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
The United States Patent & Trademark Office appreciates the application that is submitted by the inventor/assignee. The United States Patent & Trademark Office reviewed the following application and has made the following comments below.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/23/2024 and 11/14/2025 are considered and attached.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2, 9 and 16 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. The examiner strongly suggested that appropriate corrections be made to clarify the claim scope.
With respect to Claim 2, the claim recites the following, each of which renders the claim indefinite:
“the wellbore” on line 5 (unclear antecedent basis).
Claims 9 and 16 are rejected for the same reason with claim 2.
Regarding claim 16,
“the one or more processors to be identified as a known good cable” on line 3 (unclear to what this refers, Examiner believes this is a typo). For the purpose of the examination, the Examiner interprets this as “the wellbore power cable to be identified as a known good cable”;
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.
Claim(s) 1-4, 8-12, 15-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Andre (WO-2015135918-A1, cited in IDS, a copy of this document is attached, hereinafter Andre) in view of P&C Committee (Petroleum & Chemical Industry Committee “IEEE Recommended Practice for Testing of Electric Submersible Pump Cable” IEEE, published 2021, hereinafter P&C Committee), and further in view of Lim et al. (US-20250198746-A1, foreign priority claimed 2023, hereinafter Lim).
CLAIM 1
In regards to Claim 1, Andre teaches an apparatus (Andre, ¶ [0003]: “a monitoring system and corresponding method, and in particular to a wireline integrity monitoring system and method for monitoring for damage, defects and other changes in wireline”) comprising:
a memory (Andre, ¶ [0066]: “The memory or data store may be configured to store the database, log or record of the at least one property and/or operational parameter of at least the parts or portions of the line”);
one or more processors that execute instructions (Andre, ¶ [0086-0088]: “a computer program product configured to implement or at least partially implement the apparatus of the first, second, fourth, fifth, seventh or eighth aspects of the present invention … a processing apparatus provided or loaded with the computer program product) out of the memory (Andre, ¶ [0065]: “The controller may comprise or be configured to communicate with at least one of: one or more processors, one or more memories or data stores …”); and
one or more sensors that collect data when a wellbore power cable (Andre, ¶ [0005-0007]: “Two general types of flexible wireline are commonly used, namely slickline and electric line … Electric line comprises electrical cable and is generally braided … A new type of slickline, known as a coated slickline or insulated slickline, comprises a single strand of steel wire coated with a thin polymeric layer. This combines the advantages of both electric line and slickline in a new type of wireline cable” Andre teaches monitoring a coated line in well operation, the line could be slickline or electric line) is proximal to the one or more sensors (Andre, ¶ [0018]: “The measurement device may comprise an optical sensor such as a digital camera and/or video camera, a CCD sensor, a CMOS sensor, a photodiode array, a magnetic reader or sensor for sensing or determining magnetic markings, a UV, IR or fluorescence sensor, and/or the like”; ¶ [0126-0127], see annotated FIG. 4 below, the line is passed
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through the monitoring device and multiple sensors),
wherein the one or more processors execute the instructions out of the memory to:
identify one or more features of the wellbore power cable along a length of the wellbore power cable (Andre, ¶ [0038]: “Determining properties of the line, such as outer line shape or size, anomalies such as bulges or necks, and/or by performing measurements such as laser scans, insulation tests and ultrasonic testing, it may be possible to determine variations in outer coating diameter or ovality (which may lead to sealing failures), scratches, nicks or cuts in the coating (which may lead to sealing failures and/or electrical issues) and/or de bonding of the coating (which may also lead to sealing or electrical failures)”), wherein the one or more features of the wellbore power cable include dimensions of the wellbore power cable (Andre, ¶ [0014 and 0073-0074]: “0073: at least one of the dimensional scanners and/or the at least one of the monitoring systems arranged downstream of the coating unit may be configured to determine at least one of: diameter and/or ovality/roundness of the line, and/or at least part or all of one or more cross sectional profiles of the line or the one or more parts or portions of the line, e.g. of the coating, or at least one coating fault in the line, such as necks, lumps, holes, weak or thin points and/or the like”)
Andre does not explicitly disclose dimensions of the wellbore power cable that correspond to nominal dimensions of a type of power cable.
P&C Committee is in the same field of art of inspecting and testing electric submersible pump cables. Further, IEEE teaches dimensions of the wellbore power cable that correspond to nominal dimensions of a type of power cable. (P&C Committee, pages 32-33, section 7, table 11 and 12, see table 12 below. P&C Committee teaches nominal diameters for multiple cable sizes)
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Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre by incorporating nominal dimension data of different cable sizes that is taught by P&C Committee, to make a system to determine integrity of a cable by comparing measured dimension with nominal dimension; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to improve the reliability and safety of the cable inspection task by following recommended practices (P&C Committee, section 1.2 Purpose: “The purpose of this recommended practice is as follows: a) Provide a guideline for performing ESP cable factory, acceptance and maintenance tests. b) Provide guidelines for evaluation and interpretation of the test results. c) Define terms that have a specific meaning to the recommended practice.”).
