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 .
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. (PBA)
DETAILED ACTION
Claims status
Claims 1-19 are pending as the applicant filed response on 06/10/2024.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-19 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.
Claim 1, Step 1 the claim is a process (or machine) (Yes),
Step 2A Prong One, does the claim recite an abstract idea? current claim related to a method of hydraulic fracturing, comprising: monitoring the hydraulic fracturing treatment by recording data concerning pressure and properties of the fracturing materials in a wellbore; analyzing the data from stage (b) to estimate perforation cluster efficiency; adjusting the hydraulic fracturing treatment to improve the perforation cluster efficiency appears to be an abstract idea of mental process (MPEP 2106.04(a)) or data gathering equivalent to mathematical concept or mathematical manipulation function (MPEP 2106.04 (a) (2) (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), (OR Mathematical Concepts and Mental Processes) Step 2A Prong One: Yes.
Step 2A Prong Two, is the claim directed to an abstract idea? In other words, does claim recite additional elements that integrate the Judicial Exception into a practical application? the additional elements of . performing a hydraulic fracturing treatment by injecting hydraulic fracturing materials into two or more perforation clusters are recited at a high level of generality and merely amount to a particular field of use (see MPEP 2106.05(h)) and/or insignificant post-solution activity (MPEP 2106.05(g)), this does not integrate the Judicial Exception into a practical application,
Step 2A Prong Two: NO.
Step 2B, Does the claim recite additional element that amount to significantly more than the Judicial exception? there is no more additional elements
Step 2B: No. claim 1 not eligible.
Claim 2 related to wherein the pressure data are measured at a wellhead or a bottomhole or both, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 2 not eligible.
Claim 3 related to wherein the pressure data arise from pressure waves having a frequency higher than 1 Hz, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 3 not eligible.
Claim 4 related to measuring volumetric flow rate, slurry density and hydraulic fracturing material concentrations at a wellhead, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 4 not eligible.
Claim 5 related to entering the data from stage (b) into one or more computer models for hydraulic fracturing and comparing modeling results with the data from stage (b), its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 5 not eligible.
Claim 6 related to PKN, KGD,radial, Pseudo 3D or Planar 3D models, or combinations thereof, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 6 not eligible.
Claim 7 related to wherein the modeling is performed for different sets of perforation clusters with nonzero inflow of the hydraulic fracturing materials, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 7 not eligible.
Claim 8 related to wherein the comparing of modeling results is used to detect stimulated perforation clusters, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 8 not eligible.
Claim 9 related to calculation of hydraulic fracture depth based on reflection times for pressure waves travelling in the wellbore, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 9 not eligible.
Claim 10 related to calculation of the cluster efficiency based on one or more machine learning algorithms, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 10 not eligible.
Claim 11 related to wherein the one or more machine learning algorithms address the data acquired at stage (b) and heterodyne distributed vibration sensing data, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 11 not eligible.
Claim 12 related to wherein the one or more machine learning algorithms comprise linear regression, ridge regression, neural network regression, lasso regression, decision tree egression, random forest or support vector machines, or combinations thereof, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 12 not eligible.
Claim 13 related to wherein the hydraulic fracturing materials comprise fluids,proppants and additives, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 13 not eligible.
Claim 14 related to wherein the additives comprise fibers, fluid-loss, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 14 not eligible.
Claim 15 related to changing a pumping rate, concentrations of the hydraulic fracturing materials or both, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 15 not eligible.
Claim 17, related to wherein the adjusting of the hydraulic fracturing treatment is performed in real time, its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 17 not eligible.
Claim 18 related to wherein the hydraulic fracturing materials are injected in pulses during one or more stages at stage (a), its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 18 not eligible.
Claim 19 related to wherein the hydraulic fracturing materials are injected homogeneously at stage (a), its recites further data characterization and mathematical concepts that are part of the abstract idea, claim 19 not eligible.
Claim Rejections - 35 USC § 102
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.
Claim(s) 1-19 are rejected under 35 U.S.C. 102 (a) (1) as being anticipated by CREWS, CN 107923236 A, DATE PUBLISHED: 2018-04-17, CPC E21B 47/0025.
Regarding claim 1:
CREWS described a method of hydraulic fracturing, comprising: a. performing a hydraulic fracturing treatment by injecting hydraulic fracturing materials into two or more perforation clusters (page 2, hydraulic fracturing, page 7, old side well and perforation section); b. monitoring the hydraulic fracturing treatment by recording data concerning pressure and properties of the fracturing materials in a wellbore (page 10, imaging of the treatment fluid can be hydraulic fracturing); c. analyzing the data from stage (b) to estimate perforation cluster efficiency (page 10, compared with data from an adjacent section, it can determined for shale geographic specific diagnostic evaluation of cleaning degree); d. adjusting the hydraulic fracturing treatment to improve the perforation cluster efficiency (page 21, of processing parameters and reservoir parameters and fluid efficiency, page 22, increased processing efficiency).
