CTNF 18/422,207 CTNF 89590 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. Claims 1-24 are pending. Claim Rejections - 35 USC § 112 07-30-02 AIA 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. 07-34-01 Claims 1-24 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. 07-34-05 AIA Claim 1 recites the limitation " the production index " in line 1 . There is insufficient antecedent basis for this limitation in the claim. 07-34-05 AIA Claim 10 recites the limitation " the production index " in line 1 . There is insufficient antecedent basis for this limitation in the claim. 07-34-05 AIA Claim 19 recites the limitation " the production index " in line 2 . There is insufficient antecedent basis for this limitation in the claim. 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. Claim 1 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: The claim recites a method, which fall within a statutory category. Step 2A Prong one: claim 1 recites steps of “processing the plurality of parameters and respective values to obtain a training dataset and testing dataset”; “fuzzifying the training dataset, the fuzzifying comprising: creating a plurality of fuzzy sets, each fuzzy set comprising a plurality of fuzzy inputs; and creating a plurality of rules that produce a plurality of fuzzy values for a production index from the plurality of fuzzy inputs”; “determine a production index for the selected well from a second plurality of parameters and respective values associated with the selected well”. As is evident from the background, the claimed steps fall into the “mental process” group of abstract ideas, because the recited calculation and determination can be practically performed in the human mind. Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited calculation and determination, the use of such physical aid does not negate the mental nature of this limitation. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Step 2A Prong two: Besides the abstract ideas, the claim recites additional limitations “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model”. The additional limitations represent mere gathering data and training neural network model that is necessary for use of the recited judicial exception and is recited at a high level of generality. Limitations “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” in the claim is thus insignificant extra-solution activity. The claim does not recite additional elements that integrate the judicial exception into a practical application. Accordingly, the additional limitations do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Step 2B: The claim as a whole does not amounts to significantly more than the recited exception. The additional limitations of “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” represent mere gathering data and training neural network model are recited at a high level of generality, and, as disclosed in the specification, is also well-known. These limitations therefore remain insignificant extra-solution activity even upon reconsideration. Thus, limitation “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” do not amount to significantly more. The claim does not recite any additional elements that amounts to significantly more than the judicial exception. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible. Claim 10 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: The claim recites a non-transitory computer readable storage medium, which fall within a statutory category. Step 2A Prong one: claim 10 recites steps of “processing the plurality of parameters and respective values to obtain a training dataset and testing dataset”; “fuzzifying the training dataset, the fuzzifying comprising: creating a plurality of fuzzy sets, each fuzzy set comprising a plurality of fuzzy inputs; and creating a plurality of rules that produce a plurality of fuzzy values for a production index from the plurality of fuzzy inputs”; “determine a production index for the selected well from a second plurality of parameters and respective values associated with the selected well”. As is evident from the background, the claimed steps fall into the “mental process” group of abstract ideas, because the recited calculation and determination can be practically performed in the human mind. Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited calculation and determination, the use of such physical aid does not negate the mental nature of this limitation. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Step 2A Prong two: Besides the abstract ideas, the claim recites additional limitations “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model”. The additional limitations represent mere gathering data and training neural network model that is necessary for use of the recited judicial exception and is recited at a high level of generality. Limitations “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” in the claim is thus insignificant extra-solution activity. The claim does not recite additional elements that integrate the judicial exception into a practical application. Accordingly, the additional limitations do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Step 2B: The claim as a whole does not amounts to significantly more than the recited exception. The additional limitations of “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” represent mere gathering data and training neural network model are recited at a high level of generality, and, as disclosed in the specification, is also well-known. These limitations therefore remain insignificant extra-solution activity even upon reconsideration. Thus, limitation “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” do not amount to significantly more. The claim does not recite any additional elements that amounts to significantly more than the judicial exception. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible. Claim 19 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: The claim recites a system, which fall within a statutory category. Step 2A Prong one: claim 19 recites steps of “processing the plurality of parameters and respective values to obtain a training dataset and testing dataset”; “fuzzifying the training dataset, the fuzzifying comprising: creating a plurality of fuzzy sets, each fuzzy set comprising a plurality of fuzzy inputs; and creating a plurality of rules that produce a plurality of fuzzy values for a production index from the plurality of fuzzy inputs”; “determine a production index for the selected well from a second plurality of parameters and respective values associated with the selected well”. As is evident from the background, the claimed steps fall into the “mental process” group of abstract ideas, because the recited calculation and determination can be practically performed in the human mind. Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited calculation and determination, the use of such physical aid does not negate the mental nature of this limitation. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Step 2A Prong two: Besides the abstract ideas, the claim recites additional limitations “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model”. The additional limitations represent mere gathering data and training neural network model that is necessary for use of the recited judicial exception and is recited at a high level of generality. Limitations “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” in the claim is thus insignificant extra-solution activity. The additional elements “a processor” and “a non-transitory computer-readable memory” in both steps is recited at a high-level of generality (i.e., as a generic component performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Step 2B: The claim as a whole does not amounts to significantly more than the recited exception. The additional limitations of “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” represent mere gathering data and training neural network model are recited at a high level of generality, and, as disclosed in the specification, is also well-known. These limitations therefore remain insignificant extra-solution activity even upon reconsideration. Thus, limitation “obtaining a first plurality of parameters and respective values associated with one or more producing wells; training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model and using the trained fuzzy-neural model” do not amount to significantly more. The additional elements “a processor” and “a non-transitory computer-readable memory” in both steps is recited at a high-level of generality (i.e., as a generic component performing a generic computer function) such that it amounts 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. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible. Claim 2 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 2 recites step of “processing the plurality of parameters and respective values comprising normalizing the plurality of respective values to a range”, the step cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. The claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 3 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 3 recites information regarding “the first plurality of parameters comprise a plurality of reservoir properties”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 4 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 4 recites information regarding “the first plurality of parameters comprise a plurality of well characteristics”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 5 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 5 recites information regarding “the first plurality of parameters comprise a production rate”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 6 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 6 recites additional element “the neural network comprises a feed-forward neural network”. This judicial exception is not integrated into a practical application because the additional element is recited at a high-level of generality (i.e., as a generic computing system for performing a generic function, which is insignificant extra-solution activity) such that it amounts no more than mere instructions to apply the exception using a generic component. Accordingly, the additional element do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Claim 7 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 7 recites steps of “evaluating the fuzzy-neural model before using the trained fuzzy-neural model to determine a production index for the selected well, wherein evaluating the fuzzy-neural model comprises: calculating a metric between a production index produced by the fuzzy-neural model and a production index in the training data, wherein the metric comprises a mean absolute error, a mean squared error, or a root mean squared error”, the steps cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. The claim lacks any additional elements which may serve to integrate it into a practical application or amount to significantly more than the abstract idea itself. Claim 8 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 8 recites steps of “adjusting the fuzzy-neural model based on the evaluation of the fuzzy-neural model, wherein adjusting the fuzzy-neural model comprises modifying the neural network, tuning a hyperparameter of the neural network, or modifying the plurality of rules”, the steps cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. The claim lacks any additional elements which may serve to integrate it into a practical application or amount to significantly more than the abstract idea itself. Claim 9 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 9 recites step of “determining, based on production index, an operating parameter for the producing well”, the step cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Dependent Claim 9 also recites additional element “operating the hydrocarbon well in accordance with the operating parameter”. This judicial exception is not integrated into a practical application because the additional elements is recited at a high-level of generality (i.e., as a generic system performing a generic function) such that it amounts no more than mere instructions to apply the exception using a generic component and it amounts no more than mere instructions to apply the exception using a generic component. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim as a whole does not amounts to significantly more than the recited exception, mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible. Claim 11 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 11 recites step of “processing the plurality of parameters and respective values comprising normalizing the plurality of respective values to a range”, the step cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. The claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 12 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 12 recites information regarding “the first plurality of parameters comprise a plurality of reservoir properties”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 13 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 13 recites information regarding “the first plurality of parameters comprise a plurality of well characteristics”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 14 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 14 recites information regarding “the first plurality of parameters comprise a production rate”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 15 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 15 recites additional element “the neural network comprises a feed-forward neural network”. This judicial exception is not integrated into a practical application because the additional element is recited at a high-level of generality (i.e., as a generic computing system for performing a generic function, which is insignificant extra-solution activity) such that it amounts no more than mere instructions to apply the exception using a generic component. Accordingly, the additional element do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Claim 16 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 16 recites steps of “evaluating the fuzzy-neural model before using the trained fuzzy-neural model to determine a production index for the selected well, wherein evaluating the fuzzy-neural model comprises: calculating a metric between a production index produced by the fuzzy-neural model and a production index in the training data, wherein the metric comprises a mean absolute error, a mean squared error, or a root mean squared error”, the steps cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. The claim lacks any additional elements which may serve to integrate it into a practical application or amount to significantly more than the abstract idea itself. Claim 17 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 17 recites steps of “adjusting the fuzzy-neural model based on the evaluation of the fuzzy-neural model, wherein adjusting the fuzzy-neural model comprises modifying the neural network, tuning a hyperparameter of the neural network, or modifying the plurality of rules”, the steps cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. The claim lacks any additional elements which may serve to integrate it into a practical application or amount to significantly more than the abstract idea itself. Claim 18 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 18 recites step of “determining, based on production index, an operating parameter for the producing well”, the step cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Dependent Claim 9 also recites additional element “operating the hydrocarbon well in accordance with the operating parameter”. This judicial exception is not integrated into a practical application because the additional elements is recited at a high-level of generality (i.e., as a generic system performing a generic function) such that it amounts no more than mere instructions to apply the exception using a generic component and it amounts no more than mere instructions to apply the exception using a generic component. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim as a whole does not amounts to significantly more than the recited exception, mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible. Claim 20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 20 recites step of “processing the plurality of parameters and respective values comprising normalizing the plurality of respective values to a range”, the step cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. The claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 21 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 21 recites information regarding “the first plurality of parameters comprise a plurality of reservoir properties”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 22 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 2 recites information regarding “the first plurality of parameters comprise a plurality of well characteristics”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 23 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 23 recites information regarding “the first plurality of parameters comprise a production rate”, the claim lacks any additional elements which may serve to integrate it into a practical application and amount to significantly more than the abstract idea itself. The claim is not eligible subject matter under 35 U.S.C. 101. Claim 24 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Dependent Claim 24 recites step of “determining, based on production index, an operating parameter for the producing well”, the step cover performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation under its broadest reasonable interpretation covers performance of the limitation in the mind but for the recitation of generic computer components then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Dependent Claim 9 also recites additional element “operating the hydrocarbon well in accordance with the operating parameter”. This judicial exception is not integrated into a practical application because the additional elements is recited at a high-level of generality (i.e., as a generic system performing a generic function) such that it amounts no more than mere instructions to apply the exception using a generic component and it amounts no more than mere instructions to apply the exception using a generic component. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim as a whole does not amounts to significantly more than the recited exception, mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not 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. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim (s) 1-5, 7-8, 10-14, 16-17, 19-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (hereinafter “Chen”) (US 20040133531 A1) in view of HE et al. (hereinafter “HE”) (CN 115936465 A) . As to claims 1, 10, and 19, Chen teaches a system and method for analyzing a selected well, comprises: obtaining a first plurality of parameters and respective values associated with one or more producing wells ([0015, 0077-0089] input data is multidimensional geophysical data. The input data is divided into subsets and clustering methods are used to divide each subset into a plurality of clusters... Measurements from two or more instruments in the same well may be depth correlated and combined to form a set of input data parameters…Other types of data such as measurements of formation samples, e.g. drill cuttings or sidewall cores, may also be used. The input data may also include measurements taken from the earth's surface, e.g. seismic data, which may be depth correlated with borehole log data. In similar fashion, the actual target data used in training may be data from more than one logging tool and/or may include non-borehole data such as seismic data. Predicted target measurements may likewise be the types of measurements normally measured by a logging tool or data normally measured by other means, e.g. seismic); processing the plurality of parameters and respective values to obtain a training dataset and testing dataset ([Fig. 1 and paragraphs 0029-0034, 0038 show how data clusters are generated for training data selection] [0044-0046 demonstrate test data selected from testing well]); fuzzifying the training dataset ([0039] Fuzzy inference is the process of formulating the mapping from a given input to an output using fuzzy logic… In a preferred embodiment, a fuzzy inference system is used to receive inputs from the cluster characterization process, and produce an output equal to the percentage of data to be used for training in each cluster), the fuzzifying comprising: creating a plurality of fuzzy sets, each fuzzy set comprising a plurality of fuzzy inputs; and creating a plurality of rules that produce a plurality of fuzzy values for a production index from the plurality of fuzzy inputs ([0039-0043] In the step of fuzzification, the system receives the crisp input of each variable, and converts it to fuzzy input, which is a degree of satisfaction defined by the adaptive membership function. In the step of logic-operation, logical AND and OR operations are performed to represent the antecedent of each fuzzy rule, and its consequence is obtained in the step of implication. The outputs of the multiple rules are then aggregated in the step of aggregation to form a fuzzy set. Finally, for a given cluster, a single number is calculated at step 36 from the defuzzification step to indicate a percentage of the samples to be used in the training set); training a neural network using the plurality of a fuzzy values for the production index to create a fuzzy-neural model ([0004, 0044] This invention relates to neural networks trained to predict a parameter in response to a plurality of inputs, and more particularly to methods of using clustering techniques and fuzzy inference to select geophysical data for use in training a neural network to produce synthetic data…The percentages determined at step 36 are used to select a portion of data from each cluster 24. The data selected from each cluster 24 is combined into a training data set to be used to train a model for predicting the target data from real input data. As indicated above, a preferred embodiment uses an artificial neural network, ANN, as the predictive model… the training data selection process of the present invention results in a reduced training set which allows use of preferred training algorithms for training an ANN. After training and validation, the ANN may be tested with input data from other wells to determine if the model is good enough. When a model has been shown to accurately predict, or generate artificial logs, e.g. open hole logs, from real input data, for example cased hole log data, then it may be used to generate such artificial logs for other wells); using the trained fuzzy-neural model to determine a target data for the selected well from a second plurality of parameters and respective values associated with the selected well ([0018-0019, 0044, 0074] the model is an artificial neural network trained to predict, or generate artificial, logging data as target data, in response to an input of actual logging data… The data selected from each cluster 24 is combined into a training data set to be used to train a model for predicting the target data from real input data… The log may include good data for the other parameters. In such a case, the parameters with good data can be used as the inputs for model training, and the parameter(s) which are partially missing or defective can be used as target data for training. The good parameters in the zones with defective data can then be input to the trained model to provide synthetic values for the missing parameters in the defective zones). Chen teaches a system and method for analyzing a selected well by using clustering techniques and fuzzy inference to select geophysical data for use in training a neural network to predict target data for the selected well [0014-0019]. Chen does not explicitly teach the target data is a production index for the selected well. However, HE teaches a system and method for analyzing oil-gas reservoir, more specifically, for predicting critical yield of carbonate rock seam cave-type bottom water reservoir cone. Such that by using fuzzy clustering analysis method and BP artificial neural network method to calculate carbonate rock hole bottom water oil reservoir water cone critical yield critical yield, wherein the water cone critical yield is a production index for the selected well ([Abstract, pages 6-7] selecting the carbonate rock seam hole type bottom water