The combination of Andre and P&C Committee then teaches identify based on an evaluation of the data collected by the one more sensors, differences in the dimensions of the wellbore power cable as compared to the nominal dimensions (P&C Committee, pages 32-33, section 7, table 11 and 12, see table 12 above) of the type of power cable. (Andre, ¶ [0032, 0034 and 0058]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter. The initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter may be stored in and/or retrieved or retrievable from the database, log or record” Andre teaches comparing measured dimension with target dimension data by statistical or numerical analysis, to determine a state of the monitoring line)
The combination of Andre and P&C Committee does not explicitly disclose train a computer model based on the identified differences in the dimensions.
Lim is in the same field of art of inspection based on thickness value. Further, Lim teaches train a computer model (Lim, ¶ [0133 and 0154]: “when the generation of the AI model is necessary, the processor 350 trains individual feature information data of the ground truth transmitted light image to generate the AI model”) based on the identified differences in the dimensions. (Lim, ¶ [0111 - 0114]: “AI model may be a model generated based on the ground truth transmitted light image data and the feature information data of the reference sample 20 of various thicknesses of the same material as the inspection target product 10 … The AI model may include machine learning (SVM, isolation random forest, etc.), deep learning algorithms (GAN, AutoEncoder, transfer learning, etc.), …” Lim teaches training an AI model to predict thickness value of a product from an input image, based on sample data of the same material with varying thickness values)
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre and P&C Committee by incorporating the AI-based system to determine thickness value that is taught by Lim, to make an inspection system that can determine coating thickness by an AI model; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to increase efficiency and automation of the tasks measuring and inspecting thickness (Lim, ¶ [0060]: “, the present invention may be easily applied to the manufacturing process of related industrial sites that require thickness measurement of manufactured products and selection inspection of defective thickness products, and may greatly contribute to the efficiency and automation of related manufacturing processes”).
The combination of Andre, P&C Committee, and Lim then teaches train a computer model based on the identified differences in the dimensions (Lim, ¶ [0111 - 0114], Lim teaches training an AI model to predict thickness value of a product from an input image, based on sample data of the same material with varying thickness values.) of the wellbore power cable. (Andre, ¶ [0032, 0034 and 0058]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter. The initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter may be stored in and/or retrieved or retrievable from the database, log or record” Andre teaches comparing measured dimension with target dimension data by statistical or numerical analysis, to determine a state of the monitoring line)
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
CLAIM 2
Regarding Claim 2, the combination of Andre, P&C Committee, and Lim teaches the apparatus of claim 1. In addition, the combination of Andre, P&C Committee, and Lim teaches the wellbore power cable is identified as a known good cable based on the identified differences being within a threshold tolerance of the nominal dimensions of the type of power cable (Andre, ¶ [0033]: “The monitoring system may be configured to at least partially determine the integrity, risk of failure, condition of and/or damage, anomalies, wear or other changes in the line and/or in the one or more parts or portions of the line, e.g. in the coating of the line, by determining if the at least one property and/or operational parameter and/or variations therein exceeds and/or falls below one or more limits or thresholds or falls outwith a range, which may comprise preset or predetermined limits, thresholds and/or ranges.” Andre teaches determining a damaged condition of the wellbore cable if the variations/differences exceed a predetermined threshold), and
the wellbore power cable is deployed in the wellbore (Andre, ¶ [0011]: “a wellbore”) or another wellbore based on the respective dimensions (P&C Committee, pages 32-33, section 7, table 11 and 12. P&C Committee teaches multiple trade sizes of cable) along the length of the wellbore power cable being classified as being the known good cable. (P&C Committee, page 15, “maintenance leakage current test: This test is conducted after removing the cable from a well and is normally performed by the user or the designated representative using dc voltage at 40% of the factory test voltage level. It is intended to detect the deterioration of the cable insulation and to help determine suitability for reuse” P&C Committee teaches testing if the cable is suitable for re-deployment)
CLAIM 3
Regarding Claim 3, the combination of Andre, P&C Committee, and Lim teaches the apparatus of claim 1. In addition, the combination of Andre, P&C Committee, and Lim teaches evaluate additional collected data (Andre, ¶ [0017-0019]: “the line may comprise a plurality of markers, which may be provided at predetermined, known or defined locations or spacings… The devices for measuring length, position or location on the line or line speed may comprise one or more of: a reader or detector for detecting the markers on or in the line … ”), and
identify based on the evaluation on the additional data, a location of a defect in the wellbore power cable. (Andre, ¶ [0032-0035]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter … The monitoring system may be configured to record the determined properties and/or parameters and/or location or position in a database associated with the identified line”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers)
CLAIM 4
Regarding Claim 4, the combination of Andre, P&C Committee, and Lim teaches the apparatus of claim 1. In addition, the combination of Andre, P&C Committee, and Lim teaches the instructions further cause the one or more processors to identify a measure of stretching of the wellbore power cable. (Andre, ¶ [0019]: “One or more of the properties or operational parameters of the line or of the parts or portions of the line, such as a number or degree of line stretches, may be determined using the devices for measuring length, position or location on the line or line speed. For example, stretching may be determined by comparing at least one measured spacing between markers with at least one previous, predetermined or theoretical spacing or by comparing the spacings measured by two techniques or devices for measuring length, position or location on the line or line speed, such as a difference between a spacing determined by the marker reader or detector and a spacing determined by a rotary encoder or other device or by measuring differences in the spacings between the markers at different sections of the line handling apparatus”)
