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 .
DETAILED ACTION
1. The amendment filed on 04/15/2026 has been received and considered. Claims 1-20 are presented for examination.
Claim Objections
2. Claim 12-13 and 18, and 20 are objected to because of the following informalities:
As per Claim 11, it recites “wherein the process is performed wherein the input data includes at least one seismic survey.” which would be better as “wherein the input data includes at least one seismic survey.” as it recites the double subordinator “wherein…wherein”.
As per Claim 12, it recites “wherein the process is performed such that the input data includes core sample data.” which would be better as “wherein the input data includes at least one seismic survey.” as it recites the double subordinator “wherein…wherein”.
As per Claim 18, it recites the limitation “the field-based values” which would be better as “the filed-based distributions” to avoid a potential antecedent base issue.
As per Claim 20, it recites the limitation “viscosity biomarker data” which would be better as “viscosity, biomarker data”.
Appropriate correction is required.
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.
3. Claims 1-9 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.
As per Claim 1, it recites the limitation “within a threshold percentage of field-measured properties” in line 24 which is unclear what the limitation refers. In particular, percentage of what? Is it percentage of error, difference or per-property percentage?
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries 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.
4. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kauerauf et al. (US 20190293835 A1) and further in view of Gurpinar et al. (US 7953585 B2).
As per Claim 1, 10 and 17, Kauerauf et al. teaches (Claim 1) a method of evaluation of a geological stratum through simulation of a fluid charge (Abstract), the method comprising:
(Claim 10) an article of manufacture configured to store a set of instructions performed on a computer, the article of manufacture having a non-volatile memory, the set of instructions comprising a method of evaluation of a geological stratum through simulation of a fluid charge (Abstract, Fig. 1 &10), the method comprising:
(Claim 17) a method for conducting hydrocarbon recovery operations through simulation of a fluid charge (Abstract), comprising:
performing a process including:
(Claim 1, 10 and 17) obtaining input data for the geological stratum ([0076]-[0079] “input data for RFG model 402 ”);
obtaining field-based fluid distributions for a wellsite within the geological stratum, the field-based fluid distributions including measured fluid distributions from downhole fluid analysis and geochemical analysis of fluid samples (Fig. 10, [0067], [0076]-[0079], [0085], [0095] “geochemical reactions such as oil cracking and thermochemical sulfate reduction, biodegradation, biological sulfate reduction, asphaltene precipitation”; “For modeling processes within RFG model 402 by RFG simulator 404, in and outflow of energy and/or fluid (water, hydrocarbons, non-hydrocarbons such as nitrogen, carbon dioxide, etc.), masses, pressures and/or mechanical constraints (e.g., outer stresses from tectonics), may also be used as input data.”; “Resulting fluid distributions generated by RFG simulator 404 may also be used for calibration purposes, e.g., by a calibration module 422, which compares simulated fluid distributions with measurement data 424, e.g. fluid samples from downhole fluid analysis (DFA).”; “DFA data”);
preparing at least one of: an assumed reservoir architecture, a well placement, a well completion technique, a well stimulation strategy and a well production plan for the wellsite within the geological stratum (Fig. 6 & 8, [0074]-[0079], [0093]-[0095] “preparing input for an RFG simulation by RFG simulator 404. First, in blocks 452 and 454, a region of interest is selected and cut out of the integrated subsurface model and the cut out region of interest is refined to the desired scale for the RFG simulation, e.g., using refinement module 418 of FIG. 6. Next, in block 456, present day data is accessed and extrapolated over geological time (e.g., using extrapolation module 412 of FIG. 6) to scale the present day properties to the spatial resolution and timescale to be used for the RFG simulation.”, “FIG. 9 illustrates a sequence of operations 470 for running an RFG simulation, e.g., using RFG simulator 404 of FIG. 6. In block 472, a timescale and resolution is applied to configure the duration of time and the resolution to use for the simulation”, Examiner Note: building a reservoir architecture model for a region of interest at the spatial resolution corresponds to “preparing an assumed reservoir architecture”);
