DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
2. 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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
In view of the new 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register Vol. 84, No. 4, January 7, 2019), the Examiner has considered the claims and has determined that under step 1, claims 1-7 are to a machine, claims 8-15 are to a process, and claims 16-20 are to a process. Next under the new step 2A prong 1 analysis, the claims are considered to determine if they recite an abstract idea (judicial exception) under the following groupings: (a) mathematical concepts, (b) certain methods of organizing human activity, or (c) mental processes. The independent claims contain at least the following bolded limitations (see representative independent claims) that fall into the grouping of mathematical concepts and/or mental processes:
1. A system comprising:
memory to store machine-readable instructions;
and one or more processors to access the memory and execute the machine-readable instructions, the machine-readable instructions comprising:
a structural geology module to extract one or more geological properties of a naturally fractured reservoir and sub-seismic lineaments from a static fracture model and input data;
a clustering module to determine trends in properties of the sub-seismic lineaments and the naturally fractured reservoir; and
a paleo-stress region module to define one or more paleo-stress regions within the static fracture model based on the trends.
8. A computer-implemented method comprising:
receiving a static fracture model and input data for a naturally fractured reservoir;
performing one or more geological analyses on the static fracture model and input data to extract sub-seismic lineaments and geological properties of the naturally fractured reservoir;
performing one or more clustering analyses on the static fracture model utilizing the sub-seismic lineaments and geological properties to generate trends within the static fracture model;
identifying paleo-stress regions within the static fracture model as natural fracture regions based on the trends; and
performing history matching on the identified paleo-stress regions for mapping historical data for dynamic simulation of the identified paleo-stress regions.
16. A computer-implemented method comprising:
receiving a static fracture model and input data for a naturally fractured reservoir;
obtaining changes in natural fracture orientations within the naturally fractured reservoir based on the static fracture model and the input data;
obtaining variations of maximum horizontal stress directions within the naturally fractured reservoir based on principal stresses therein;
determining one or more paleo-stress regions based on the changes in natural fracture orientations and the variations of maximum horizontal stress directions; and
history matching each determined paleo-stress region to a known quantity of dynamic response based upon a known dynamic response, a historical data set, or a plurality of assumptions for flow characteristics.
It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula."(see MPEP 2106.04(a)(2) I.). The limitations to "extract one or more geological properties of a naturally fractured reservoir and sub-seismic lineaments from a static fracture model and input data" amount to a mental step to evaluate and identify properties data, or a mathematical calculation step to solve for geological properties from a static fracture model and input data. The limitations to "determine trends in properties of the sub-seismic lineaments and the naturally fractured reservoir" amount to a mental process to evaluate data and recognize patterns, or a mathematical analysis to solve for trends and commonalities in properties data. The limitations to "define one or more paleo-stress regions within the static fracture model based on the trends" amounts to a mental process to categorize or classify sets of data as paleo-stress regions based on the trends, or a mathematical calculation to solve for similar sets of data to define paleo-stress regions within the static fracture model based on the trends. The limitations of "performing one or more geological analyses on the static fracture model and input data to extract sub-seismic lineaments and geological properties of the naturally fractured reservoir" amount to a a mental process to carry out data evaluation and analysis to recognize sub-seismic lineaments and geological properties, or a mathematical calculation if the extraction process requires a more complicated mathematical analysis. The limitations of "performing one or more clustering analyses on the static fracture model utilizing the sub-seismic lineaments and geological properties to generate trends within the static fracture model" amounts to a mental process to classify and group together similar sub-seismic lineament and geological data to recognize trends, or a mathematical analysis to carry out clustering of numerical data to solve for trends in the model. The limitations of "identifying paleo-stress regions within the static fracture model as natural fracture regions based on the trends" amounts to a mental process to identify and classify paleo-stress regions based on the trends, or a mathematical analysis to solve for similar data identifying a paleo-stress region based on the trends. The limitations of "performing history matching on the identified paleo-stress regions for mapping historical data for dynamic simulation of the identified paleo-stress regions" amounts to a mental process to compare between