CLAIM 8
In regards to Claim 8, Andre teaches A method comprising:
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accessing collected data associated with a wellbore power cable (Andre, ¶ [0005-0007]: “Two general types of flexible wireline are commonly used, namely slickline and electric line … Electric line comprises electrical cable and is generally braided … A new type of slickline, known as a coated slickline or insulated slickline, comprises a single strand of steel wire coated with a thin polymeric layer. This combines the advantages of both electric line and slickline in a new type of wireline cable” Andre teaches monitoring a coated line in well operation, the line could be slickline or electric line), wherein the data was collected when a portion of the wellbore cable was proximal to one or more sensors (Andre, ¶ [0018]: “The measurement device may comprise an optical sensor such as a digital camera and/or video camera, a CCD sensor, a CMOS sensor, a photodiode array, a magnetic reader or sensor for sensing or determining magnetic markings, a UV, IR or fluorescence sensor, and/or the like”; ¶ [0126-0127], see annotated FIG. 4 below, the line is passed through the monitoring device and multiple sensors);
identifying one or more features of the wellbore power cable along a length of the wellbore power cable (Andre, ¶ [0038]: “Determining properties of the line, such as outer line shape or size, anomalies such as bulges or necks, and/or by performing measurements such as laser scans, insulation tests and ultrasonic testing, it may be possible to determine variations in outer coating diameter or ovality (which may lead to sealing failures), scratches, nicks or cuts in the coating (which may lead to sealing failures and/or electrical issues) and/or de bonding of the coating (which may also lead to sealing or electrical failures)”), wherein the one or more features of the wellbore power cable include dimensions of the wellbore power cable (Andre, ¶ [0014 and 0073-0074]: “0073: at least one of the dimensional scanners and/or the at least one of the monitoring systems arranged downstream of the coating unit may be configured to determine at least one of: diameter and/or ovality/roundness of the line, and/or at least part or all of one or more cross sectional profiles of the line or the one or more parts or portions of the line, e.g. of the coating, or at least one coating fault in the line, such as necks, lumps, holes, weak or thin points and/or the like”)
Andre does not explicitly disclose dimensions of the wellbore power cable that correspond to nominal dimensions of a type of power cable.
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P&C Committee is in the same field of art of inspecting and testing electric submersible pump cables. Further, IEEE teaches dimensions of the wellbore power cable that correspond to nominal dimensions of a type of power cable. (P&C Committee, pages 32-33, section 7, table 11 and 12, see table 12 below. P&C Committee teaches nominal diameters for multiple cable sizes)
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre by incorporating nominal dimension data of different cable sizes that is taught by P&C Committee, to make a system to determine integrity of a cable by comparing measured dimension with nominal dimension; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to improve the reliability and safety of the cable inspection task by following recommended practices (P&C Committee, section 1.2 Purpose: “The purpose of this recommended practice is as follows: a) Provide a guideline for performing ESP cable factory, acceptance and maintenance tests. b) Provide guidelines for evaluation and interpretation of the test results. c) Define terms that have a specific meaning to the recommended practice.”).
The combination of Andre and P&C Committee then teaches identifying based on an evaluation of the data collected by the one more sensors, differences in the dimensions of the wellbore power cable as compared to the nominal dimensions (P&C Committee, pages 32-33, section 7, table 11 and 12, see table 12 above) of the type of power cable. (Andre, ¶ [0032, 0034 and 0058]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter. The initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter may be stored in and/or retrieved or retrievable from the database, log or record” Andre teaches comparing measured dimension with target dimension data by statistical or numerical analysis, to determine a state of the monitoring line)
The combination of Andre and P&C Committee does not explicitly disclose training a computer model based on the identified differences in the dimensions.
Lim is in the same field of art of inspection based on thickness value. Further, Lim teaches train a computer model (Lim, ¶ [0133 and 0154]: “when the generation of the AI model is necessary, the processor 350 trains individual feature information data of the ground truth transmitted light image to generate the AI model”) based on the identified differences in the dimensions. (Lim, ¶ [0111 - 0114]: “AI model may be a model generated based on the ground truth transmitted light image data and the feature information data of the reference sample 20 of various thicknesses of the same material as the inspection target product 10 … The AI model may include machine learning (SVM, isolation random forest, etc.), deep learning algorithms (GAN, AutoEncoder, transfer learning, etc.), …” Lim teaches training an AI model to predict thickness value of a product from an input image, based on sample data of the same material with varying thickness values)
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre and P&C Committee by incorporating the AI-based system to determine thickness value that is taught by Lim, to make an inspection system that can determine coating thickness by an AI model; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to increase efficiency and automation of the tasks measuring and inspecting thickness (Lim, ¶ [0060]: “, the present invention may be easily applied to the manufacturing process of related industrial sites that require thickness measurement of manufactured products and selection inspection of defective thickness products, and may greatly contribute to the efficiency and automation of related manufacturing processes”).