performing a (claim 17) computer-based (Claim 1, 10 and 17) dynamic simulation of a charge process for the geological stratum for the at least one of: the assumed reservoir architecture, the well placement, the well completion technique, the well stimulation strategy, or the well production plan for the wellsite to produce a result, the dynamic simulation being carried out to simulate charging of hydrocarbon fluids into the reservoir over thousands to millions of years, and, as fluids enter the reservoir, the fluids mix with previously-charged fluids, inducing both convective and diffusive mixing (Fig. 9, [0067], [0074]-[0082], [0084], [0094] “RFG modeling may be based upon both intermediate timescales (e.g., in terms of thousands of years, such as about 1000 to about 10,000,000 years), and intermediate dimensions”, “RFG simulator 404 may model any combination of the following processes: diffusion of fluid compounds, e.g. compositional grading; fluid phase separation (PVT); separate phase flow, e.g. Darcy flow; biodegradation and biological sulfate reduction; secondary chemical cracking of oil; asphaltene flocculation; tar mat formation; pressure, temperature and stress variations; gas hydrates (fluid solid phase separation); flow baffling up to compartmentalization; thermochemical sulfate reduction; rock compaction, fracturing and rock failure; fluid rock interactions, e.g. cementation, dolomitization, smectite to illite transformations; magmatic intrusions, e.g. heat impact; ground water flow; convection; CO.sub.2 sequestration; and/or impact of nuclear waste disposal on the geological environment, e.g. diffusion of radioactive compounds.”, “RFG simulation by RFG simulator 404 results in… hydrocarbon amounts accessible for production.”, “FIG. 9 illustrates a sequence of operations 470 for running an RFG simulation, e.g., using RFG simulator 404 of FIG. 6. In block 472, a timescale and resolution is applied to configure the duration of time and the resolution to use for the simulation”, Examiner Note: running a computer simulation on the RFG model over a geological timescale and at a reservoir-scale spatial resolution to produce fluid distribution results corresponds to “performing a computer-based dynamic simulation/dynamic simulation”.), (Claim 17) the dynamic simulation of the charge process being used to infer reservoir-scale connectivity (Examiner note- it is interpreted as intended use as the claim fails to define he function “being used to infer” thus no patentable weight given to the limitation);
comparing the result to the field-based fluid distributions for the wellsite, the comparing the result including comparing fluid distribution characteristics including one or more of: composition, asphaltene content, gas-to-oil ratio, isotope ratios, or other geochemical metrics (Fig. 10, [0082], [0085], [0095], “compositional grading; … asphaltene flocculation; … biodegradation and biological sulfate reduction; secondary chemical cracking of oil; … thermochemical sulfate reduction”, “Resulting fluid distributions generated by RFG simulator 404 may also be used for calibration purposes, e.g., by a calibration module 422, which compares simulated fluid distributions with measurement data 424, e.g. fluid samples from downhole fluid analysis (DFA).”, “Block 484 then accesses fluid distribution data from the RFG model, and block 486 performs a comparison between this data, e.g., using various model validation techniques ”);
(Claim 1) ending the process when the comparing of the result to the field-based fluid distributions for the wellsite is below a … threshold value the threshold value including model calculation results being within a threshold percentage of field-measured properties ([0054], [0085], [0095] “These measurements may be analyzed to better define the properties of the formation(s) and/or determine the accuracy of the measurements and/or for checking for errors.”, “In case of not matching measurement data with a sufficient degree of accuracy, uncertain model parameters may be adjusted to achieve a better match after re-running the simulation. A calibration workflow may allow for adjusting the RFG model iteratively, achieving high accuracy for matching available data”, "Block 488 determines if the model is acceptable, i.e., is sufficiently accurate given the actual measurement data. If so, the sequence of operations is complete”: Examiner Note - a binary acceptance test that terminates an iterative calibration loop; the limitation “within a threshold percentage of field-measured properties” is supported under inherency on Kauerauf's binary block 488 acceptance test, which inherently requires a quantitative criterion, and where percentage tolerance is the canonical engineering form of that criterion; binary block 488 acceptance test inherently requires a quantitative criterion to render the binary decision);