different sets of data. The limitations of "obtaining changes in natural fracture orientations within the naturally fractured reservoir based on the static fracture model and the input data" amounts to a mental process to recognize changes or differences in natural fracture orientations by a user analyzing or visualizing the data from the static fracture model and input data, or a mathematical analysis to solve for changes or differences based on a more complex mathematical analysis of the static fracture model data and input data. The limitations of "obtaining variations of maximum horizontal stress directions within the naturally fractured reservoir based on principal stresses therein" amounts to a mental process to recognize changes or variations in the directions of the data, or a mathematical concept to solve for the variations of maximum horizontal stress directions based on the principal stress data. The limitations of "determining one or more paleo-stress regions based on the changes in natural fracture orientations and the variations of maximum horizontal stress directions" amounts to a mental process to identify and classify one or more paleo-stress regions based on analyzing the data of the changes in natural fracture orientations and variations of maximum horizontal stress directions, or a mathematical calculation to solve for similar data to classify a paleo-stress region based on inputs of the changes in natural fracture orientations and variations of maximum horizontal stress directions. The limitations of "history matching each determined paleo-stress region to a known quantity of dynamic response based upon a known dynamic response, a historical data set, or a plurality of assumptions for flow characteristics" amounts to a mental process to compare between different sets of data. Taken together, the bolded limitations in the independent claims above describe a series of algorithmic steps that can be carried out by a person mentally or on pen and paper to obtain input data and solve for an output data result (identified paleo-stress regions and/or recognized history data comparison matches). The analysis of the EPG Court is particularly applicable to the claims in the present case: "Accordingly, we have treated collecting information, including when limited to particular content (which does not change its character as information), as within the realm of abstract ideas. In a similar vein, we have treated analyzing information by steps people go through in their minds, or by mathematical algorithms, without more, as essentially mental processes within the abstract-idea category," (see Electronic Power Group, LLC v. Alstom, 830 F. 3d 1350, 119 U.S.P.Q. 2d 1739 (Fed. Cir. 2016) at pg. 7).
Next in step 2A prong 2, the independent claims are analyzed to determine whether there are additional elements or combination of elements that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception such that it is more than a drafting effort designed to monopolize the exception, in order to integrate the judicial exception into a practical application. These limitations have been identified and underlined above, and are not indicative of integration into a practical application because: (1) the recitations of "a system comprising: memory to store machine-readable instructions," "one or more processors to access the memory and execute the machine-readable instructions, the machine-readable instructions comprising: a structural geology module…a clustering module…and a paleo-stress region module," and "a computer-implemented method," amount to mere instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); and (2) the recitations of "receiving a static fracture model and input data for a naturally fractured reservoir" amount to adding insignificant extra-solution data gathering activity to the judicial exception (see MPEP 2106.05(g)). Next in step 2B, the independent claims are considered to determine if they recite additional elements that amount to an inventive concept (“significantly more”) than the recited judicial exception.
These limitations have been identified and also underlined above, and are not indicative of "significantly more" than the judicial exception because: (1) the recitations of "a system comprising: memory to store machine-readable instructions," "one or more processors to access the memory and execute the machine-readable instructions, the machine-readable instructions comprising: a structural geology module…a clustering module…and a paleo-stress region module," and "a computer-implemented method," amount to mere instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), where merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection (see Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94); and (2) the recitations of "receiving a static fracture model and input data for a naturally fractured reservoir" amount to adding insignificant extra-solution data gathering activity to the judicial exception (see MPEP 2106.05(g)), and do not describe any data gathering in an unconventional way or using a particular physical measurement structure.
Dependent claims 2-7 and 9-15, and 17-20 contain additional limitations that fall under the abstract idea groupings of a mental process and/or mathematical concept to describe additional comparisons, types of data processed, and additional mental analysis steps or calculations of the overall algorithm. Dependent claim 19 recites displaying the dynamic simulation responses on an output device, which amounts to insignificant post-solution activity to output a calculation result (see MPEP 2106.05(g)).