The combination of Andre, P&C Committee, and Lim then teaches training a computer model based on the identified differences in the dimensions (Lim, ¶ [0111 - 0114], Lim teaches training an AI model to predict thickness value of a product from an input image, based on sample data of the same material with varying thickness values.) of the wellbore power cable. (Andre, ¶ [0032, 0034 and 0058]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter. The initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter may be stored in and/or retrieved or retrievable from the database, log or record” Andre teaches comparing measured dimension with target dimension data by statistical or numerical analysis, to determine a state of the monitoring line)
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
CLAIM 9
Regarding Claim 9, the combination of Andre, P&C Committee, and Lim teaches the method of claim 8. In addition, the combination of Andre, P&C Committee, and Lim teaches identifying that the wellbore power cable is as a known good cable based on the identified differences being within a threshold tolerance of the nominal dimensions of the type of power cable (Andre, ¶ [0033]: “The monitoring system may be configured to at least partially determine the integrity, risk of failure, condition of and/or damage, anomalies, wear or other changes in the line and/or in the one or more parts or portions of the line, e.g. in the coating of the line, by determining if the at least one property and/or operational parameter and/or variations therein exceeds and/or falls below one or more limits or thresholds or falls outwith a range, which may comprise preset or predetermined limits, thresholds and/or ranges.” Andre teaches determining a damaged condition of the wellbore cable if the variations/differences exceed a predetermined threshold), and
the wellbore power cable is deployed in the wellbore (Andre, ¶ [0011]: “a wellbore”) or another wellbore based on the respective dimensions (P&C Committee, pages 32-33, section 7, table 11 and 12. P&C Committee teaches multiple trade sizes of cable) along the length of the wellbore power cable being classified as being the known good cable. (P&C Committee, page 15, “maintenance leakage current test: This test is conducted after removing the cable from a well and is normally performed by the user or the designated representative using dc voltage at 40% of the factory test voltage level. It is intended to detect the deterioration of the cable insulation and to help determine suitability for reuse” P&C Committee teaches testing if the cable is suitable for re-deployment)
CLAIM 10
Regarding Claim 10, the combination of Andre, P&C Committee, and Lim teaches the method of claim 8. In addition, the combination of Andre, P&C Committee, and Lim teaches evaluating additional collected data (Andre, ¶ [0017-0019]: “the line may comprise a plurality of markers, which may be provided at predetermined, known or defined locations or spacings… The devices for measuring length, position or location on the line or line speed may comprise one or more of: a reader or detector for detecting the markers on or in the line … ”), and
identifying based on the evaluation on the additional data, a location of a defect in the wellbore power cable. (Andre, ¶ [0032-0035]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter … The monitoring system may be configured to record the determined properties and/or parameters and/or location or position in a database associated with the identified line”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers)
CLAIM 11
Regarding Claim 11, the combination of Andre, P&C Committee, and Lim teaches the method of claim 8. In addition, the combination of Andre, P&C Committee, and Lim teaches identifying a measure of stretching of the wellbore power cable. (Andre, ¶ [0019]: “One or more of the properties or operational parameters of the line or of the parts or portions of the line, such as a number or degree of line stretches, may be determined using the devices for measuring length, position or location on the line or line speed. For example, stretching may be determined by comparing at least one measured spacing between markers with at least one previous, predetermined or theoretical spacing or by comparing the spacings measured by two techniques or devices for measuring length, position or location on the line or line speed, such as a difference between a spacing determined by the marker reader or detector and a spacing determined by a rotary encoder or other device or by measuring differences in the spacings between the markers at different sections of the line handling apparatus”)
CLAIM 12
Regarding Claim 12, the combination of Andre, P&C Committee, and Lim teaches the method of claim 8. In addition, the combination of Andre, P&C Committee, and Lim teaches identifying a potential (Andre, ¶ [0014]: “the monitoring system may be configured to identify any dimensional properties or changes in the line that may be indicative of damage or potential failure, such as bulges, constrictions, nicks, cuts, indentations, protrusions, stretches and/or the like”,) anomalous condition located at a first location of the wellbore power cable. (Andre, ¶ [0038]: “Determining properties of the line, such as outer line shape or size, anomalies such as bulges or necks, and/or by performing measurements such as laser scans, insulation tests and ultrasonic testing, it may be possible to determine variations in outer coating diameter or ovality (which may lead to sealing failures), scratches, nicks or cuts in the coating (which may lead to sealing failures and/or electrical issues) and/or de bonding of the coating (which may also lead to sealing or electrical failures)”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers)
CLAIM 15
Regarding Claim 15, Andre teaches a non-transitory computer-readable storage medium (Andre, ¶ [0066]: “The memory or data store may be configured to store the database, log or record of the at least one property and/or operational parameter of at least the parts or portions of the line”) having embodied thereon instructions (Andre, ¶ [0086-0088]: “a computer program product configured to implement or at least partially implement the apparatus of the first, second, fourth, fifth, seventh or eighth aspects of the present invention … a processing apparatus provided or loaded with the computer program product) of that when executed by one or more processors (Andre, ¶ [0065]: “The controller may comprise or be configured to communicate with at least one of: one or more processors, one or more memories or data stores …”):