Regarding claim 2, CREWS further described wherein the pressure data are measured at a wellhead or a bottomhole (page 23-24, bottom or anywhere) or both.
Regarding claim 3, CREWS further described wherein the pressure data arise from pressure waves having a frequency higher than 1 Hz (page 15, low frequency).
Regarding claim 4, CREWS further described measuring volumetric flow rate (page 19, flow rate), slurry density (any different density) and hydraulic fracturing material concentrations at a wellhead (page 20, hydraulic
Fracture pressure).
Regarding claim 5, CREWS further described comprises entering the data from stage (b) into one or more computer models for hydraulic fracturing and comparing modeling results with the data from stage (b) (page 7, have wide range of variables on the adjacent lateral well relative to using old side well and perforation section, well relative to model drilling).
Regarding claim 6, CREWS further described wherein the one or more computer models comprise PKN, KGD,radial, Pseudo 3D or Planar 3D models (page 12-13, 3D formation of planar fissure length), or combinations thereof.
Regarding claim 7, CREWS further described wherein the modeling is performed for different sets of perforation clusters with nonzero inflow of the hydraulic fracturing materials (page 19, any flow rate, injection rate).
Regarding claim 8, CREWS further described wherein the comparing of modeling results is used to detect stimulated perforation clusters (page 14, receiving signal can be made of the same or different diagnostic devices).
Regarding claim 9, CREWS further described calculation of hydraulic fracture depth based on reflection times for pressure waves travelling in the wellbore (page 15, by measuring shear wave anisotropy evaluation of crack induced around about 2ft-4ft depth extending into the wellbore (0.6m-1.2m, page 17, primary injection formed by pressure on either side of lateral wellbore area or region).
Regarding claim 10, CREWS further described calculation of the cluster efficiency based on one or more machine learning algorithms (page 22, cause increased processing efficiency, to create a larger complexity of crack and fracture stream guidance capability, so that hydrocarbon production and hydrocarbon recovery is maximized).
Regarding claim 11, CREWS further described wherein the one or more machine learning algorithms address the data acquired at stage (b) and heterodyne distributed vibration sensing data (page 6, for the best crack generated complexity, area, fracture stream guidance capability of the quantity and distribution, permeability and/or hydrocarbon sweet spot formation is determined to each of the shale reservoir fracturing or fracturing mode. Also important is that know which well treatment to which complex fracture network is such that only the well treatment to industry. Page 14, included vibration).
Regarding claim 12, CREWS further described wherein the one or more machine learning algorithms comprise linear regression, ridge regression, neural network regression, lasso regression, decision tree egression, random forest or support vector machines (page 14, waveform vector travel time), or combinations thereof.
Regarding claim 13, CREWS further described wherein the hydraulic fracturing materials comprise fluids ,proppants and additives (page 19, injection rate, fluid viscosity from water with chemical agent).
Regarding claim 14, CREWS further described the additives comprise fibers, fluid-loss additives,diverting agents, breakers, corrosion inhibitors, friction reducers, scale inhibitors, ;urfactants, water soluble polymers, crosslinkers, biocides, pH adjusting agents (page 11, pH buffering agent) or buffers,>r combinations thereof.
Regarding claim 15, CREWS further described changing a pumping rate (page 13, agent pump, 6, 30 and 60, can detect up to 250ft, 02. Inch wide), concentrations of the hydraulic fracturing materials or both.
Regarding claim 16, CREWS further described in real time (page 10, real-time processing).
Regarding claim 17, CREWS further described more than one stage (page 4, after the initial production stage).
Regarding claim 18, CREWS further described wherein the hydraulic fracturing materials are injected in pulses during one or more stages at stage (a) (page 10, the injection side well of fracture plane orientation of intermediate length 62 can be used for placing diagnosis such as tracer material for evaluating the crack section fluid production, page 15, of sequential pulse or alternating pulses).
Regarding claim 19, CREWS further described wherein the hydraulic fracturing materials are injected homogeneously at stage (a) (page 15, of sequential pulse or alternating pulses, continuously using water power crack generation time and sweep is a real-time plot of fracturing during processing, page 19, injection rate, fluid viscosity from water with chemical agent).
Contact information
4. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Tung Lau whose telephone number is (571)272-2274, email is Tungs.lau@uspto.gov. The examiner can normally be reached on Tuesday-Friday 7:00 AM-5:00 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, TURNER SHELBY, can be reached on 571-272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TUNG S LAU/Primary Examiner, Art Unit 2857
Technology Center 2800
July 20, 2026
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