3. An invention is not rendered ineligible for patent simply because it involves an abstract concept. Applications of such concepts "to a new and useful end" remain eligible for patent protection (see Alice Corp., 134 S. Ct. at 2354 (quoting Benson, 409 U.S. at 67)). However, "a claim for a new abstract idea is still an abstract idea" (see Synopsys v. Mentor Graphics Corp. _F.3d_, 120 U.S.P.Q. 2d1473 (Fed. Cir. 2016)). There needs to be additional elements or combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception or render the claim as a whole to be significantly more than the exception itself in order to demonstrate “integration into a practical application” or an “inventive concept.” For instance, particular physical arrangements for actively obtaining the sensor data, or further physical applications using the calculated paleo-stress regions and/or history matches to drive a transformation, change in physical operation, or repair/maintenance of a technology or technical process could provide integration into a practical application to demonstrate an improvement to the technology or technical field.
Claim Rejections - 35 USC § 102
4. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
5. Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lejri et al. (US Pat. Pub. 2018/0172857, hereinafter "Lejri").
In regards to claim 1, Lejri teaches a system comprising (Lejri Fig. 2 and paragraph [0063] teach a system 250):
memory to store machine-readable instructions (Lejri paragraph [0063] teaches the system comprising a memory 258 for storing machine-readable instructions); and
one or more processors to access the memory and execute the machine-readable instructions, the machine-readable instructions (Lejri paragraph [0063] teaches the system comprising one or more processors 256 for executing the instructions) comprising:
a structural geology module to extract one or more geological properties of a naturally fractured reservoir (Lejri paragraph [0033] teaches a simulation component as a structural geology module that extracts one or more properties of an entity such as a reservoir) and sub-seismic lineaments from a static fracture model (Lejri paragraph [0034] teaches where the simulation component operates in conjunction with a software framework, and paragraph [0024] and [0027] teaches where a framework can include instructions to implement a boundary element method (BEM) where surfaces in space are described via boundary elements (lineaments), for providing characterization and modeling of subseismic fractures; Lejri paragraph [0025] teaches where the model may be steady-state (static)) and input data (Lejri paragraph [0035] teaches where the simulation component also performs operations on input information based on one or more attributes);
a clustering module to determine trends in properties of the sub-seismic lineaments and the naturally fractured reservoir (Lejri paragraph [0103] suggests a clustering module for carrying out a numerical iterative technique based on dynamic cluster analysis to separate heterogeneous sets of data into subsets, and paragraph [0116] teaches where the clustering leads to polyphase inversion for determining separated fracture types (fracture data trends for each type of fracture) to allow a reservoir engineer to predict fracture distribution and orientation)); and
a paleo-stress region module to define one or more paleo-stress regions within the static fracture model based on the trends (Lejri paragraph [0146] suggests a paleo-stress region module for carrying out a stress inversion technique based on analyzing the trends from the clusterized subsets, in order to define an individual stress inversion solution (region) in a tectonic stress domain as a dot with a particular area; Lejri paragraphs [0002], [0084], and [0117] teach where the inversion technique allows for paleostresses to be inferred).
In regards to claim 2, Lejri teaches the system wherein the paleo-stress region module generates history matched paleo-stress regions including a dynamic behavior or one or more fluid flow assumptions for the one or more paleo-stress regions (Lejri paragraphs [0145] and [0147] teach performing history matching of the defined paleostress fracture region to one or more historically observed fracture regions, and paragraph [0103] teaches where the data making up the subsets are analyzed for the dynamics of faulting).
In regards to claim 3, Lejri teaches the system wherein the machine-readable instructions cause the processor (Lejri paragraph [0063]) to further:
perform one or more dynamic simulations on the static fracture model with the defined one or more paleo-stress regions (Lejri paragraph [0147] teaches performing a forward simulation on one or more of the plotted stress region solutions, where paragraph [0103] teaches that the data subsets are analyzed for the dynamics of faulting).
In regards to claim 4, Lejri teaches the system wherein the input data includes a borehole image (Lejri paragraphs [0040] and [0053] teach where the input data includes seismic borehole image data) and the structural geology module is to extract sub-seismic lineaments from the borehole image (Lejri paragraph [0026] teaches where the software framework (of a structural geology module) performs seismic interpretation from the received seismic borehole image data, where the framework includes a boundary element method (BEM or iBEM) framework; Lejri paragraph [0024] teaches where the boundary element method describes surfaces in space via boundary elements (lineaments)).