identify one or more features (Andre, ¶ [0038]: “Determining properties of the line, such as outer line shape or size, anomalies such as bulges or necks, and/or by performing measurements such as laser scans, insulation tests and ultrasonic testing, it may be possible to determine variations in outer coating diameter or ovality (which may lead to sealing failures), scratches, nicks or cuts in the coating (which may lead to sealing failures and/or electrical issues) and/or de bonding of the coating (which may also lead to sealing or electrical failures)”) of a wellbore power cable (Andre, ¶ [0005-0007]: “Two general types of flexible wireline are commonly used, namely slickline and electric line … Electric line comprises electrical cable and is generally braided … A new type of slickline, known as a coated slickline or insulated slickline, comprises a single strand of steel wire coated with a thin polymeric layer. This combines the advantages of both electric line and slickline in a new type of wireline cable” Andre teaches monitoring a coated line in well operation, the line could be slickline or electric line) along a length of the wellbore power cable based on an evaluation on data collected by one or more sensors(Andre, ¶ [0018]: “The measurement device may comprise an optical sensor such as a digital camera and/or video camera, a CCD sensor, a CMOS sensor, a photodiode array, a magnetic reader or sensor for sensing or determining magnetic markings, a UV, IR or fluorescence sensor, and/or the like”; ¶ [0126-0127], see annotated FIG. 4 below, the line is passed through the monitoring device and multiple sensors),
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wherein the one or more features of the wellbore power cable include dimensions of the wellbore power cable (Andre, ¶ [0014 and 0073-0074]: “0073: at least one of the dimensional scanners and/or the at least one of the monitoring systems arranged downstream of the coating unit may be configured to determine at least one of: diameter and/or ovality/roundness of the line, and/or at least part or all of one or more cross sectional profiles of the line or the one or more parts or portions of the line, e.g. of the coating, or at least one coating fault in the line, such as necks, lumps, holes, weak or thin points and/or the like”)
Andre does not explicitly disclose dimensions of the wellbore power cable that correspond to nominal dimensions of a type of power cable.
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P&C Committee is in the same field of art of inspecting and testing electric submersible pump cables. Further, IEEE teaches dimensions of the wellbore power cable that correspond to nominal dimensions of a type of power cable. (P&C Committee, pages 32-33, section 7, table 11 and 12, see table 12 below. P&C Committee teaches nominal diameters for multiple cable sizes)
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre by incorporating nominal dimension data of different cable sizes that is taught by P&C Committee, to make a system to determine integrity of a cable by comparing measured dimension with nominal dimension; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to improve the reliability and safety of the cable inspection task by following recommended practices (P&C Committee, section 1.2 Purpose: “The purpose of this recommended practice is as follows: a) Provide a guideline for performing ESP cable factory, acceptance and maintenance tests. b) Provide guidelines for evaluation and interpretation of the test results. c) Define terms that have a specific meaning to the recommended practice.”).
The combination of Andre and P&C Committee then teaches identify based on an evaluation of the data collected by the one more sensors, differences in the dimensions of the wellbore power cable as compared to the nominal dimensions (P&C Committee, pages 32-33, section 7, table 11 and 12, see table 12 above) of the type of power cable. (Andre, ¶ [0032, 0034 and 0058]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter. The initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter may be stored in and/or retrieved or retrievable from the database, log or record” Andre teaches comparing measured dimension with target dimension data by statistical or numerical analysis, to determine a state of the monitoring line)
The combination of Andre and P&C Committee does not explicitly disclose train a computer model based on the identified differences in the dimensions.
Lim is in the same field of art of inspection based on thickness value. Further, Lim teaches train a computer model (Lim, ¶ [0133 and 0154]: “when the generation of the AI model is necessary, the processor 350 trains individual feature information data of the ground truth transmitted light image to generate the AI model”) based on the identified differences in the dimensions. (Lim, ¶ [0111 - 0114]: “AI model may be a model generated based on the ground truth transmitted light image data and the feature information data of the reference sample 20 of various thicknesses of the same material as the inspection target product 10 … The AI model may include machine learning (SVM, isolation random forest, etc.), deep learning algorithms (GAN, AutoEncoder, transfer learning, etc.), …” Lim teaches training an AI model to predict thickness value of a product from an input image, based on sample data of the same material with varying thickness values)
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre and P&C Committee by incorporating the AI-based system to determine thickness value that is taught by Lim, to make an inspection system that can determine coating thickness by an AI model; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to increase efficiency and automation of the tasks measuring and inspecting thickness (Lim, ¶ [0060]: “, the present invention may be easily applied to the manufacturing process of related industrial sites that require thickness measurement of manufactured products and selection inspection of defective thickness products, and may greatly contribute to the efficiency and automation of related manufacturing processes”).