(Claim 10) ending the process when the comparing of the result to the field-based fluid distributions for the wellsite is below a … threshold value ([0054], [0085], [0095] “These measurements may be analyzed to better define the properties of the formation(s) and/or determine the accuracy of the measurements and/or for checking for errors.”, “In case of not matching measurement data with a sufficient degree of accuracy, uncertain model parameters may be adjusted to achieve a better match after re-running the simulation. A calibration workflow may allow for adjusting the RFG model iteratively, achieving high accuracy for matching available data”, "Block 488 determines if the model is acceptable, i.e., is sufficiently accurate given the actual measurement data. If so, the sequence of operations is complete”),
(Claim 17) ending the process when the comparing of model result to the field-based fluid distributions for the wellsite is below a … threshold value to produce a final result ([0054], [0085], [0095] “These measurements may be analyzed to better define the properties of the formation(s) and/or determine the accuracy of the measurements and/or for checking for errors.”, “In case of not matching measurement data with a sufficient degree of accuracy, uncertain model parameters may be adjusted to achieve a better match after re-running the simulation. A calibration workflow may allow for adjusting the RFG model iteratively, achieving high accuracy for matching available data”, "Block 488 determines if the model is acceptable, i.e., is sufficiently accurate given the actual measurement data. If so, the sequence of operations is complete”);
revising the at least one of: the reservoir architecture, the well placement, the well completion technique, the well stimulation strategy, or the well production plan for the wellsite and the dynamic simulation of the charge process and returning to perform another dynamic simulation and comparing the result to the field-based fluid distributions for the wellsite until the ending of the method process ([0085], [0095] “In case of not matching measurement data with a sufficient degree of accuracy, uncertain model parameters may be adjusted to achieve a better match after re-running the simulation. A calibration workflow may allow for adjusting the RFG model iteratively, achieving high accuracy for matching available data”, "Block 488 determines if the model is acceptable, i.e., is sufficiently accurate given the actual measurement data. If so, the sequence of operations is complete”);
using the revised at least one of: the reservoir architecture, the well placement, the well completion technique, the well stimulation strategy, or the well production plan to drill a well, control a production well, or control an injection well at the wellsite ([0096] “the results of the simulation may also be used in the performance of an oilfield operation, e.g., to drill a well, determine a field development plan, to configure a surface network, to control a production and/or injection well, etc.”).
Kauerauf et al. fails to teach exility a user-defined.
Gurpinar et al. teaches (Claim 1, 10 and 17) a user-defined (Fig. 11A-B, Col. 9 lines 51-67m Col. 10 lines 1-3, “This `iterative process` (of running through history, comparing to measured data, and adjusting the model properties) continues until you have what you feel is a satisfactory representation of how the reservoir has actually performed. At that point, since you have now produced a `history calibrated model`, branch off from the `model reproduces history` decision triangle 42a13 to the `history calibrated model` block 42a16.”). In particular, Gurpinar's "what you feel is a satisfactory" corresponds to the claimed limitation “user-defined threshold value” criterion as the user i.e., the engineer running the calibration defines what counts as satisfactory; Gurpinar's contribution is the user-controllability dimension.
Kauerauf et al. and Gurpinar et al. are analogous art because they are both related to a method for reservoir operation development.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate Gurpinar et al. into Kauerauf et al.’s invention to properly allocate resources to assure that the reservoir meets its potential and to make proper reservoir management decisions (Gurpinar et al.: Col. 1 lines 25-40, col. 8 lines 32-37).
As per Claim 2 and 11, Kauerauf et al. teaches wherein the input data includes at least one seismic survey ([0075] “seismic surveys with interpretation”).
As per Claim 3 and 12, Kauerauf et al. teaches wherein the input data includes at least one of; geology logs or petrophysical logs ([0075], [0077] “well data (e.g. well logs)”, “subsurface maps of geological formations…faults… rock properties”).
As per Claim 4 and 13, Kauerauf et al. teaches wherein the input data includes core sample data ([0075], [0085], [0095] “fluid samples from downhole fluid analysis (DFA)”).
