, well test data, or subsequent seismic surveys, a more detailed MEM of the rock formations at the reservoir level may be developed. MEMs may be used, for example, for designing completions, performing fracture stimulation, and simulating reservoir production. Batmaz at col. 11, lines 21-27. Collection from “one or more boreholes” is analogous to “over space” measurements of “stresses of a borehole” (i.e., “stress change correlations”). Collection “as new information accumulates” is analogous to “over…time.” determining, using reservoir geomechanical modeling tools and using the stress change correlations, a stress distribution of the reservoir; A three-dimensional model may then be constructed 902 to use as a framework model and determine drilling hazards. The model may be based on the data audit, and may include, for example, locations of major faults. Batmaz at col. 11, lines 38-41. Further, measurements characterizing a formation may be used in modeling a reservoir system, for example, by using a mechanical earth model (“MEM”). As used herein, an MEM is a numerical representation of the geomechanical state of the reservoir, field, or basin. In addition to property distribution (e.g., density, porosity) and fracture system, an MEM may incorporate pore pressures, state of stress, and rock mechanical properties. The stresses on the reservoir may be caused by overburden weight (vertical stress), any superimposed tectonic forces, localized forces (e.g., resulting from faults, fractures, laminations, depositional orientation, variability in rock mechanical properties, etc.), and by production and injection. Various types of MEMs may be used, such as well-centric MEMs (concentrated on borehole effects, such as breakouts, collapses, sanding, and wellbore stability issues, and may be used for near-well dynamic simulations) and field wide MEMs (may be used to evaluate the effects of drilling and producing for full-field dynamic simulations), which may include time-lapse modeling of fluid flow and pressure, temperature changes, and associated effects on stresses. Batmaz at col. 10, line 62-col. 11, line 16. An “MEM” is a “reservoir geomechanical modeling tool.” “Locations of major faults,” “overburden weight,” “state of stress,” and “rock mechanical properties” are examples of “stress distribution of the reservoir.” determining, using the optimized injection or production and placement of wells, an optimum stress distribution for placement of new wells and fractures in terms of orientation and size to maximize recovery of hydrocarbons; After re-evaluation of reservoir characterization 12, completion and stimulation 14 may be analyzed and optimized. As mentioned above, increased production may depend, in part, on choosing a well in a location having good reservoir quality. However, increasing production in wells having stress regime heterogeneity may depend on having both good reservoir quality and good completion quality. Completion quality includes a set of properties that allows for effective reservoir contact through the creation of optimal hydraulic fracture geometry that provides connectivity to the wellbore and maintains sufficient conductivity for hydrocarbon production. This effective reservoir contact may be enhanced by hydraulic fractures that connect to the pre-existing natural fractures, but may be negatively impacted by features such as laminations that may compromise vertical connectivity within the hydraulic fracture. Batmaz at col. 14, lines 47-63. The “properties that allows for effective reservoir contact through the creation of optimal hydraulic fracture geometry” are analogous to “optimum stress distribution” for a well. controlling drilling equipment for drilling of a new well by using the location of well placement and the fracture design, by adjusting drilling parameters comprising a speed and a direction of the drilling equipment. Upon modeling the borehole through the formation and/or the hydraulic fracturing operation, the borehole may be drilled through the formation. In some embodiments, a new trajectory of a borehole being drilled may be modeled to extend through at least one normal stress regime region. Based on the model of the new trajectory, the drilling direction of the borehole may be altered. Batmaz at col. 18, lines 13-15. [A] new trajectory of a borehole being drilled may be modeled to extend through at least one normal stress regime region. Based on the model of the new trajectory, the drilling direction of the borehole may be altered. Batmaz at col. 18, lines 15-19. “Trajectory” includes a path of an object over time, which includes the speed of the object. Batmaz does not appear to disclose: A computer-implemented method2, comprising: determining, using the stress distribution of the reservoir and field-wide geomechanical properties for optimizing treatment, a fracture growth defining, using a fracturing model, a predicted propagation behavior of a fracture in the reservoir; determining fracture design and orientation for optimum recovery of hydrocarbons by by