reservoir in the development of 25 well as fuzzy clustering analysis sample well for fuzzy clustering analysis prediction water cone critical yield… selecting the sample well for BP neural network critical yield prediction… using the BP artificial neural network of Table 5 critical yield prediction sample well parameter, by adjusting BP artificial neural network hidden layer number and node number… using the established BP artificial neural network model to calculate the 15-port pre-logging, so as to obtain the water cone critical yield of BP artificial neural network). Chen and HE are analogous art because they are from the same field of endeavor of analyzing wells by using fuzzy clustering analysis method and neural network method to obtain target data to improve the operation of the wells. At the time before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to determine a production index value as the target data. The suggestion for doing so would have been obvious to determine different target data from the wells using fuzzy clustering analysis method and neural network method. Therefore, it would have been obvious to an ordinary person skilled in the art before the effective filing date of the invention to incorporate the teachings of HE with the teachings of Chen for the purpose of determining the target data is a production index for the selected well as specified in the claims 1, 10, and 19. As to claims 2, 11, and 20, Chen teaches processing the plurality of parameters and respective values comprising normalizing the plurality of respective values to a range [0010, 0033-0035, 0056]. As to claims 3, 12, and 21, Chen teaches the first plurality of parameters comprise a plurality of reservoir properties [0037, 0077-0090]. As to claims 4, 13, and 22, Chen teaches the first plurality of parameters comprise a plurality of well characteristics [0015, 0077-0089]. As to claims 5, 14, and 23, HE teaches the first plurality of parameters comprise a production rate [pages 4, 6-7]. As to claims 7 and 16, Chen teaches evaluating the fuzzy-neural model before using the trained fuzzy-neural model to determine a production index for the selected well, wherein evaluating the fuzzy-neural model comprises: calculating a metric between a production index produced by the fuzzy-neural model and a production index in the training data, wherein the metric comprises a mean absolute error, a mean squared error, or a root mean squared error [0039-0046, 0048]. As to claims 8 and 17, Chen teaches adjusting the fuzzy-neural model based on the evaluation of the fuzzy-neural model, wherein adjusting the fuzzy-neural model comprises modifying the neural network, tuning a hyperparameter of the neural network, or modifying the plurality of rules [0039-0046, 0048] . 07-21-aia AIA Claim (s) 6, 9, 15, 18, and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen in view of HE, and further in view of Katterbauer et al. (hereinafter “Katterbauer”) (US 20240052734 A1) . As to claims 6 and 15, Chen teaches using clustering techniques and fuzzy inference to select geophysical data for use in training a neural network to produce synthetic data [Abstract, 0004]. Chen does not explicitly teach the neural network comprises a feed-forward neural network. However, Katterbauer teaches a system and method for determining a sweep efficiency within a hydrocarbon reservoir, by using trained machine learning network models, to improve the amount of hydrocarbon that would otherwise be recovered. Especially, Katterbauer teaches the neural network comprises a feed-forward neural network [0004-0008, 0081]. It would have been obvious to an ordinary person skilled in the art before the effective filing date of the invention to incorporate the teachings of Katterbauer with the teachings of Chen and HE for the purpose of using a feed-forward neural network to determine target data from a hydrocarbon reservoir. As to claim 9, 18, and 24, Katterbauer teaches determining, based on production index, an operating parameter for the producing well; and operating the hydrocarbon well in accordance with the operating parameter [0008, 0105, 0109-0113]. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHIPENG WANG whose telephone number is (571)272-5437. The examiner can normally be reached Monday-Friday 10-7. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached at 5712722279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. 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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. /ZHIPENG WANG/Primary Examiner, Art Unit 2115 Application/Control Number: 18/422,207 Page 2 Art Unit: 2115 Application/Control Number: 18/422,207 Page 3 Art Unit: 2115 Application/Control Number: 18/422,207 Page 4 Art Unit: 2115 Application/Control Number: 18/422,207 Page 5 Art Unit: 2115 Application/Control Number: 18/422,207 Page 6 Art Unit: 2115 Application/Control Number: 18/422,207 Page 7 Art Unit: 2115 Application/Control Number: 18/422,207 Page 8 Art Unit: 2115 Application/Control Number: 18/422,207 Page 9 Art Unit: 2115 Application/Control Number: 18/422,207 Page 10 Art Unit: 2115 Application/Control Number: 18/422,207 Page 11 Art Unit: 2115 Application/Control Number: 18/422,207 Page 12 Art Unit: 2115 Application/Control Number: 18/422,207 Page 13 Art Unit: 2115 Application/Control Number: 18/422,207 Page 14 Art Unit: 2115 Application/Control Number: 18/422,207 Page 15 Art Unit: 2115 Application/Control Number: 18/422,207 Page 16 Art Unit: 2115 Application/Control Number: 18/422,207 Page 17 Art Unit: 2115 Application/Control Number: 18/422,207 Page 18 Art Unit: 2115 Application/Control Number: 18/422,207 Page 19 Art Unit: 2115 Application/Control Number: 18/422,207 Page 20 Art Unit: 2115 Application/Control Number: 18/422,207 Page 21 Art Unit: 2115 Application/Control Number: 18/422,207 Page 22 Art Unit: 2115 Application/Control Number: 18/422,207 Page 23 Art Unit: 2115 Application/Control Number: 18/422,207 Page 24 Art Unit: 2115 Application/Control Number: 18/422,207 Page 25 Art Unit: 2115 Application/Control Number: 18/422,207 Page 26 Art Unit: 2115 Application/Control Number: 18/422,207 Page 27 Art Unit: 2115
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