In regards to claim 5, Lejri teaches the system wherein the clustering module is to determine the trends based on the extracted sub-seismic lineaments (Lejri paragraphs [0178]-[0179] teach where the boundary elements (lineaments) may represent some portion of a fracture of a fault surface across which a discontinuity in displacement is approximately constant, and several such elements (having the same trend) may be joined (clustered) together for modeling geological structures with various 3D boundaries and shapes).
In regards to claim 6, Lejri teaches the system wherein the structural geology module calculates principal stress magnitudes (Lejri paragraph [0065] teaches calculating principal stress magnitudes) using a poro-elasticity stress model (Lejri paragraph [0186] teaches carrying out stress analysis via the principle of superposition that can apply to linear elasticity for a model of heterogeneous, isotropic whole-of half space media, and paragraph [0051] teaches where porosity distributions in the basin and petroleum systems (media) are modeled).
In regards to claim 7, Lejri teaches the system wherein the clustering module calculates a maximum horizontal stress direction based on the principal stress magnitudes to produce directional trends within the naturally fractured reservoir for defining the one or more paleo-stress regions (Lejri paragraphs [0066]-[0067] teach calculating maximum horizontal stress directions based on the principal stress magnitudes to produce stress trends along orthogonal axes for defining a tectonic regime (paleo-stress regime)).
In regards to claim 8, Lejri teaches a computer-implemented method (Lejri paragraph [0003] teaches a method carried out by a computing system (computer)) comprising:
receiving a static fracture model and input data for a naturally fractured reservoir (Lejri paragraph [0025] teaches receiving steady-state (static) modeling equations for modeling an oil and gas field, where paragraph [0027] teaches application of modeling to subseismic fractures in a reservoir; Lejri paragraph [0035] teaches also receiving input information based on one or more attributes);
performing one or more geological analyses on the static fracture model and input data (Lejri paragraph [0035] teaches performing a geological analysis simulation based on the model and input data) to extract sub-seismic lineaments and geological properties of the naturally fractured reservoir (Lejri paragraphs [0024] and [0027] teach implementing a boundary element method (BEM) for extracting boundary elements (lineaments) and geological properties such as stress fields);
performing one or more clustering analyses on the static fracture model utilizing the sub-seismic lineaments and geological properties to generate trends within the static fracture model (Lejri paragraph [0103] teaches carrying out a numerical iterative technique based on dynamic cluster analysis to separate heterogeneous sets of data into subsets, and paragraph [0116] teaches where the clustering leads to polyphase inversion for determining separated fracture types (fracture data trends for each type of fracture) to allow a reservoir engineer to predict fracture distribution and orientation));
identifying paleo-stress regions within the static fracture model as natural fracture regions based on the trends; (Lejri paragraph [0146] teaches carrying out a stress inversion technique based on analyzing the trends from the clusterized subsets, in order to identify each individual stress inversion solution (region) in a tectonic stress domain as a dot with a particular area; Lejri paragraphs [0002], [0084], and [0117] teach where the inversion technique allows for paleostresses to be inferred); and
performing history matching on the identified paleo-stress regions for mapping historical data for dynamic simulation of the identified paleo-stress regions (Lejri paragraphs [0145] and [0147] teach performing history matching of the predicted (identified) paleostress fracture region to one or more historically observed fracture regions, in order to carry out a forward simulation; Lejri paragraph [0103] teaches that the data subsets are analyzed for the dynamics of faulting).
In regards to claim 9, Lejri teaches the method wherein the one or more geological analyses includes analyzing seismic discontinuities in a three-dimensional (3D) seismic volume to identify the sub-seismic lineaments (Lejri paragraphs [0024] and [0137] teach analyzing 3D discontinuities in an elastic, heterogeneous, isotropic whole or half-space seismic volume to identify boundary elements (sub-seismic lineaments)).