The combination of Andre, P&C Committee, and Lim then teaches train a computer model based on the identified differences in the dimensions (Lim, ¶ [0111 - 0114], Lim teaches training an AI model to predict thickness value of a product from an input image, based on sample data of the same material with varying thickness values.) of the wellbore power cable. (Andre, ¶ [0032, 0034 and 0058]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter. The initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter may be stored in and/or retrieved or retrievable from the database, log or record” Andre teaches comparing measured dimension with target dimension data by statistical or numerical analysis, to determine a state of the monitoring line)
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
CLAIM 16
Regarding Claim 16, the combination of Andre, P&C Committee, and Lim teaches the medium of claim 15. In addition, the combination of Andre, P&C Committee, and Lim teaches the wellbore power cable is identified as a known good cable based on the identified differences being within a threshold tolerance of the nominal dimensions of the type of power cable (Andre, ¶ [0033]: “The monitoring system may be configured to at least partially determine the integrity, risk of failure, condition of and/or damage, anomalies, wear or other changes in the line and/or in the one or more parts or portions of the line, e.g. in the coating of the line, by determining if the at least one property and/or operational parameter and/or variations therein exceeds and/or falls below one or more limits or thresholds or falls outwith a range, which may comprise preset or predetermined limits, thresholds and/or ranges.” Andre teaches determining a damaged condition of the wellbore cable if the variations/differences exceed a predetermined threshold), and
the wellbore power cable is deployed in the wellbore (Andre, ¶ [0011]: “a wellbore”) or another wellbore based on the respective dimensions (P&C Committee, pages 32-33, section 7, table 11 and 12. P&C Committee teaches multiple trade sizes of cable) along the length of the wellbore power cable being classified as being the known good cable. (P&C Committee, page 15, “maintenance leakage current test: This test is conducted after removing the cable from a well and is normally performed by the user or the designated representative using dc voltage at 40% of the factory test voltage level. It is intended to detect the deterioration of the cable insulation and to help determine suitability for reuse” P&C Committee teaches testing if the cable is suitable for re-deployment)
CLAIM 17
Regarding Claim 17, the combination of Andre, P&C Committee, and Lim teaches the medium of claim 15. In addition, the combination of Andre, P&C Committee, and Lim teaches evaluate additional collected data (Andre, ¶ [0017-0019]: “the line may comprise a plurality of markers, which may be provided at predetermined, known or defined locations or spacings… The devices for measuring length, position or location on the line or line speed may comprise one or more of: a reader or detector for detecting the markers on or in the line … ”), and
identify based on the evaluation on the additional data, a location of a defect in the wellbore power cable. (Andre, ¶ [0032-0035]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter … The monitoring system may be configured to record the determined properties and/or parameters and/or location or position in a database associated with the identified line”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers)
CLAIM 18
Regarding Claim 4, the combination of Andre, P&C Committee, and Lim teaches the medium of claim 15. In addition, the combination of Andre, P&C Committee, and Lim teaches the instructions further cause the one or more processors to identify a measure of stretching of the wellbore power cable. (Andre, ¶ [0019]: “One or more of the properties or operational parameters of the line or of the parts or portions of the line, such as a number or degree of line stretches, may be determined using the devices for measuring length, position or location on the line or line speed. For example, stretching may be determined by comparing at least one measured spacing between markers with at least one previous, predetermined or theoretical spacing or by comparing the spacings measured by two techniques or devices for measuring length, position or location on the line or line speed, such as a difference between a spacing determined by the marker reader or detector and a spacing determined by a rotary encoder or other device or by measuring differences in the spacings between the markers at different sections of the line handling apparatus”)
CLAIM 19
Regarding Claim 19, the combination of Andre, P&C Committee, and Lim teaches the medium of claim 15. In addition, the combination of Andre, P&C Committee, and Lim teaches identifying a potential (Andre, ¶ [0014]: “the monitoring system may be configured to identify any dimensional properties or changes in the line that may be indicative of damage or potential failure, such as bulges, constrictions, nicks, cuts, indentations, protrusions, stretches and/or the like”,) anomalous condition located at a first location of the wellbore power cable. (Andre, ¶ [0038]: “Determining properties of the line, such as outer line shape or size, anomalies such as bulges or necks, and/or by performing measurements such as laser scans, insulation tests and ultrasonic testing, it may be possible to determine variations in outer coating diameter or ovality (which may lead to sealing failures), scratches, nicks or cuts in the coating (which may lead to sealing failures and/or electrical issues) and/or de bonding of the coating (which may also lead to sealing or electrical failures)”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers)
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Andre in view of P&C Committee in view of Lim, and further in view of Hanhirova et al. (Hanhirova, Jussi, et al. "A machine learning based quality control system for power cable manufacturing." IEEE, published 2019, hereinafter Hanhirova).