analyzing spatio-temporal relationships between the injection of the fluids to the reservoir and the production of the fluids from the reservoir and, by analyzing geomechanical changes, the stress distribution, reservoir geomechanical characteristics and flow characteristics using the fracture growth, determining changes in the stress distribution in the reservoir through injection or production of fluids relative to field configurations comprising the single well and the plurality of wells; determining, using the changes in the stress distribution and the fracture design and orientation, an optimized injection or production and placement of wells, comprising using machine learning to adjust injection and production of fluids to or from the reservoir; determining, using the optimized injection or production and placement of wells, an optimum stress distribution for placement of new wells; determining, using the optimum stress distribution, location of well placement and fracture design comprising orientation and size of fractures to maximize recovery of hydrocarbons; Ouenes, which is analogous art, discloses: A computer-implemented method, comprising: Properties of the injection treatment can be calculated or selected based on computer simulations of complex hydraulic fracture 121 propagation and interaction with the natural fracture network 109 in the subterranean region 104. Ouenes at [0043]. determining, using the stress distribution of the reservoir- and field-wide geomechanical properties for optimizing treatment, a fracture growth defining, using a fracturing model, a propagation behavior of a fracture in the reservoir; The present invention uses these initial geomechanical conditions as input in the simulation of the hydraulic fracturing and the resulting interaction between the hydraulic and natural fractures which lead to a complex distribution of the strain around the stimulated well. Ouenes at [0049]. A major feature of the present invention is its ability to first combine the continuous representation of the natural fractures as a 2D map or a 3D volume derived from multiple sources that is then transformed into an equivalent fracture model where natural fractures or faults are represented by segments of certain lengths and orientations, which are used as input into a meshless particle-based geomechanical simulator able to represent explicitly the natural fractures or faults. Another major feature is the ability to model in the meshless particle-based method the interaction between the regional stress with the equivalent fracture model to quickly yield (i.e., in only few hours) horizontal differential stress maps and local maximum principal stresses directions, which can be used as the proper initial geomechanical conditions present before hydraulic fracturing. The meshless particle-based geomechanical simulator able to represent explicitly the natural fractures with the proper derived initial geomechanical conditions is used to add explicitly hydraulic fractures which are pressurized to reproduce the stress effects, and its propagation in the continuum reservoir, created during a hydraulic fracturing operations. The resulting strain is used to interpret geomechanical asymmetric half-lengths that can be input as a constraint into hydraulic fracturing design software to estimate the fracture heights and stress gradient at each stimulation stage. Ouenes at [0015]. “A meshless particle-based geomechanical simulator” is “a fracture model” that models “stress effects, and its propagation in the continuum reservoir, created during a hydraulic fracturing operations” (analogous to “fracture growth” and “propagation behavior”). The result is provided to “hydraulic fracturing design software to estimate the fracture heights and stress gradient at each stimulation stage” (analogous to “optimizing treatment”). “Estimating the fracture heights and stress gradient” is analogous to “predicted propagation behavior.” determining fracture design and orientation for optimum recovery of hydrocarbons by FIGS. 5a-5b are flowcharts of an exemplary method of hydraulic fracture design and completion optimization according to the present invention. Ouenes at [0050]. by analyzing spatio-temporal relationships between the injection of the fluids to the reservoir and the production of the fluids from the reservoir and, by analyzing geomechanical changes, the stress distribution, reservoir geomechanical characteristics and flow characteristics using the fracture growth, using a first model of a single well and a second model of a plurality of wells; determining changes in the stress distribution in the reservoir through injection or production of fluids relative to field configurations comprising the single well and the plurality of wells; The meshless particle-based geomechanical simulator able to represent explicitly the natural fractures with the proper derived initial geomechanical conditions is used to add explicitly hydraulic fractures which are pressurized to reproduce the stress effects, and its propagation in the continuum reservoir, created during a hydraulic fracturing operations. Ouenes at [0015]. “Stress effects” are analogous to “stress distributions.” “Hydraulic fractures which are pressurized” is analogous to “injection or production of fluids” (i.e., injecting fluids causes pressurization of the fractures). determining, using the optimum stress distribution, FIGS. 5a-5b are flowcharts of an exemplary method of hydraulic fracture design and completion optimization according to the present invention. Ouenes at [0050]. Ouenes is analogous art to the claimed invention because are related to simulations of reservoir properties to assist in hydraulic fracturing operations. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the application, to combine the fracture modeling of Ouenes with the data collection methods disclosed in Batmaz to result in a system that can estimate stress distributions of a reservoir and model natural and hydraulic fractures based on the modeled distributions. Motivation to combine includes streamlining and automating parts of the well selection process to ensure a profitable well, thus saving time and costs associated with underperforming wells. Ouenes does not appear to disclose: determining, using the changes in the stress distribution and the fracture design and orientation, an optimized injection or production and placement of wells, comprising using machine learning to adjust injection and production of fluids to or from the reservoir; Liu, which is analogous art, discloses: determining, using the changes in the stress distribution and the fracture design and orientation, an optimized injection or production and placement of wells, comprising using machine learning to adjust injection and production of fluids to or from the reservoir; In some implementations, the data from the hydrocarbon reservoir includes at least one of a hydraulic fracture geometry of the hydrocarbon reservoir; an injection rate of the hydrocarbon reservoir; or a mineral composition and an in situ stress of the hydrocarbon reservoir. Liu at [0006]. The disclosed methods and systems use measured reservoir characterization data, measured hydraulic fracturing data, and measured production rates of multiple hydrocarbon reservoirs and production wells to train a physics-constrained machine learning model. The physics-constrained machine learning model includes an artificial neural network to generate parameters that correspond to the physical mechanisms for fluid flow in the unconventional hydrocarbon reservoir. The physics-constrained machine learning model includes a reservoir flow model to predict hydrocarbon production rates for the hydrocarbon reservoir as a function of time based on the parameters. Liu at [0021]. Moreover, the methods and systems are used to estimate potential production as a function of time at geographical locations where production wells are not drilled yet. Therefore, optimal geographical locations for drilling production wells are determined. Liu at [0022]. The “parameters that correspond to the physical mechanisms for fluid flow in the unconventional hydrocarbon reservoir” are analogous to “optimized injection/production.” “Generated properties” include “adjusting injection and production fluids” determining, using the optimum stress distribution, location of well placement Moreover, the methods and systems are used to estimate potential production as a function of time at geographical locations where production wells are not drilled yet. Therefore, optimal geographical locations for drilling production wells are determined. Liu at [0022]. Liu is analogous art to the claimed invention because both are related to optimum well placement and hydraulic fracturing. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the application, to combine the injection/production regulation of Liu with the models of Batmaz and Ouenes to maintain production levels once geomechanical properties and stress distributions are determined. Motivation to combine includes ensuring a completed well maintains an acceptable production level to improve profitability of the well. Claim 8 Liu discloses: A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations In some implementations, the hardware processors 108 are general-purpose microprocessors. The computer system 100 also includes a main memory 606, such as a random-access memory (RAM) or other dynamic storage device, coupled to the bus 602 for storing information and instructions to be executed by processors 108. Liu at [0055]. Further, claim 8 recites a method that is substantially the same as the method disclosed in claim 1. Accordingly, for at least the same reasons and based on the same prior art as 1, claim 8 is rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes and Liu. Claim 15 Liu discloses: A computer-implemented system, comprising: one or more processors; and a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors, the programming instructions instructing the one or more processors to perform operations The computer system 100 is used