CTNF 18/185,768 CTNF 91226 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 07-30-03-h AIA Claim Interpretation 07-30-03 AIA The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. 07-30-05 The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph: (A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function; (B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and (C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. 07-30-06 This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a data receiver”, “a variable normalizer”, and “an efficiency evaluator” from claim 8, “a hydraulic fracturing operations controller” from claim 9, “a modeling tool” from claim 12, and “a variable normalizer” from claim 15. Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Specifically, the rejected claims recite a “machine-readable storage medium” which reads on signals per se. Under the broadest readable interpretation, computer-readable medium encompasses program code transmitted via optical, electromagnetic, and infrared subject matter, which may read on a signal, and therefore constitutes non-statutory subject matter. The Examiner recommends that the Applicant amend the rejected claims to recite “non-transitory machine-readable storage medium.” Claims 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (mental processes and mathematical relationships) without significantly more. Claim 1 recites: A machine-readable storage medium having stored thereon a computer program for evaluating a perforation efficiency, the computer program comprising a routine of set instructions for causing the machine to perform the steps of: (invoking generic computer components merely as tools to carry out the claimed tasks, equivalent to mere instructions to apply an exception as per MPEP 2106.05(f)) receiving a plurality of flow variables for a perforation design; (insignificant extra-solution activity in the form of mere data gathering as per MPEP 2106.05(g), and the variables are numerical data values that are later used to perform mathematical calculations) normalizing the plurality of flow variables into a stimulation treatment deliverability index; (normalization is a mathematical calculation/operation, and it is being performed here on the numerical data, falling within the scope of mathematical relationships) assessing a perforation efficiency for the perforation design using the stimulation treatment deliverability index; (a percentage is a numerical value, and the assessment is made based on numerical metrics from the previously calculated normalized value, also falling within the scope of mathematical relationships. Alternatively, a person could mentally observe the stimulation treatment deliverability index from the prior step and then make an evaluation to determine the resulting percent for efficiency, falling within the scope of mental processes) generating instructions for hydraulic fracturing operations based upon the perforation efficiency for the perforation design; and (A person can mentally observe the percentage from the prior step, evaluate it, and make a judgement based on their professional expertise for instructions appropriate to execute a fracture operation. Note that performing the fracture operation is not positively recited, only generating instructions. Any link to hydraulic fracturing here is merely generally linking the use of the exception to that technical field, as per MPEP 2106.05(h)) incorporating the instructions generated into a recommendation of one or more perforation designs for ongoing or future hydraulic operations. (providing a recommendation here amounts to insignificant extra-solution activity in the form of selecting a particular data source or type of data to be manipulated, as per MPEP 2106.05(g).) This judicial exception is not integrated into a practical application. In particular, the claim only recites the following additional elements: 1) mere instructions to apply the exception using generic computer components (the computer/instructions), 2) generally linking the use of the exception to the technical field of hydraulic fracturing, and 3) insignificant extra-solution activity in the form of more data gathering (receiving data) and selecting a particular data source or type of data to be manipulated (generating a recommendation). The computer/instructions are recited at a high-level of generality (i.e., as a generic computer/instructions performing a generic computer function of executing calculations and storing data) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception cannot integrate a judicial exception into a practical application. The specification that data is received and a recommendation is generated is only tangentially linked to the calculation and analysis steps, and does not meaningfully limit the claim. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer/instructions to perform the claimed steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself. The addition of insignificant extra-solution activity does not amount to an inventive concept. The claim is not patent eligible. Dependent Claim 2 includes “modifying a planned fracturing operation” in the scope of “performing one or more hydraulic fracturing operations”, and that this falls within the scope of mental processes as a person can modify a plan mentally via evaluation and judgement. Dependent claims 4 and 8 recite visualization/display, but this amounts merely to further extra-solution activity in the form of selecting a particular data source or type of data to be manipulated in the same manner as the recommendation of claim 1. Aside from the above, the dependent claims 2-8 recite only features that fall within the scope of the above analysis of claim 1, and are rejected under the same grounds. Claim 9 is, from an eligibility standpoint, substantially similar to claim 1, and is rejected under the same grounds as those set forth above for claim 1. Dependent claims 10-14 are rejected under the same grounds as claim 1 above and specifically for claim 14, also the rationale discussed above for claims 4 and 8. Claim 15 does not recite (i.e. is not directed to) a judicial exception and is eligible. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 1-8, 10-11, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Mondal (Mondal, S., Zhang, M., Huckabee, P., Ugueto, G., Jones, R., Vitthal, S., ... & Sharma, M. (2021, April). Advancements in step down tests to guide perforation cluster design and limited entry pressure intensities-Learnings from field tests in multiple basins. In SPE hydraulic fracturing technology conference and exhibition (p. D021S006R002). SPE.) in view of Jin (US 20210388718 A1) and Heidari (US 20210087925 A1) . Regarding Claim 1: Mondal teaches: receiving a plurality of flow variables for a perforation design; (p.4, From the estimated ΔPperf, the number of active perforations (N) is calculated using Eq. 3.; p. 9, The perforation pressure drop is calculated using: ... The near-wellbore pressure drop is modelled using this equation: ... where knwbt and β are assumed to change linearly with the cumulative pumped proppant mass into this completion stage during the treatment.) normalizing the plurality of flow variables into a stimulation treatment deliverability index; (p.4, ... In a following section, the theoretical derivation of β will be presented for different fracture geometries and flow regimes ... By fitting the cumulative bottomhole pressure drop as a function of rate (Eq. 2), perforation friction and near-wellbore tortuosity can be quantitatively estimated.) assessing a perforation efficiency for the perforation design using the stimulation treatment deliverability index; (Abstract, The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity) Mondal does not teach in particular, but Jin teaches: generating instructions for hydraulic fracturing operations based upon the perforation efficiency for the perforation design; and (Abstract, to determine borehole perforation cluster efficiency ... These results can be used to improve well completion and stimulation designs; ¶2 perforation efficiency diagnosis using distributed sensing measurements; ¶7 the relation between perforation cluster efficiency and hydraulic fracturing designs can be established in the same stimulation well to accelerate hydraulic fracturing design optimization in the reservoir development.; examiner notes that instructions for hydraulic fracturing operations are being interpreted to include a hydraulic fracture design, such as the one optimized by the reference in the above cited sections.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the efficiency analysis-based fracturing design optimization of Jin in the perforation cluster design and analysis system of Mondal, in order to improve well completion and stimulation designs, increase field production, and/or decrease costs. (Jin, Abstract). Mondal does not teach in particular, but Heidari teaches: incorporating the instructions generated into a recommendation of one or more perforation designs for ongoing or future hydraulic operations. (¶27 Use of the model to predict aBased on the objective function (e.g., maximizing production), a most optimal scenario (e.g., a pumping schedule) given the constraints from a pool of top scenarios for a next stage and treatment may be recommended in real-time for a hydraulic fracturing job. As an example, the real-time design optimization model may recommend a change in proppant concentration from a first treatment to a second treatment based on real-time data collected on the location during the job.nd optimize a fracturing job ... the model may be based on additional well characteristics ... perforation cluster spacing; ¶27 The model may be used to predict and track KPIs of the well in real-time during the fracturing job and provide recommendations to optimize the KPIs for the fracturing job.; ¶40 next stage and treatment may be recommended in real-time for a hydraulic fracturing job.