CLAIM 5
In regards to Claim 5, the combination of Andre, P&C Committee, and Lim teaches the apparatus of claim 1. In addition, the combination of Andre, P&C Committee, and Lim teaches the instructions further cause the one or more processors to identify a potential anomalous condition located at a first location of the wellbore power cable. (Andre, ¶ [0014]: “the monitoring system may be configured to identify any dimensional properties or changes in the line that may be indicative of damage or potential failure, such as bulges, constrictions, nicks, cuts, indentations, protrusions, stretches and/or the like”, ¶ [0038]: “Determining properties of the line, such as outer line shape or size, anomalies such as bulges or necks, and/or by performing measurements such as laser scans, insulation tests and ultrasonic testing, it may be possible to determine variations in outer coating diameter or ovality (which may lead to sealing failures), scratches, nicks or cuts in the coating (which may lead to sealing failures and/or electrical issues) and/or de bonding of the coating (which may also lead to sealing or electrical failures)”)
The combination of Andre, P&C Committee, and Lim does not explicitly disclose at least one feature of the one or more features is identified based on a visual appearance.
Hanhirova is in the same field of art of inspecting power cable. Further, Hanhirova teaches at least one feature of the one or more features is identified based on a visual appearance. (Hanhirova, page 193, Introduction: “Visual anomalies at the surface of a cable can be caused by numerous underlying problems inside the insulated cable core … Using machine learning methods, it is possible to distinguish between naturally occurring surface features and features that are related to significant defects … Our experiments with the prototype show that well-known pre trained CNN models can effectively be fine-tuned to detect defects”; page 195-196 section IV training: “we map the surface mesh data to grayscale images. This allows us to use pre-trained image classification CNNs as a base to fine-tune the defect detection CNN models … In this paper, we use a balanced training data set consisting of 28000 clean and 28000 non-clean tiles.”, and the annotated FIG. 4 below. Hanhirova teaches mapping the scan data of a cable surface to images, and using a CNN to identify cable surface defects from the images.)
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Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre, P&C Committee, and Lim by incorporating the CNN based system that is taught by Hanhirova, to make a cable inspection system that can detect defects using visual features; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to improve accuracy and automation of the task defect inspection (Hanhirova, page 198, section VII: “Our experiment results show that well-known pre-trained CNN models can effectively be fine-tuned to detect typical power cable surface defects. Our measurements show that with suitable system configuration the false positive rate can be limited near zero while defects can still be detected with high confidence.”).
The combination Andre, P&C Committee, Lim and Hanhirova then teaches identify a potential (Hanhirova, page 194, left col, third paragraph: “Not all scratches are critical, but the presence of any mechanical damage is an indication of potentially faulty equipment or a need of maintenance.”) anomalous condition (Hanhirova, page 195-196 section IV training: “we map the surface mesh data to grayscale images. This allows us to use pre-trained image classification CNNs as a base to fine-tune the defect detection CNN models … In this paper, we use a balanced training data set consisting of 28000 clean and 28000 non-clean tiles.”, see annotated FIG. 4 above. Hanhirova teaches mapping the scan data of a cable surface to images, and using a CNN to identify cable surface defects from the images) located at a first location of the wellbore power cable (Andre, ¶ [0032-0035]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter … The monitoring system may be configured to record the determined properties and/or parameters and/or location or position in a database associated with the identified line”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers), and wherein at least one feature of the one or more features is identified based on a visual appearance (Hanhirova, page 195-196 section IV training. The CNN identifies defects based on difference between visual features of clean cable and cable with defect) of at least a portion of the wellbore power cable. (Andre, ¶ [0032-0035]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter … The monitoring system may be configured to record the determined properties and/or parameters and/or location or position in a database associated with the identified line”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers)
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Claim(s) 7 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Andre in view of P&C Committee in view of Lim, and further in view of Zhou et al. (Zhou, Zhixiang, et al. "Surface damage detection for bridge cables based on YOLOv7." IEEE, published 2022, hereinafter Zhou).
CLAIM 7
In regards to Claim 7, the combination of Andre, P&C Committee, and Lim teaches the apparatus of Claim 1.
The combination of Andre, P&C Committee, and Lim does not explicitly disclose identify debris on cable surface.