to train the physics-constrained machine learning model 116 to generate a predicted hydrocarbon production rate for the hydrocarbon reservoir 128 as a function of time. An implementation of the computer system 100 is illustrated and described in more detail later with reference to FIG. 6. The computer system 100 includes a physics-constrained machine learning model 116, one or more computer processors 108, a storage device 112, training data 120, and a display device 124. The computer processors 108 are computer hardware used to perform the methods disclosed herein. Liu at [0029]. Further, claim 15 recites limitations that are substantially the same as the limitations recited in claim 1. Accordingly, for at least the same reasons and based on the same prior art as claim 1, claim 15 is rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes and Liu. Claims 2, 3, 9, 10, 16, and 17 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Garcia-Teijeiro, et al., (U.S. Patent No. 10,788,604, hereinafter “Garcia”). Claim 2 Batmaz, Ouenes, and Liu do not appear to disclose: generating, for display in a user interface, a plot showing a single well pressure distribution for a single well model. Garcia, which is analogous art to the claimed invention, discloses: generating, for display in a user interface, a plot showing a single well pressure distribution for a single well model. FIG. 9 shows examples of plots 910, 930 and 950. The plot 910 illustrates three-dimensional stress change in a neighborhood of a hydraulic fracture in a model where the hydraulic fracture is made within a model of a homogeneous medium. The plot 910 includes examples of values of Δfs (e.g., in psi) some of which are less than zero and some of which are greater than zero…In the plots 930 and 950 the abscissa (σ) and ordinate (τ) of each point on a circle are the magnitudes of the normal stress and shear stress components, respectively (e.g., acting on the rotated coordinate system). Garcia at col. 18, lines 29-42. See also FIG. 9, illustrating a single well and pressures surrounding the well. Garcia is analogous art to the claimed invention because both are related to illustrating well data related to hydraulic fracturing and reservoir stresses and pressures. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the application, to combine Garcia with the analysis performed in Ouenes, Liu, and Batmaz to generate plots of the modeled characteristics. Motivation to combine includes providing engineers with visual representations of reservoir and well conditions to improve readability of the model results and assist the engineers in making decisions regarding drilling new wells and maintenance of existing wells. Claim 3 Batmaz, Ouenes, and Liu do not appear to disclose: generating, for display in a user interface, a diagram showing a grid investigated for shear strain and shear stress. Garcia discloses: generating, for display in a user interface, a diagram showing a grid investigated for shear strain and shear stress. In such an example, one or more increases in the projected shear plastic strain, with respect to the referential value, on a fracture may be interpreted as a microseismic event. Garcia at col. 21, lines 16-19. As an example, the plastic strain tensor (e.g., used to compute microseismicity) may be decomposed into the normal and shear components on the discontinuity planes. Garcia at col. 21, lines 29-32. Microseismicity recorded during multistage fracture treatments may provide disperse “clouds” of events (e.g., located at individual event hypocenters). As an example, a method can include analyzing clouds of events to extract planar-type features, which may be indicative of fracture location, directions of stresses, etc. Garcia at col. 15, lines 60-65. FIG. 5 shows an example of a geologic environment 501 in an approximate perspective view and in an approximate side view where the geologic environment includes a monitoring bore 543 with a sensor array 544, a treatment bore 546, a fracture 548, a surface 549 and surface sensors 554 (e.g., seismic sensors, tiltmeters, etc.). As an example, during growth of the fracture 548, energy may be emitted as a microseismic event 556. Garcia at col. 14, lines 15-22. Claims 9 and 10 Claims 9 and 10 recite limitations that are substantially the same as the limitations disclosed in claim 2 and 3. Accordingly, for at least the same reasons and based on the same prior art as claims 2 and 3, claims 9 and 10 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Garcia. Claims 16 and 17 Claims 16 and 17 recite limitations that are substantially the same as the limitations recited in claims 2 and 3. Accordingly, for at least the same reasons and based on the same prior art as claims 2 and 3, claims 16 and 17 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Garcia. Claims 4, 11, and 18 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Shen, et al., (U.S. Patent Pub. No. 2019/0211653, hereinafter “Shen”). Claim 4 Batmaz, Ouenes, and Liu do not appear to disclose: generating, for display in a