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 2: Mondal does not teach in particular, but Heidari teaches: performing one or more hydraulic fracturing operations using the one or more perforation designs of the recommendation, and (¶27 The solutions discussed herein may use a data-driven mathematical and statistical model based on time-series data to predict and optimize fracturing jobs in real-time by performing operations that optimize key performance indicators including, but not limited to maximizing well production, stimulated reservoir volume, NPV, minimizing job time, or minimizing cost.) wherein the one or more hydraulic fracturing operations comprise initiating a fracturing operation, modifying a planned fracturing operation, or any combination thereof. (¶40 Based on the objective function (e.g., maximizing production), a most optimal scenario (e.g., a pumping schedule) given the constraints from a pool of top scenarios for a next stage and treatment may be recommended in real-time for a hydraulic fracturing job. As an example, the real-time design optimization model may recommend a change in proppant concentration from a first treatment to a second treatment based on real-time data collected on the location during the job ... Alternatively, the scenario may be automatically selected and implemented; ¶2 When these events occur, an on-location engineer makes decisions to control the job and fracture the well; ¶14 real-time hydraulic fracture control; ¶80 the hydraulic fracturing job optimization system 201 can implement the optimized job design for the particular hydraulic fracturing well.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 3: Mondal teaches: wherein the plurality of flow variables comprises a treatment pressure, a pump rate, a friction reducer concentration, a pressure derivative, or any combination thereof. (p. 9, The perforation pressure drop is calculated using: ... The near-wellbore pressure drop is modelled using this equation: ... where knwbt and β are assumed to change linearly with the cumulative pumped proppant mass into this completion stage during the treatment.; examiner notes that these fall within the scope of treatment pressure; Abstract, The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity; examiner notes that a pressure rate is equivalent to the first derivative of pressure with respect to time.) Regarding Claim 4: Mondal teaches: calculating a normalized pressure derivative via the plurality of flow variables, (p.4, ... In a following section, the theoretical derivation of β will be presented for different fracture geometries and flow regimes ... By fitting the cumulative bottomhole pressure drop as a function of rate (Eq. 2), perforation friction and near-wellbore tortuosity can be quantitatively estimated.) wherein the normalized pressure derivative is used in visualizing pressure change trends between a plurality of perforation designs. (p.3, shows the pressure-rate response from a post-frac SDT consisting of 5 steps.; p.4, The instantaneous pressure-rate response is assumed because of flow-dependent or frictional pressure drop in the system, which consists of friction in the wellbore, across perforations and near-wellbore tortuosity (Eq. 1); Fig. 3, Pressure-rate response from pre- and post-frac SDT in 9 stages of cSPE well.; see also Heidari ¶49 "the hydraulic fracturing job optimization system 201 can also include a display device 210 for displaying data and graphical elements such as images, videos, text, simulations" and note it would be obvious to display the above cited pressure-rate data using Heidari's display device, though Mondal is maintained to disclose the limitation regardless by virtue of its figures providing such displays.) Regarding Claim 5: Mondal teaches: wherein the plurality of flow variables are received from one or more hydraulic fracturing models, from previously defined default values, or a combination thereof. (p.3, The calibrated model is used to optimize perforation cluster designs for various scenarios and the sensitivity of this optimal design is checked against the uncertainties in near-wellbore complexity, perforation erosion, critical proppant bridging concentration, minimum horizontal stress, fracture toughness, etc. ) Regarding Claim 6: Mondal does not teach in particular, but Jin teaches: assessing a viability of the perforation design from the one or more hydraulic fracturing models; and (Abstract, to determine borehole perforation cluster efficiency ... These results can be used to improve well completion and stimulation designs; ¶2 perforation efficiency diagnosis using distributed sensing measurements; ¶7 the relation between perforation cluster efficiency and hydraulic fracturing designs can be established in the same stimulation well to accelerate hydraulic fracturing design optimization in the reservoir development.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the efficiency analysis-based fracturing design optimization of Jin in the perforation cluster design and analysis system of Mondal, in order to improve well completion and stimulation designs, increase field production, and/or decrease costs. (Jin, Abstract). Mondal does not teach in particular, but Heidari teaches: recommending the perforation design within a planned well. (¶27 Use of the model to predict aBased on the objective function (e.g., maximizing production), a most optimal scenario (e.g., a pumping schedule) given the constraints from a pool of top scenarios for a next stage and treatment may be recommended in real-time for a hydraulic fracturing job. As an example, the real-time design optimization model may recommend a change in proppant concentration from a first treatment to a second treatment based on real-time data collected on the location during the job.nd optimize a fracturing job ... the model may be based on additional well characteristics ... perforation cluster spacing; ¶27 The model may be used to predict and track KPIs of the well in real-time during the fracturing job and provide recommendations to optimize the KPIs for the fracturing job.; ¶40 next stage and treatment may be recommended in real-time for a hydraulic fracturing job.