As per Claim 5 and 14, Kauerauf et al. teaches wherein the input data includes fluid sample data ([0055], [0060], [0077], “core sample data measured from a core sample of the formation”, “rock properties… such as rock type (e.g., sandstone, shale, salt, limestone, etc.), porosity, shale content, etc. Fault properties, e.g., shale gouge content, may also be used””).
As per Claim 6 and 15, Kauerauf et al. teaches wherein the input data includes pressure test data ([0056], [0078] “pressures… may also be used as input data”).
As per Claim 7 and 16, Kauerauf et al. teaches wherein the charge process occurs over a period of fluid exposure to geological processes ([0067], [0081]-[0082 “model varying fluid compositions within a reservoir or an accumulation but on geological timescales…. a geological timescale of greater than about 100 years, e.g., between about 100 and about 100 million years, may be used.”).
As per Claim 8, Kauerauf et al. teaches further comprising saving a final reservoir architecture in a non-volatile memory (Fig. 1, [0009]-[0010], [0094], [0096] “results may then be output to the integrated subsurface model in block 478”, “block 508 the results of the simulation are output, e.g., to the integrated subsurface model, to a separate simulation output, or to a visualization module for display and analysis.”).
As per Claim 9, Kauerauf et al. teaches further comprising printing characteristics of a final reservoir architecture ([0096] “the results of the simulation may also be used in the performance of an oilfield operation, e.g., to drill a well, determine a field development plan, to configure a surface network, to control a production and/or injection well, etc.”).
As per Claim 18, Kauerauf et al. teaches wherein the field-based values are used in at least one of field development planning, well placement and construction, wellbore completion, wellbore stimulation, or wellbore production activities ([0025], [0063]-[0067], [0070], [0074], [0096] “early development workflows in the oil & gas industry”, “block 508 the results of the simulation are output, e.g., to the integrated subsurface model, to a separate simulation output, or to a visualization module for display and analysis.”).
As per Claim 19, Kauerauf et al. teaches wherein the obtaining input data includes obtaining petrophysics data ([0077]-[0078] [0088], [0097] “input data for RFG model 402 may include at least subsurface maps of geological formations… faults … rock properties describing the volumes between mapped surfaces and faults may be used, such as rock type (e.g., sandstone, shale, salt, limestone, etc.), porosity, shale content, etc. Fault properties, e.g., shale gouge content, may also be used”, “subsurface formation data, which may include measurement data, rock properties, subsurface maps, fault maps,”).
As per Claim 20, Kauerauf et al. teaches wherein the obtaining input data includes obtaining one or more of: fluid composition data, optical density data, gas to oil gas-to-oil ratio data, mass density data, viscosity biomarker data, or isotope pressure data ([0047], [0049], [0055], [0064], [0077]-[0082], [0085] “a graph of the density, porosity, permeability, or some other physical property of the core sample over the length of the core. Tests for density and viscosity may be performed on the fluids in the core at varying pressures and temperatures.”, “fluid compositions within a reservoir”, “diffusion of fluid compounds, e.g. compositional grading”, “in and outflow of energy and/or fluid (water, hydrocarbons, non-hydrocarbons such as nitrogen, carbon dioxide, etc.), masses, pressures and/or mechanical constraints (e.g., outer stresses from tectonics), may also be used as input data.”, “measurement data 424, e.g. fluid samples from downhole fluid analysis (DFA)”).
Response to Arguments
5. Applicant's arguments filed on 04/15/2026 have been fully considered but they are not persuasive.
Examiner respectfully withdraws Objection to Drawing in view of the amendment and/or applicant’s arguments.
Examiner respectfully withdraws Claim Rejections - 35 USC § 101 in view of the amendment and/or applicant’s arguments.
Applicant have argued that:
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It is noted that Examiner also noted that further search and consideration would be necessary when amendments are formally filed and no agreement was reached. Furthermore, it is noted that independent claim 10 and 17 does not recite the limitans “the threshold value including model calculation results being within a threshold percentage of field-measured properties” as recited in amended Claim 1.
