Systems and methods for an expert system for well control using Bayesian intelligence

Patent metadata

Field	Value
Publication number	US-9202175-B2
Application number	US-201313827794-A
Country	US
Kind code	B2
Filing date	Mar 14, 2013
Priority date	Nov 2, 2012
Publication date	Dec 1, 2015
Grant date	Dec 1, 2015

Abstract

Systems and methods are provided for a well control expert system that provides well control recommendations for a drilling system. The well control expert system includes a well control Bayesian decision network (BDN) model that receives inputs and outputs recommendations based on Bayesian probability determinations. The well control BDN model includes a circulation section, a well control practices section, and a troubleshooting section.

First claim

What is claimed is:

1. A system, comprising:
one or more processors;
a non-transitory tangible computer-readable memory, the memory comprising:
a well control expert system executable by the one or more processors and configured to provide one or more well control recommendations based on one or more inputs, the well control expert system comprising a well control Bayesian decision network (BDN) model, the well control BDN model comprising:
a kick indicators uncertainty node configured to receive one or more kick indicators from the one or more inputs;
a kick verifications uncertainty node dependent on the kick indicators uncertainty node and configured to receive one or more kick verifications from the one or more inputs;
a kick details uncertainty node dependent on the kick verifications uncertainty node and configured to receive one or more kick details from the one or more inputs;
a circulations decision node configured to receive one or more circulations from the one or more inputs;
a circulations consequences node dependent on the kick details uncertainty node and the circulations decision node and configured to output the one or more well control recommendations based on one or more Bayesian probabilities calculated from one or more kick details and the one or more circulations; and

a well control practices consequences node dependent on (a) a well control scenarios uncertainty node, (b) a well control operations uncertainty node, and (c) a recommended practices decision node, the well control practices consequences node being configured to output the one or more well control recommendations based on one or more Bayesian probabilities calculated from:
one or more well control scenarios input to the well control uncertainty node,
one or more well control operations input to the well control operations uncertainty node, and
one or more recommended practices input to the recommended practices decision node.

2. The system of claim 1 , further comprising a user interface configured to display the well control BDN model and receive user selections of the one or more inputs.

3. The system of claim 1 , wherein the one or more kick indicators, the one or more kick verifications phases, and the one or more kick details are each associated with a respective plurality of probabilities.

4. The system of claim 1 , wherein the well control BDN model comprises:
a troubleshooting solutions consequences node dependent on a well control problems uncertainty node and a troubleshooting solutions decision node, wherein the troubleshooting solutions consequences node is configured to output the one or more well control recommendations based on one or more Bayesian probabilities calculated from one or more well control problems input to the well control problems uncertainty node and one or more troubleshooting solutions input to the troubleshooting decisions node.

5. A method for a well control expert system having a well control Bayesian decision network (BDN) model, the method comprising:
receiving one or more inputs;
providing the one or more inputs to one or more nodes of a well control BDN model, the one or more nodes comprising:
a kick indicators uncertainty node;
a kick verifications uncertainty node dependent on the kick indicators uncertainty node;
a kick details uncertainty node dependent on the kick verifications uncertainty node; and
a circulations decision node;

determining one or more well control recommendations at a second consequences node of the well control BDN model, the determination comprising a calculation of one or more Bayesian probabilities based on the one or more inputs, the one or more inputs provided to: (a) a well control scenarios uncertainty node, (b) a well control operations uncertainty node dependent on the well control scenarios uncertainty node, and (c) a recommended practices decisions node; and
providing the one or more well control recommendations to a user.

6. The method of claim 5 , wherein providing the one or more well control recommendations to a user comprises displaying the one or more well control recommendations in a user interface element of a user interface configured to display the well control BDN model.

7. The method of claim 5 , comprising determining the one or more well control recommendations at a third consequences node of the well control BDN model, the determination comprising a calculation of one or more Bayesian probabilities based on the one or more inputs, wherein the one or inputs are provided to a troubleshooting checklists uncertainty node, an actions and results uncertainty node dependent on the troubleshooting checklists uncertainty node, a well control problems uncertainty node dependent on the actions and results uncertainty node, and a troubleshooting solutions decision node.

8. A system, comprising:
one or more processors;
a non-transitory tangible computer-readable memory, the memory comprising:
a well control expert system executable by the one or more processors and configured to provide one or more well control recommendations based on one or more inputs, the well control expert system comprising a well control Bayesian decision network (BDN) model, the well control BDN model comprising:
a well control scenarios uncertainty node configured to receive one or more well control scenarios from the one or more inputs;
a well control operations uncertainty node dependent on the well control scenarios uncertainty node and configured to receive one or more well control operations from the one or more inputs;
a recommended practices decision node configured to receive one or more recommended practices from the one or more inputs;
a circulations consequences node dependent on a kick details uncertainty node and a circulations decision node and configured to output the one or more well control recommendations based on one or more Bayesian probabilities calculated from one or more kick details input to the kick details uncertainty node and one or more circulations input to the circulations decision node;
a troubleshooting solutions consequences node dependent on a well control problems uncertainty node and a troubleshooting solutions decision node, the troubleshooting solutions consequences node being configured to output the one or more well control recommendations based on one or more Bayesian probabilities calculated from one or more well control problems input to the well control problems uncertainty node and one or more troubleshooting solutions input to the troubleshooting decisions node; and
a well control practices consequences node dependent on (a) the well control scenarios uncertainty node, (b) the well control operations uncertainty node, and (c) the recommended practices decision node and configured to output the one or more well control recommendations based on one or more Bayesian probabilities calculated from:

the one or more well control scenarios,
the one or more well control operations, and
the one or more recommended practices.

9. The system of claim 8 , comprising a user interface configured to display the well control BDN model and receive user selections of the one or more inputs.

10. The system of claim 8 , wherein the one or more well control scenarios and the one or more well control operations are each associated with a respective plurality of probabilities.

11. A method for a well control expert system having a well control Bayesian decision network (BDN) model, the method comprising:
receiving one or more inputs;
providing the one or more inputs to one or more nodes of a well control BDN model, the one or more nodes comprising:
a well control scenarios uncertainty node;
a

Assignees

• Saudi Arabian Oil Co
• Texas A&M University
• Texas A & M Univ Sys

Inventors

• Al-Yami Abdullah Saleh Hussain
• Schubert Jerome

Classifications

• E21B44/00 Primary

  Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• E21B47/1025

  Fixed Constructions · mapped topic

• E21B47/12

  Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling · CPC title

• G06N7/005

  Physics · mapped topic