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 7: Mondal teaches: wherein the perforation efficiency is a first perforation efficiency, and (Abstract, The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity) normalizing the second plurality of flow variables into a second stimulation treatment deliverability index; (p.4, ... In a following section, the theoretical derivation of β will be presented for different fracture geometries and flow regimes ... By fitting the cumulative bottomhole pressure drop as a function of rate (Eq. 2), perforation friction and near-wellbore tortuosity can be quantitatively estimated.) assessing a second perforation efficiency for the second perforation design; and (Abstract, The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity) comparing the first perforation efficiency to the second perforation efficiency. (Fig. 7, Summary of 11 stages of an Utica PnP well (a) initial and final near-wellbore tortuosity pressures and β; (b) type of near-wellbore tortuosity; (c) initial and final perforation friction; and (d) estimated range of perforation efficiency.) Mondal does not teach in particular, but Heidari teaches: receiving a second plurality of flow variables for a second perforation design; (¶66 may obtain data during the second stage and use the data from the first stage and the second stage to generate one or more modified job designs.; ¶80 some portions of method 600 may repeat including using the machine learning model for the particular hydraulic fracturing well based on the historical production data, the time-series data associated with the at least one hydraulic fracturing well and based on the original job design, time-series data associated with a first stage of the job, time-series data associated with the second stage of the job, and the non-temporal data to determine an optimized job design for the particular hydraulic fracturing well for a third stage of the job. This optimization of the job design may continue for a fourth stage of the job and so on until the last stage for the well.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 8: Mondal does not teach in particular, but Heidari teaches: determining an optimal perforation design of the first perforation design and the second perforation design; and (¶27 Use of the model to predict aBased on the objective function (e.g., maximizing production), a most optimal scenario (e.g., a pumping schedule) given the constraints from a pool of top scenarios for a next stage and treatment may be recommended in real-time for a hydraulic fracturing job. As an example, the real-time design optimization model may recommend a change in proppant concentration from a first treatment to a second treatment based on real-time data collected on the location during the job.nd optimize a fracturing job ... the model may be based on additional well characteristics ... perforation cluster spacing; ¶27 The model may be used to predict and track KPIs of the well in real-time during the fracturing job and provide recommendations to optimize the KPIs for the fracturing job.; ¶40 next stage and treatment may be recommended in real-time for a hydraulic fracturing job.) displaying to an operator the optimal perforation design, the first perforation efficiency, the second perforation efficiency, or any combination thereof. (¶40 There may be one scenario that provides a best result or a highest objective function or there may be more than one scenario that provides a best result or highest objective function. The hydraulic fracturing job optimization system may display a graph or a representation of each scenario that may show the features/parameters over time. A user such as an operations engineer may view the scenarios and select one to modify the fracturing job for a next stage in the job.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 10: Mondal does not teach in particular, but Jin teaches: wherein the efficiency evaluator generates the instructions for hydraulic fracturing operations from the perforation efficiency of the perforation design. (Abstract, to determine borehole perforation cluster efficiency ... These results can be used to improve well completion and stimulation designs; ¶2 perforation efficiency diagnosis using distributed sensing measurements; ¶7 the relation between perforation cluster efficiency and hydraulic fracturing designs can be established in the same stimulation well to accelerate hydraulic fracturing design optimization in the reservoir development.; examiner notes that instructions for hydraulic fracturing operations are being interpreted to include a hydraulic fracture design, such as the one optimized by the reference in the above cited sections.