Field operations system with particle filter

Patent metadata

Field	Value
Publication number	US-11591894-B2
Application number	US-201816192609-A
Country	US
Kind code	B2
Filing date	Nov 15, 2018
Priority date	Nov 15, 2017
Publication date	Feb 28, 2023
Grant date	Feb 28, 2023

Abstract

A method can include receiving channels of data from equipment responsive to operation of the equipment in an environment where the equipment and environment form a dynamic system; defining a particle filter that localizes a time window with respect to the channels of data; applying the particle filter at least in part by weighting particles of the particle filter using the channels of data, where each of the particles represents a corresponding time window; and selecting one of the particles according to its weight as being the time window of an operational state of the dynamic system.

First claim

What is claimed is:

1. A method comprising:
receiving channels of data from equipment responsive to operation of the equipment in an environment wherein the equipment and environment form a dynamic system;
defining a particle filter that localizes a time window with respect to the channels of data;
applying the particle filter at least in part by weighting particles of the particle filter using the channels of data, wherein each of the particles represents a corresponding time window;
selecting one of the particles according to its weight as being the time window of an operational state of the dynamic system; and
controlling the dynamic system based at least in part on the operational state.

2. The method of claim 1 , wherein the particle filter comprises a map simulated from operational procedure (OP) control signal instances and physical constraints.

3. The method of claim 1 , wherein the particles are characterized by a time window velocity.

4. The method of claim 1 , wherein the particle filter comprises a state transition model that depends on a time window velocity and changes in received channels of data with respect to time.

5. The method of claim 1 , wherein the weighting particles comprises using the channels of data and a deep Kalman filter.

6. The method of claim 5 , wherein the weighting particles is performed in a latent space defined in the deep Kalman filter.

7. The method of claim 1 , wherein the weighting particles is performed in a state space for representing states of the dynamic system.

8. The method of claim 1 , wherein the weighting particles utilizes a space that comprises a dimensionality that is greater than three.

9. The method of claim 8 , wherein the dimensionality depends on dimensionality of output of one or more recurrent layers of a neural network model of the dynamic system.

10. The method of claim 1 , wherein the operational state is a proscribed state of a pre-defined operational procedure.

11. The method of claim 1 , comprising outputting confidence of the selected one of the particles being the operational state.

12. The method of claim 1 , wherein the equipment comprises drilling equipment.

13. The method of claim 1 , wherein the equipment comprises sensors wherein the data are sensor data.

14. The method of claim 1 , wherein the channels of data comprise at least two channels of data.

15. The method of claim 14 , wherein the channels of data comprise block position data of a traveling block of a drilling rig.

16. A system comprising:
a processor;
memory accessible by the processor;
processor-executable instructions stored in the memory and executable to instruct the system to:
receive channels of data from equipment responsive to operation of the equipment in an environment wherein the equipment and environment form a dynamic system;
define a particle filter that localizes a time window with respect to the channels of data;
apply the particle filter at least in part by weighting particles of the particle filter using the channels of data, wherein each of the particles represents a corresponding time window;
select one of the particles according to its weight as being the time window of an operational state of the dynamic system; and
control at least one piece of equipment of the dynamic system based on the operational state.

17. One or more computer-readable storage media comprising processor-executable instructions to instruct a computing system to:
receive channels of data from equipment responsive to operation of the equipment in an environment wherein the equipment and environment form a dynamic system;
define a particle filter that localizes a time window with respect to the channels of data;
apply the particle filter at least in part by weighting particles of the particle filter using the channels of data, wherein each of the particles represents a corresponding time window;
select one of the particles according to its weight as being the time window of an operational state of the dynamic system; and
control at least one piece of equipment of the dynamic system based on the operational state.

Assignees

• Schlumberger Technology Corp

Inventors

• Yu Yingwei
• Liu Qiuhua
• Meehan Richard
• Chambon Sylvain
• Hamzah Mohammad

Classifications

• G06N3/08

  Learning methods · CPC title

• G06N3/0442

  characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] · CPC title

• G06N3/045

  Combinations of networks · CPC title

• E21B21/08

  Controlling or monitoring pressure or flow of drilling fluid, e.g. automatic filling of boreholes, automatic control of bottom pressure (valve arrangements therefor E21B21/10) · CPC title

• G06N3/09

  Supervised learning · CPC title