Method of training neural network models and using same for drilling wellbores
First Claim
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1. A method of operating a tool in a wellbore, comprising:
- defining at least one value of at least one tool parameter,defining a plurality of values of at least one wellbore parameter,using the at least one value of the at least one tool parameter and the plurality of values of the at least one wellbore parameter as inputs to a selected model to estimate a bending moment of the tool;
obtaining an expected value of the bending moment by inputting into the neural network model the defined plurality of values of the at least one wellbore parameter and the estimated bending moment of the tool; and
comparing the expected value of bending moment of the tool obtained from the neural network model to the estimated bending moment of the tool obtained from the selected model to train the neutral network;
using the obtained neural network model to operate the tool in the wellbore.
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Abstract
A method of creating and using a neural network model for wellbore operations is disclosed. The method, in one aspect, may include defining a plurality of a wellbore parameter; calculating a plurality of output values of a tool operating parameter using the plurality of values of the wellbore parameter as input to a preexisting model; and obtaining a neural network model by using the plurality of values of the wellbore parameter and the calculated plurality of output values of the tool operating parameter. The neural network may be utilized for any suitable wellbore operation, including in conjunction with a drilling assembly for drilling a wellbore.
48 Citations
22 Claims
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1. A method of operating a tool in a wellbore, comprising:
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defining at least one value of at least one tool parameter, defining a plurality of values of at least one wellbore parameter, using the at least one value of the at least one tool parameter and the plurality of values of the at least one wellbore parameter as inputs to a selected model to estimate a bending moment of the tool; obtaining an expected value of the bending moment by inputting into the neural network model the defined plurality of values of the at least one wellbore parameter and the estimated bending moment of the tool; and comparing the expected value of bending moment of the tool obtained from the neural network model to the estimated bending moment of the tool obtained from the selected model to train the neutral network; using the obtained neural network model to operate the tool in the wellbore. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. An apparatus for use in a well bore, comprising:
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a drilling assembly configured to drill the wellbore; a data storage medium; a neural network model stored in the data storage medium, which neural network model is created by; obtaining a bending moment of the drilling assembly by using as input to a selected model at least one value of at least one tool parameter and a plurality of values of at least one well bore parameter, and obtaining an expected value of the bending moment of the drilling assembly by inputting into the neural network mode! the plurality of values of the at least one well bore parameter and the estimated bending moment of the drilling assembly, and comparing the expected value of the bending moment of the drilling assembly obtained from the neural network model to bending moment of the drilling assembly obtained from the selected model to train the neural network; and a processor configured to use the trained neural network to operate the drilling assembly in the wellbore. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22)
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Specification