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the efficiency analysis-based fracturing design optimization of Jin in the perforation cluster design and analysis system of Mondal, in order to improve well completion and stimulation designs, increase field production, and/or decrease costs. (Jin, Abstract). Mondal does not teach in particular, but Heidari teaches: a hydraulic fracturing operations controller to receive and implement instructions for hydraulic fracturing operations, (¶40 Based on the objective function (e.g., maximizing production), a most optimal scenario (e.g., a pumping schedule) given the constraints from a pool of top scenarios for a next stage and treatment may be recommended in real-time for a hydraulic fracturing job. As an example, the real-time design optimization model may recommend a change in proppant concentration from a first treatment to a second treatment based on real-time data collected on the location during the job ... Alternatively, the scenario may be automatically selected and implemented; ¶2 When these events occur, an on-location engineer makes decisions to control the job and fracture the well; ¶14 real-time hydraulic fracture control; ¶80 the hydraulic fracturing job optimization system 201 can implement the optimized job design for the particular hydraulic fracturing well.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 11: Mondal does not teach in particular, but Heidari teaches: wherein the hydraulic fracturing operations controller is part of a hydraulic fracturing operations system communicably coupled to the efficiency determination tool. (See the components described in ¶43, 45, 51, 55, and 59; ¶40 Based on the objective function (e.g., maximizing production), a most optimal scenario (e.g., a pumping schedule) given the constraints from a pool of top scenarios for a next stage and treatment may be recommended in real-time for a hydraulic fracturing job. As an example, the real-time design optimization model may recommend a change in proppant concentration from a first treatment to a second treatment based on real-time data collected on the location during the job ... Alternatively, the scenario may be automatically selected and implemented; ¶2 When these events occur, an on-location engineer makes decisions to control the job and fracture the well; ¶14 real-time hydraulic fracture control; ¶80 the hydraulic fracturing job optimization system 201 can implement the optimized job design for the particular hydraulic fracturing well.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 13: Mondal does not teach in particular, but Jin teaches: wherein the efficiency evaluator determines an optimal perforation design of the one or more simulated perforation designs. (Abstract, to determine borehole perforation cluster efficiency ... These results can be used to improve well completion and stimulation designs; ¶2 perforation efficiency diagnosis using distributed sensing measurements; ¶7 the relation between perforation cluster efficiency and hydraulic fracturing designs can be established in the same stimulation well to accelerate hydraulic fracturing design optimization in the reservoir development.; examiner notes that instructions for hydraulic fracturing operations are being interpreted to include a hydraulic fracture design, such as the one optimized by the reference in the above cited sections.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the efficiency analysis-based fracturing design optimization of Jin in the perforation cluster design and analysis system of Mondal, in order to improve well completion and stimulation designs, increase field production, and/or decrease costs. (Jin, Abstract) . 07-21-aia AIA Claim s 9, 12, and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Mondal (Mondal, S., Zhang, M., Huckabee, P., Ugueto, G., Jones, R., Vitthal, S., ... & Sharma, M. (2021, April). Advancements in step down tests to guide perforation cluster design and limited entry pressure intensities-Learnings from field tests in multiple basins. In SPE hydraulic fracturing technology conference and exhibition (p. D021S006R002). SPE.) in view of Heidari (US 20210087925 A1) . Regarding Claim 9: Mondal teaches: a data receiver to receive or retrieve one or more flow variables of a perforation design; (p.4, From the estimated ΔPperf, the number of active perforations (N) is calculated using Eq. 3.; p. 9, The perforation pressure drop is calculated using: ... The near-wellbore pressure drop is modelled using this equation: ... where knwbt and β are assumed to change linearly with the cumulative pumped proppant mass into this completion stage during the treatment.) a variable normalizer to calculate a stimulation treatment deliverability index, a normalized pressure derivative, or any combination thereof using the one or more flow variables; and (p.4, ... In a following section, the theoretical derivation of β will be presented for different fracture geometries and flow regimes ... By fitting the cumulative bottomhole pressure drop as a function of rate (Eq. 2), perforation friction and near-wellbore tortuosity can be quantitatively estimated.) an efficiency evaluator to determine a perforation efficiency of the perforation design using the stimulation treatment deliverability index, the normalized pressure derivative, or any combination thereof. (Abstract, The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity) Mondal does not teach in particular, but Heidari