Applicant have argued that:
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It is noted that is Examiner’s relies on the teaching in Gurpinar et al. to teach the user-controllability dimension while Kauerauf et al. is relied upon for a teaching of the limitation of “dynamic simulation of a charge process … simulating charging of hydrocarbon fluids into the reservoir over thousands to millions of years”, “comparing fluid distribution characteristics including one or more of: composition, asphaltene content, gas-to-oil ratio, isotope ratios, or other geochemical metrics”, and “using the revised reservoir architecture, well placement, well completion technique, well stimulation strategy, or well production plan to drill a well, control a production well, or control an injection well”.
Gurpinar et al.'s "what you feel is a satisfactory representation" criterion is itself a user-defined threshold under BRI because the user (the engineer running the calibration) defines what counts as satisfactory, which is the threshold. Moreover, Kauerauf et al. independently teaches threshold-based termination ([0085] “In case of not matching measurement data with a sufficient degree of accuracy”; [0095] “determines if the model is acceptable, i.e., is sufficiently accurate given the actual measurement data” block 488). Gurpinar's contribution is the user-controllability dimension, not the threshold-based-termination concept itself.
As rejected above, Kauerauf et al. teaches:
“dynamic simulation of a charge process … simulating charging of hydrocarbon fluids into the reservoir over thousands to millions of years”: (Fig. 9, [0067], [0074]-[0082], [0084], [0094] “RFG modeling may be based upon both intermediate timescales (e.g., in terms of thousands of years, such as about 1000 to about 10,000,000 years), and intermediate dimensions”, “RFG simulator 404 may model any combination of the following processes: diffusion of fluid compounds, e.g. compositional grading; fluid phase separation (PVT); separate phase flow, e.g. Darcy flow; biodegradation and biological sulfate reduction; secondary chemical cracking of oil; asphaltene flocculation; tar mat formation; pressure, temperature and stress variations; gas hydrates (fluid solid phase separation); flow baffling up to compartmentalization; thermochemical sulfate reduction; rock compaction, fracturing and rock failure; fluid rock interactions, e.g. cementation, dolomitization, smectite to illite transformations; magmatic intrusions, e.g. heat impact; ground water flow; convection; CO.sub.2 sequestration; and/or impact of nuclear waste disposal on the geological environment, e.g. diffusion of radioactive compounds.”, “RFG simulation by RFG simulator 404 results in… hydrocarbon amounts accessible for production.”, “FIG. 9 illustrates a sequence of operations 470 for running an RFG simulation, e.g., using RFG simulator 404 of FIG. 6. In block 472, a timescale and resolution is applied to configure the duration of time and the resolution to use for the simulation”, Examiner Note: running a computer simulation on the RFG model over a geological timescale and at a reservoir-scale spatial resolution to produce fluid distribution results corresponds to “performing a computer-based dynamic simulation/dynamic simulation”.);
“comparing fluid distribution characteristics including one or more of: composition, asphaltene content, gas-to-oil ratio, isotope ratios, or other geochemical metrics” (Fig. 10, [0082], [0085], [0095], “compositional grading; … asphaltene flocculation; … biodegradation and biological sulfate reduction; secondary chemical cracking of oil; … thermochemical sulfate reduction”, “Resulting fluid distributions generated by RFG simulator 404 may also be used for calibration purposes, e.g., by a calibration module 422, which compares simulated fluid distributions with measurement data 424, e.g. fluid samples from downhole fluid analysis (DFA).”, “Block 484 then accesses fluid distribution data from the RFG model, and block 486 performs a comparison between this data, e.g., using various model validation techniques ”), and
“using the revised reservoir architecture, well placement, well completion technique, well stimulation strategy, or well production plan to drill a well, control a production well, or control an injection well” ([0096] “the results of the simulation may also be used in the performance of an oilfield operation, e.g., to drill a well, determine a field development plan, to configure a surface network, to control a production and/or injection well, etc.”).
Thus, 103 rejection maintains for the reason set forth the above.
Conclusion
6. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
7. Any inquiry concerning this communication or earlier communications from the examiner should be directed to EUNHEE KIM whose telephone number is (571)272-2164. The examiner can normally be reached Monday-Friday 9am-5pm ET.
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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.
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EUNHEE KIM
Primary Examiner
Art Unit 2188
/EUNHEE KIM/Primary Examiner, Art Unit 2188
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