Zhou is in the same field of art of detecting anomalous feature on cable surface. Further, Zhou teaches identify debris on cable surface. (Zhou, Abstract: “this paper proposes a surface damage detection method for bridge cables based on YOLOv7, a powerful real-time object detector. We introduce the basic algorithm of YOLOv7, and elaborate its training, transfer, and deployment methods for cable damage detection. A dataset is built containing 7548 cable damage images collected from real bridge cables. The results show that this method can effectively detect common bridge cable defects, including scratches, dirt, and abrasions”; pages 128-127, section III and IV. Zhou teaches a neural network YOLOv7 trained to detect dirt on cable surface. The Examiner notes without a definition of “wellbore debris”, the Examiner interprets “wellbore debris” includes dirt, the Examiner attaches a definition of “wellbore debris” from Google)
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Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre, P&C Committee, and Lim by incorporating the neural network YOLOv7 that is taught by Zhou, to make a cable inspection system that can detect dirt based on neural network; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to improve efficiency, objectivity and consistency of the task inspection (Zhou, Abstract: “The proposed approach is practically useful for assisting humans in data processing, reducing labor input significantly, and improving the objectivity and consistency of cable inspection”).
The combination of Andre, P&C Committee, Lim and Zhou then teaches identify locations of the cable (Andre, ¶ [0032-0035]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter … The monitoring system may be configured to record the determined properties and/or parameters and/or location or position in a database associated with the identified line”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers) that are covered by scaling or wellbore debris. (Zhou, Abstract: “this paper proposes a surface damage detection method for bridge cables based on YOLOv7, a powerful real-time object detector. We introduce the basic algorithm of YOLOv7, and elaborate its training, transfer, and deployment methods for cable damage detection. A dataset is built containing 7548 cable damage images collected from real bridge cables. The results show that this method can effectively detect common bridge cable defects, including scratches, dirt, and abrasions”; pages 128-127, section III and IV. Zhou teaches a neural network YOLOv7 trained to detect dirt on cable surface)
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
CLAIM 14
In regards to Claim 14, the combination of Andre, P&C Committee, and Lim teaches the method of Claim 8.
The combination of Andre, P&C Committee, and Lim does not explicitly disclose identify debris on cable surface.
Zhou is in the same field of art of detecting anomalous feature on cable surface. Further, Zhou teaches identify debris on cable surface. (Zhou, Abstract: “this paper proposes a surface damage detection method for bridge cables based on YOLOv7, a powerful real-time object detector. We introduce the basic algorithm of YOLOv7, and elaborate its training, transfer, and deployment methods for cable damage detection. A dataset is built containing 7548 cable damage images collected from real bridge cables. The results show that this method can effectively detect common bridge cable defects, including scratches, dirt, and abrasions”; pages 128-127, section III and IV. Zhou teaches a neural network YOLOv7 trained to detect dirt on cable surface. The Examiner notes without a definition of “wellbore debris”, the Examiner interprets “wellbore debris” includes dirt, the Examiner attaches a definition of “wellbore debris” from Google)
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Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Andre, P&C Committee, and Lim by incorporating the neural network YOLOv7 that is taught by Zhou, to make a cable inspection system that can detect dirt based on neural network; thus, one of ordinary skilled in the art would be motivated to combine the references since among its several aspects, the present invention recognizes there is a need to improve efficiency, objectivity and consistency of the task inspection (Zhou, Abstract: “The proposed approach is practically useful for assisting humans in data processing, reducing labor input significantly, and improving the objectivity and consistency of cable inspection”).
The combination of Andre, P&C Committee, Lim and Zhou then teaches identify locations of the cable (Andre, ¶ [0032-0035]: “The monitoring system may be configured to at least partially determine the integrity or condition or a risk of failure of, and/or damage, anomalies, wear or other changes in, the line or the parts or portions of the line, e.g. in the coating, by determining variations or changes in the at least one property of the line, for example, by comparison with the initial or calibration data and/or previously measured and/or determined values of the at least one property and/or operational parameter … The monitoring system may be configured to record the determined properties and/or parameters and/or location or position in a database associated with the identified line”; ¶ [0079-0081]: “one of the markers may indicate faults or defects” Andre teaches determining location of a damaged/defective portion of the line using markers) that are covered by scaling or wellbore debris. (Zhou, Abstract: “this paper proposes a surface damage detection method for bridge cables based on YOLOv7, a powerful real-time object detector. We introduce the basic algorithm of YOLOv7, and elaborate its training, transfer, and deployment methods for cable damage detection. A dataset is built containing 7548 cable damage images collected from real bridge cables. The results show that this method can effectively detect common bridge cable defects, including scratches, dirt, and abrasions”; pages 128-127, section III and IV. Zhou teaches a neural network YOLOv7 trained to detect dirt on cable surface)
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Allowable Subject Matter
Claims 6, 13 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Pertinent Arts
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Melo et al. (US-20230296015-A1, cited in IDS) which is directed to a diagnostics and control system (DCS) for an artificial lift system (ALS) in a well, comprising: a sensor network comprising a plurality of sensors for monitoring and obtaining measurements at a power source of the ALS and at a downhole pump of the ALS; wherein a condition of the ALS is evaluated by the permanent local wellsite monitor using the processed sensor data, testing results and system performance data to monitor a health of the ALS. In addition, Melo teaches performing Failure location test, which can locates a damaged portion of a power cable.
Conclusion
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/NHUT HUY PHAM/Examiner, Art Unit 2674
/ONEAL R MISTRY/Supervisory Patent Examiner, Art Unit 2674
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