teaches: a processor; and (¶51 one or more processors; ¶52 For example, the compute components 202 can include one or more microprocessors;) memory storing machine readable instructions executable by the processor, the machine readable instructions comprising: an efficiency determination tool comprising: (¶61 one or more memory components; ¶88 computer-executable instructions that are stored or otherwise available from computer readable media) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 12: Mondal teaches: a modeling tool to generate one or more hydraulic fracturing perforation efficiency estimates of one or more simulated perforation designs, (Abstract, sensitivity of near-wellbore pressure drops and perforation size on stimulation distribution effectiveness in plug-and-perf (PnP) treatments is modeled using a coupled hydraulic fracturing simulator.; p.8, In this simulator, a computationally efficient pseudo-3D (P3D) fracture model is used to simulate the simultaneous multi-fracture propagation in a PnP completion. A resistance method is developed to distribute fluid among multiple fractures) wherein the efficiency determination tool determines one or more perforation efficiencies of the one or more simulated perforation designs. (Abstract, The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity) Regarding Claim 14: Mondal teaches: wherein the efficiency determination tool generates a visual of the perforation efficiency, the stimulation treatment deliverability index, the normalized pressure derivative, or any combination thereof, and (p.3, shows the pressure-rate response from a post-frac SDT consisting of 5 steps.; p.4, The instantaneous pressure-rate response is assumed because of flow-dependent or frictional pressure drop in the system, which consists of friction in the wellbore, across perforations and near-wellbore tortuosity (Eq. 1); Fig. 3, Pressure-rate response from pre- and post-frac SDT in 9 stages of cSPE well.) Mondal does not teach in particular, but Heidari teaches: a display communicatively coupled to the efficiency determination tool, (¶49 the hydraulic fracturing job optimization system 201 can also include a display device 210 for displaying data and graphical elements such as images, videos, text, simulations) wherein the display presents the visual to an operator. (¶40 A user such as an operations engineer may view the scenarios and select one to modify the fracturing job for a next stage in the job.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Regarding Claim 15: Mondal teaches: an efficiency determination tool comprising: (Abstract, The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity) a variable normalizer for determining a stimulation treatment deliverability index (STDI) from sensor data received by the receiver, and (p.4, ... In a following section, the theoretical derivation of β will be presented for different fracture geometries and flow regimes ... By fitting the cumulative bottomhole pressure drop as a function of rate (Eq. 2), perforation friction and near-wellbore tortuosity can be quantitatively estimated.) Mondal does not teach in particular, but Heidari teaches: a data receiver, (¶55 the data input engine 204 may obtain and process time-series data including surface data, downhole pumping data, or other sensor data such as DAS data, DTS data, or DSS data) a hydraulic fracturing operations system comprising: (¶62 The hydraulic fracturing job optimization system 201 may determine one or more best designs from the list of modified job designs and select one best design 306 to use in a next stage; ¶80 the hydraulic fracturing job optimization system 201 can implement the optimized job design for the particular hydraulic fracturing well.) one or more sensors for providing the sensor data to the data receiver, and (¶55 the data input engine 204 may obtain and process time-series data including surface data, downhole pumping data, or other sensor data such as DAS data, DTS data, or DSS data) a hydraulic fracturing operations controller for operating the operating equipment based on the STDI. (¶80 the hydraulic fracturing job optimization system 201 can implement the optimized job design for the particular hydraulic fracturing well.) It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the recommendation of optimized model results from Heidari to the optimized hydraulic fracturing designs of Jin, resulting in them being recommended to the user, in order to balance a maximization of production and minimization of cost and can be optimized for cost, short term production outputs, long term production outputs, and other KPIs (Heidari ¶25). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to BIJAN MAPAR whose telephone number is (571)270-3674. The examiner can normally be reached Monday - Thursday, 11:00-8:30. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /BIJAN MAPAR/ Primary Examiner, Art Unit 2189 Application/Control Number: 18/185,768 Page 2 Art Unit: 2189 Application/Control Number: 18/185,768 Page 3 Art Unit: 2189 Application/Control Number: 18/185,768 Page 4 Art Unit: 2189 Application/Control Number: 18/185,768 Page 5 Art Unit: 2189 Application/Control Number: 18/185,768 Page 6 Art Unit: 2189 Application/Control Number: 18/185,768 Page 7 Art Unit: 2189