In regards to claim 10, Lejri teaches the method wherein the one or more geological analyses includes interpreting a borehole image received as the input data (Lejri paragraphs [0040] and [0053] teach receiving input data that includes seismic borehole image data for interpretation analysis) to extract a natural fracture type, a dip angle, a dip azimuth, and/or an intensity at well level within the naturally fractured reservoir (Lejri paragraph [0116] teaches at inversion analysis to extract at least the fracture types, and paragraph [0055] teaches defining (extracting) a dip magnitude angle and a dip azimuth).
In regards to claim 11, Lejri teaches the method wherein the borehole image is a seismic image or a resistive image of the naturally fractured reservoir (Lejri paragraph [0053] teaches wherein the borehole image is at least a current-based (resistive V/R) image of the naturally fractured reservoir).
In regards to claim 12, Lejri teaches the method wherein the one or more geological analyses includes calculating structural stress regimes within the naturally fractured reservoir through determination of principal stresses within the naturally fractured reservoir (Lejri paragraphs [0065]-[0067] teach calculating structural tectonic stress regimes through the determination of principle stresses).
In regards to claim 13, Lejri teaches the method wherein elastic properties, a rock strength, and a pore pressure within a poro-elasticity stress model is used to determine the principal stresses (Lejri paragraph [0138] teaches obtaining linear elasticity (elastic properties), paragraph [0069] teaches obtaining a tensile strength of rock for comparison to a tensile stress, paragraph [0052] teaches obtaining pore pressure, and paragraph [0027] teaches where where the combination of various types of geological data is used with fundamental principles of physics that govern rock deformation within a stress modeling framework (stress model) to determine stresses (including principal stresses); paragraph [0051] teaches where the model accounts for porosity distributions in the basin and petroleum systems).
In regards to claim 14, Lejri teaches the method wherein the one or more geological analyses includes generating a structural framework of faults and surfaces to define a volume-based model for identification of paleo-stress regions therein (Lejri paragraphs [0023]-[0025] teach using a geomechanical (structural) framework of gridding subterranean volumes including faults and surfaces to define a volume-based model for identifying three-dimensional stress fields (stress regions) therein; Lejri paragraph [0030] defines paleostress as one of the types of stress).
In regards to claim 15, Lejri teaches the method wherein the paleo-stress regions are identified based on maximum horizontal stress direction trends (Lejri paragraphs [0067] and [0140] teach determining a stress domain region based on variation trends of the maximum principal horizontal stress direction defined clockwise according to the North; Lejri paragraph [0030] defines paleostress as one of the types of stress) and sub-seismic lineament property trends (Lejri paragraphs [0178]-[0179] teach identifying trends using the boundary elements (sub-seismic lineaments) such as elements across which a discontinuity in displacement is approximately constant, in order to identify a closed surface region from the superposition of the elements).
In regards to claim 16, Lejri teaches a computer-implemented method (Lejri paragraph [0003] teaches a method carried out by a computing system (computer)) comprising:
receiving a static fracture model and input data for a naturally fractured reservoir (Lejri paragraph [0025] teaches receiving steady-state (static) modeling equations for modeling an oil and gas field, where paragraph [0027] teaches application of modeling to subseismic fractures in a reservoir; Lejri paragraph [0035] teaches also receiving input information based on one or more attributes);
obtaining changes in natural fracture orientations within the naturally fractured reservoir based on the static fracture model and the input data (Lejri paragraphs [0027] and [0035] teach obtaining orientations of subseismic fractures within the reservoir based on the modeling and input data; Lejri paragraph [0049] teaches tracking for time-based changes in the orientation of faults (including fractures) described in coordinate systems);
obtaining variations of maximum horizontal stress directions within the naturally fractured reservoir based on principal stresses therein (Lejri Fig. 3 and paragraphs [0066]-[0067] teach obtaining variations (represented by an ellipsoid) of the maximum horizontal stress directions based on the principal stresses therein);
determining one or more paleo-stress regions based on the changes in natural fracture orientations and the variations of maximum horizontal stress directions (Lejri paragraphs [0067] and [0140] teach determining a stress domain region based on changes in the fracture orientations (corresponding to different types of faults) and variations of the maximum principal horizontal stress direction defined clockwise according to the North; Lejri paragraph [0030] defines paleostress as one of the types of stress); and
history matching each determined paleo-stress region to a known quantity of dynamic response based upon a known dynamic response, a historical data set, or a plurality of assumptions for flow characteristics (Lejri paragraphs [0145] and [0147] teach performing history matching of the predicted (identified) paleostress fracture region to one or more historically observed fracture region data sets, where paragraph [0103] teaches that the data subsets are analyzed for the dynamics of faulting (as a type of response)).