user interface, a three-dimensional (3D) plot showing different phenomena of shear strain between a toe and a heel of a well within an IJ plane. Shen, which is analogous art to the claimed invention, discloses: generating, for display in a user interface, a three-dimensional (3D) plot showing different phenomena of shear strain between a toe and a heel of a well within an IJ plane. FIG. 10 is a graphical display illustrating the contour of normal strain in the horizontal direction (LE11) within the model in FIG. 2 at time t=1,008,110 s. Shen at [0015]. The figure illustrates a horizontal well, which is horizontal (“an IJ direction”) between a heel and a toe of the wellbore. Shen is analogous art to the claimed invention because both are related to injection processes to improve petroleum extraction in wells. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the application, to combine the plots of Shen with the models of Batmaz, Ouenes, and Liu to provide a graphical representation of the modeled characteristics. Motivation to combine includes providing engineers with visual representations of reservoir and well conditions to improve readability of the model results and assist the engineers in making decisions regarding drilling new wells and maintenance of existing wells. Claims 11 and 18 Claims 11 and 18 recite limitations that are substantially the same as the limitations disclosed in claim 4. Accordingly, for at least the same reasons and based on the same prior art as claim 4, claims 11 and 18 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Shen. Claim 5, 12, and 19 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Boone, et al., (U.S. Patent Pub. No. 2011/0272153, hereinafter “Boone”). Claim 5 Batmaz, Ouenes, and Liu do not appear to disclose: generating, for display in a user interface, a plot showing a gas saturation distribution of a parent well and a child well. Boone, which is analogous art to the claimed invention, discloses: generating, for display in a user interface, a plot showing a gas saturation distribution of a parent well and a child well. FIG. 18 shows the 3D results of reservoir simulations modeling a CSS operation in a partitioned reservoir with Athabasca Cold Lake type properties and one vertical permeability barrier, comparing gas saturation in a typical split pay reservoir with a split pay reservoir having a zone of increased permeability extending through the vertical permeability barrier above each of two adjacent horizontal CSS wells, in accordance with an embodiment of the invention; Boone at [0043]. Boone is analogous art to the claimed invention because both are related to enhanced petroleum recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the application, to combine the plots of Boone with the models of Batmaz, Ouenes, and Liu to provide a graphical representation of the modeled characteristics. Motivation to combine includes providing engineers with visual representations of reservoir and well conditions to improve readability of the model results and assist the engineers in making decisions regarding drilling new wells and maintenance of existing wells. Claims 12 and 19 Claims 12 and 19 recite limitations that are substantially the same as the limitations disclosed in claim 5. Accordingly, for at least the same reasons and based on the same prior art as claim 5, claims 12 and 19 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Boone. Claim 6, 13, and 20 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Shen and Boone. Claim 6 Batmaz, Ouenes, and Liu do not appear to disclose: generating, for display in a user interface, a 3D plot of shear strain in a parent well and a child well. Shen discloses: generating, for display in a user interface, a 3D plot of shear strain in a well. FIG. 10 is a graphical display illustrating the contour of normal strain in the horizontal direction (LE11) within the model in FIG. 2 at time t=1,008,110 s. Shen at [0015]. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the application, to combine the plots of Shen with the models of Batmaz, Ouenes, and Liu to provide a graphical representation of the modeled characteristics. Motivation to combine includes providing engineers with visual representations of reservoir and well conditions to improve readability of the model results and assist the engineers in making decisions regarding drilling new wells and maintenance of existing wells. Shen does not appear to disclose: a parent well and a child well. Boone discloses: a parent well and a child well. FIG. 18 shows the 3D results of reservoir simulations modeling a CSS operation in a partitioned reservoir with Athabasca Cold Lake type properties and one vertical permeability barrier, comparing gas saturation in a typical split pay reservoir with a split pay reservoir having a zone of increased permeability extending through the vertical permeability barrier above each of two adjacent horizontal CSS wells, in accordance with an embodiment of the invention; Boone at [0043]. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the application, to combine Shen with the plots of Boone to model multiple wells that are in the same vicinity, such as parent and child wells. Motivation to combine includes providing data on multiple wells simultaneously, which improves analysis because, in some circumstances, one well can have effects on other wells. Claims 13 and 20 Claims 13 and 20 recite limitations that are substantially the same as the limitations disclosed in claim 6. Accordingly, for at least the same reasons and based on the same prior art as claim 6, claims 13 and 20 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Shen and Boone. Claims 7 and 14 are rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Herrera, et al., (U.S. Patent Pub. No. 2018/0355707, hereinafter “Herrera”). Claim 7 Batmaz, Ouenes, and Liu do not appear to disclose: generating, for display in a user interface, a 3D plot of shear stress in a parent well and a child well. Herrera, which is analogous art, discloses: generating, for display in a user interface, a 3D plot of shear stress in a parent well and a child well. FIG. 15 is a plot of microseismic event predictions 1576.1 about the modeled fractures 774.1 for a pair of adjacent wellbores 1504.1, 1504.2. The estimated microseismic events 1576.1 are shown as solid circles with darker shading indicating greater stress. Measured microseismic events 1576.2 are also shown. The microseismic events 1576 may be computed from stress drop that occurs during reactivation of the natural fractures. The predicted microseismic events can also be used for calibration to field observations. Herrera at [0178]. “Microseismic events” are analogous to “shear stress.” Herrera is analogous art to the claimed invention because both are related to reservoir fracturing to generate petroleum production. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the application, to combine the plots of Herrera with the models of Batmaz, Ouenes, and Liu to provide a graphical representation of the modeled characteristics. Motivation to combine includes providing engineers with visual representations of reservoir and well conditions to improve readability of the model results and assist the engineers in making decisions regarding drilling new wells and maintenance of existing wells. Claims 14 Claim 14 recites limitations that are substantially the same as the limitations disclosed in claim 7. Accordingly, for at least the same reasons and based on the same prior art as claim 7, claim 14 is rejected under 35 U.S.C. 103 as being obvious over Batmaz in view of Ouenes, Liu, and further in view of Herrera. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure: Blauch, et al. (U.S. Pat. No. 5,277,062), “Measuring in situ stress, induced fracture orientation, fracture distribution and spatial orientation of planar rock fabric features using computer tomography imagery of oriented core.” Soliman, et al., (U.S. Pat. Pub. No. 2005/0125209), “Methods for geomechanical fracture modeling.” Wang, et al., “Integrated well placement and fracture design optimization for multi-well pad development in tight oil reservoirs,” Computational Geosciences (2019) 23:471–493. Ebadat, et al., “Well placement optimization according to field production curve using gradient-based control methods through dynamic modeling,” Journal of Petroleum Science and Engineering 100 (2012) 178–188. 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. Communication Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEPH MORRIS whose telephone number is (703)756-5735. The examiner can normally be reached M-F 8:30-5:00. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan Pitaro can be reached at (571) 272-4071. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. JOSEPH MORRIS Examiner Art Unit 2188 /JOSEPH P MORRIS/Examiner, Art Unit 2188 /EUNHEE KIM/Primary Examiner, Art Unit 2188 1 This suggestion is in light of how the recited abstract ideas could be considered significantly more than an idea of a solution, therefore overcoming the rejection at Step 2B. The suggestion does not take into account the specific disclosure in the Specification and Examiner suggests that any additional amendments that address this suggestion be accompanied by citations to the Specification. Further, any further consideration will be contingent on the particular presented amendment and how the ideas suggested are integrated. 2 Not explicitly disclosed by Batmaz, though the modeling disclosed would be implemented on a computing device.
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Nov 06, 2025
Final Rejection mailed — §101, §103, §112
Dec 10, 2025
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Dec 11, 2025
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Dec 12, 2025
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Dec 22, 2025
Response after Non-Final Action
Mar 10, 2026
Non-Final Rejection mailed — §101, §103, §112
May 12, 2026
Response Filed
Aug 13, 2026
Final Rejection mailed — §101, §103, §112 (current)

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