Systems and methods for drilling fluids expert systems using bayesian decision networks
First Claim
Patent Images
1. A system, comprisingone or more processors;
- a non-transitory tangible computer-readable memory, the memory comprising;
a drilling fluids expert system executable by the one or more processors and configured to provide one or more drilling fluids recommendations based on one or more inputs, the drilling fluids expert system comprising a drilling fluids Bayesian decision network (BDN) model, the drilling fluids BDN model comprisinga temperature ranges uncertainty node configured to receive one or more temperature ranges from the one or more inputs, each of the one or more temperature ranges associated with a respective one or more temperature range probabilities;
a formations uncertainty node configured to receive one or more formations from the one or more inputs, each of the one or more formations associated with a respective one or more formation probabilities;
a potential hole problems uncertainty node dependent on the formations uncertainty node and configured to receive one or more potential hole problems from the one or more inputs and the one or more formation probabilities, each of the one or more potential hole problems associated with a respective one or more potential hole problem probabilities;
a drilling fluids decision node configured to receive one or more drilling fluids from the one or more inputs; and
a consequences node dependent on the temperature ranges uncertainty node, the potential hole problems uncertainty node, and the drilling fluids decision node and configured to output the one or more drilling fluids recommendations based on one or more Bayesian probabilities calculated from the one or more temperature ranges and the one more temperature range probabilities, the one or more potential hole problems and the one or more potential hole problem probabilities, and the one or more drilling fluids.
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Abstract
Provided are systems and methods for drilling fluids expert systems using Bayesian decision networks to determine drilling fluid recommendations. A drilling fluids expert system includes a drilling fluids Bayesian decision network (BDN) model that receives inputs and outputs recommendations based on Bayesian probability determinations. The drilling fluids BDN model includes a temperature ranges uncertainty node, a formation uncertainty node, a potential hole problems uncertainty node, and a drilling fluids decision node.
25 Citations
20 Claims
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1. A system, comprising
one or more processors; a non-transitory tangible computer-readable memory, the memory comprising; a drilling fluids expert system executable by the one or more processors and configured to provide one or more drilling fluids recommendations based on one or more inputs, the drilling fluids expert system comprising a drilling fluids Bayesian decision network (BDN) model, the drilling fluids BDN model comprising a temperature ranges uncertainty node configured to receive one or more temperature ranges from the one or more inputs, each of the one or more temperature ranges associated with a respective one or more temperature range probabilities; a formations uncertainty node configured to receive one or more formations from the one or more inputs, each of the one or more formations associated with a respective one or more formation probabilities; a potential hole problems uncertainty node dependent on the formations uncertainty node and configured to receive one or more potential hole problems from the one or more inputs and the one or more formation probabilities, each of the one or more potential hole problems associated with a respective one or more potential hole problem probabilities; a drilling fluids decision node configured to receive one or more drilling fluids from the one or more inputs; and a consequences node dependent on the temperature ranges uncertainty node, the potential hole problems uncertainty node, and the drilling fluids decision node and configured to output the one or more drilling fluids recommendations based on one or more Bayesian probabilities calculated from the one or more temperature ranges and the one more temperature range probabilities, the one or more potential hole problems and the one or more potential hole problem probabilities, and the one or more drilling fluids. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A computer-implemented method for a drilling fluids expert system having a drilling fluids Bayesian decision network (BDN) model, the method comprising:
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receiving, at one or more processors, one or more inputs; providing, by one or more processors, the one or more inputs to one or more nodes of the drilling fluids BDN model, the one or more nodes comprising; a temperature ranges uncertainty node configured to receive one or more temperature ranges from the one or more inputs, each of the one or more temperature ranges associated with a respective one or more temperature range probabilities; a formations uncertainty node configured to receive one or more formations from the one or more inputs each of the one or more formations associated with a respective one or more formation probabilities; a potential hole problems uncertainty node dependent on the formations uncertainty node and configured to receive one or more potential hole problems from the one or more inputs and the one or more formation probabilities, each of the one or more potential hole problems associated with a respective one or more potential hole problem probabilities; a drilling fluids decision node; and a consequences node dependent on the temperature ranges uncertainty node, the potential hole problems uncertainty node, and the drilling fluids decision node; determining, at one or more processors, one or more drilling fluids recommendations at the consequences node of the drilling fluids BDN model, the determination comprising a calculation of one or more Bayesian probabilities based on the one or more inputs; and providing, by one or more processors, the one or more drilling fluids recommendations to a user. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17)
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18. A computer-implemented method of determining a drilling fluid formulation for a drilling system, the method comprising:
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receiving, at one or more processors, an input from a user, the input comprising a temperature range, a formation, a potential hole problem, or any combination thereof; providing, by one or more processors, the input to a drilling fluids Bayesian decision network (BDN) model configured to receive one or more drilling fluid formulations; determining, by one or more processors, an expected utility value for the one or more drilling fluid formulations based on the input, the determination comprising a calculation of one or more Bayesian probabilities for the one or more drilling fluid formulations based on the input; and providing, by one or more processors, an output from the drilling fluids BDN model, the output comprising one or more recommended drilling fluid formulations selected from the one or more drilling fluid formulations. - View Dependent Claims (19, 20)
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Specification