In regards to claim 17, Lejri teaches the method further comprising:
simulating flow within the naturally fractured reservoir to obtain dynamic simulation responses within the static fracture model (Lejri paragraphs [0062] and [0116] teach simulating fluid flow within the reservoir using hydrodynamic potential of fluid to obtain dynamic simulation responses) via history matched paleo-stress regions (Lejri paragraph [0147] teaches carrying out the a forward simulation via history matching to original fracture data from a group of fractures (in a paleo-stress region).
In regards to claim 18, Lejri teaches the method wherein, the dynamic simulation responses are output to well planning, gas injection, or drilling operation software for optimization of extraction operations in the naturally fractured reservoir (Lejri paragraph [0116] teaches where the outputs of the dynamic simulations are used in planning, performing, etc. of one or more field operations).
In regards to claim 19, Lejri teaches the method further comprising:
causing the dynamic simulation responses within the static fracture model to be displayed on an output device (Lejri Fig. 1 and paragraphs [0041]-[0042] and [0208] teach causing the simulation responses to be displayed on a user interface output device).
In regards to claim 20, Lejri teaches the method wherein the changes in natural fracture orientations (Lejri paragraphs [0027] and [0035] teach obtaining orientations of subseismic fractures within the reservoir based on the modeling and input data; Lejri paragraph [0049] teaches tracking for time-based changes in the orientation of faults (including fractures) described in coordinate systems) and variation of maximum horizontal stress directions (Lejri Fig. 3 and paragraphs [0066]-[0067] teach obtaining variations (represented by an ellipsoid) of the maximum horizontal stress directions) are determined based on properties extracted using an analysis of seismic discontinuities (Lejri paragraph [0024] teaches determining properties using an analysis of a model for modeling discontinuities), an interpretation of a borehole image (Lejri paragraph [0059] teaches sedimentological interpretations from borehole images to determine dips for use in interpreting sand body orientation), a calculation of structural stresses (Lejri paragraph [0065] teaches calculation of structural stresses at a point in a solid body), and/or a generation of a structural framework (Lejri paragraphs [0024] teach generation of a structural framework to describe angular dislocations for modeling three-dimensional stress fields).
Pertinent Art
6. Applicants are directed to consider additional pertinent prior art included on the Notice of References Cited (PTOL 892) attached herewith. The Examiner has pointed out particular references contained in the prior art of record within the body of this action 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. Applicant, in preparing the response, should consider fully the entire reference as potentially teaching all or part of the claimed invention, as well as the context of the of the passage as taught by the prior art or disclosed by the Examiner. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
B. Amer et al. (US Pat. Pub. 2016/0266268) discloses Determining a Fracture Type Using Stress Analysis. C. Ouenes (US Pat. Pub. 2017/0051598) discloses System for Hydraulic Fracturing Desing and Optimization in Naturally Fractured Reservoirs. D. Umholtz et al. (US Pat. Pub. 2017/0132339) discloses System for Predicting Induced Seismicity Potential Resulting from Injection of Fluids in Naturally Fractured Reservoirs. E. Sung (US Pat. Pub. 2019/0114352) discloses Paleo Fossil and Sedimentary Structure Data Mining and Datum for Biostratigraphy.
Conclusion
7. Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAUL D LEE whose telephone number is (571)270-1598. The examiner can normally be reached on M to F, 9:30 am to 6 pm.
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, Arleen Vazquez can be reached at 571-272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PAUL D LEE/Primary Examiner, Art Unit 2857 4/24/2026
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