Borehole drilling optimization with multiple cutting structures
AssigneeSmith International, Inc.
InventorsArifin Purwanto, David P. Moran, Lei Yan
Life of this patent
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Abstract
A method of optimizing a drilling operating parameter or a drilling system parameter for a drilling assembly employing at least first and second distinct cutting structures includes entering at least one design parameter for each of the cutting structures into a trained artificial neural network. At least one of the design parameters of the first cutting structure may be optionally combined with at least one of the design parameters of the second cutting structure. The combined design parameter may also be entered into the artificial neural network.
Claims24
A method for optimizing a drilling operating parameter for a drilling system, the method comprising:
- (a) entering a plurality of drilling system design parameters into a trained artificial neural network, the drilling system including first and second longitudinally spaced cutting structures on a single drill string, the design parameters including design parameters for the first cutting structure and design parameters for the second cutting structure, and processing at least one the design parameters of the first cutting structure in combination with at least one the design parameters of the second cutting structure to obtain at least one combined design parameter;
- and entering the at least one combined design parameter into the trained artificial neural network;
- (b) entering at least one property of an earth formation to be drilled by the drilling system into the trained artificial neural network;
- (c) entering at least one drilling operating parameter into the trained artificial network;
- and
- (d) adjusting a value of the at least one drilling operating parameter in response to an output of the trained artificial neural network so as to optimize said drilling operating parameter.
A method for optimizing a drilling system, the method comprising:
- (a) entering a plurality of drilling system design parameters into a trained artificial neural network, the drilling system including first and second longitudinally spaced cutting structures on a single drill string, the design parameters including design parameters for the first cutting structure and design parameters for the second cutting structure and processing at least one the design parameters of the first cutting structure in combination with at least one the design parameters of the second cutting structure to obtain at least one combined design parameter;
- and entering the at least one combined design parameter into the trained artificial neural network;
- (b) entering at least one property of an earth formation to be drilled by the drilling system into the trained artificial neural network;
- (c) entering at least one drilling operating parameter into the trained artificial neural network;
- and
- (d) adjusting values of the drilling system design parameters, including design parameters of the first and second longitudinally spaced cutting structures, in response to an output of the trained artificial neural network so as to optimize the drilling system design parameters.
A method for training an artificial neural network, the method comprising:
- (a) providing an artificial neural network;
- (b) selecting training data from at least one previously drilled borehole, the training data including corresponding values of a plurality of drilling system design parameters, the drilling system design parameters including, at least one design parameter for a first cutting structure and at least one design parameter for a second cutting structure, where the first cutting structure and second cutting structure are located on a single drill string, and wherein the at least one of the design parameters of the first cutting structure comprises a first cutting area;
- the at least one of the design parameters of the second cutting structure comprises a second cutting area;
- and the at least one combined design parameter comprises a ratio of the first cutting area to the second cutting area;
- (c) processing the at least one design parameter of the first cutting structure in combination with the at least one design parameter of the second cutting structure to obtain at least one combined design parameter;
- (d) entering the at least one combined design parameter into the artificial neural network;
- and
- (e) adjusting the at least one combined design parameter in response to an output of the artificial neural network.
A method for optimizing a drilling operating parameter, for a drilling system, the method comprising:
- (a) acquiring a plurality of drilling system design parameters, the drilling system including first and second longitudinally spaced cutting structures on a single drill string, the design parameters including at least one design parameter for the first cutting structure and at least one design parameter for the second cutting structure;
- (b) processing the at least one design parameter of the first cutting structure in combination with the at least one design parameter of the second cutting structure to obtain at least one combined design parameter, wherein the combined design parameter comprises a ratio of a first cutting area corresponding to the first cutting structure to a second cutting area corresponding to the second cutting structure;
- (c) entering the at least one combined design parameter into a trained artificial neural network;
- (d) entering at least one property of an earth formation to be drilled by the drilling system into the trained artificial neural network;
- (e) entering at least one drilling operating parameter into the trained artificial neural network;
- and
- (f) adjusting a value of the at least one drilling operating parameter in response to an output of the trained artificial neural network so as to optimize said drilling operating parameter.
Dependencies are inferred from the claim text.