Distributed real-time processing for gas lift optimization

Patent metadata

Field	Value
Publication number	US-2016053753-A1
Application number	US-201414466750-A
Country	US
Kind code	A1
Filing date	Aug 22, 2014
Priority date	Aug 22, 2014
Publication date	Feb 25, 2016
Grant date	—

Abstract

A method, apparatus, and program product perform lift optimization in a field with a plurality of wells, with each well including an artificial lift mechanism controlled by an associated well controller. In a central controller, a network simulation model functioning as a proxy of the field is accessed to determine an optimal allocation solution for the field, and a well-specific control signal is generated for each of the plurality of wells based upon the determined optimal allocation solution. The well-specific control signal for each of the plurality of wells is communicated to the associated well controller to cause the associated well controller to control a lift parameter associated with the artificial lift mechanism for the well.

First claim

What is claimed is:

1 . A method of performing lift optimization in a field comprising a plurality of wells, with each well including an artificial lift mechanism controlled by an associated well controller, the method comprising, in a central controller:
accessing a network simulation model as a proxy of the field to determine an optimal allocation solution for the field; generating a well-specific control signal for each of the plurality of ells based upon the determined optimal allocation solution; and communicating the well-specific control signal for each of the plurality of wells to the associated well controller to cause the associated well controller to control a lift parameter associated with the artificial lift mechanism for the well.

2 . The method of claim 1 , wherein accessing the network simulation model includes iteratively converging to the optimal allocation solution.

3 . The method of claim 2 , wherein iteratively converging to the optimal allocation solution includes converging based upon a network solution determined from the network simulation model.

4 . The method of claim 2 , wherein iteratively converging to the optimal allocation solution includes converging based upon actual field data collected from at least one of the plurality of wells.

5 . The method of claim 1 , further comprising running a field-wide simulation to generate the network simulation model.

6 . The method of claim 5 , further comprising generating a well-specific model for each of the plurality of wells.

7 . The method of claim 6 , further comprising generating a set of lift performance curves for each of the plurality of wells from the well-specific model for each of the plurality of wells, wherein generating the well-specific control signal for each of the plurality of wells includes generating the well-specific control signal using the set of lift performance curves for each of the plurality of wells.

8 . The method of claim 7 , wherein running the field-wide simulation and generating the set of lift performance curves are performed externally to the central controller, the method further comprising communicating the network simulation model and each set of lift performance curves to the central controller.

9 . The method of claim 5 , further comprising:
collecting actual field data; and retuning at least one well-specific model in response to determining from the collected actual field data that the optimal allocation solution is out of tolerance.

10 . The method of claim 1 , wherein the artificial lift mechanism for at least one well comprises a gas lift mechanism, and wherein the lift parameter comprises a gas lift rate.

11 . A central controller for performing lift optimization in a field comprising a plurality of wells, with each well including an artificial lift mechanism controlled by an associated well controller, the central controller comprising:
at least one processor; and program code configured upon execution by the at least one process access a network simulation model as a proxy of the field to determine an optimal allocation solution for the field, generate generating a well-specific control signal for each of the plurality of wells based upon the determined optimal allocation solution, and communicate the well-specific control signal for each of the plurality of wells to the associated well controller to cause the associated well controller to control a lift parameter associated with the artificial lift mechanism for the well.

12 . The central controller of claim 11 , wherein the program code is configured to access the network simulation model by iteratively converging to the optimal allocation solution.

13 . The central controller of claim 12 , wherein the program code is configured to iteratively converge to the optimal allocation solution by converging based upon a network solution determined from the network simulation model.

14 . The central controller of claim 12 , wherein the program code is configured to iteratively converge to the optimal allocation solution by converging based upon actual field data collected from at least one of the plurality of wells.

15 . The central controller of claim 11 , wherein the network simulation model is generated from a field-wide simulation.

16 . The central controller of claim 15 , wherein the program code is further configured to access a well-specific model for each of the plurality of wells.

17 . The central controller of claim 16 , wherein the program code is further configured to access a set of lift performance curves for each of the plurality of wells, and wherein the program code is configured to generate the well-specific control signal for each of the plurality of wells using the set of lift performance curves for each of the plurality of wells.

18 . The central controller of claim 17 , wherein the network simulation model and the set of lift performance curves are generated externally from the central controller, and wherein the program code is configured to receive the network simulation model and each set of lift performance curves.

19 . The central controller of claim 15 , wherein the program code is configured to collect actual field data and retune at least one well-specific model in response to determining from the collected actual field data that the optimal allocation solution is out of tolerance.

20 . A computer readable storage medium having a set of computer-readable instructions residing thereon that, when executed, perform lift optimization in a field comprising a plurality of wells, with each well including an artificial lift mechanism controlled by an associated well controller, wherein the set of computer-readable instructions are configured upon execution by a central controller to access a network simulation model as a proxy of the field to determine an optimal allocation solution for the field, generate a well-specific control signal for each of the plurality of wells based upon the determined optimal allocation solution, and communicate the well-specific control signal for each of the plurality of wells to the associated well controller to cause the associated well controller to control a lift parameter associated with the artificial lift mechanism for the well.

Assignees

• Schlumberger Technology Corp

Inventors

• Rashid Kashif
• Rossi David John

Classifications

• E21B47/008 Primary

  Monitoring of down-hole pump systems, e.g. for the detection of "pumped-off" conditions · CPC title

• G05B13/04

  involving the use of models or simulators · CPC title

• F04B49/065 Primary

  and making use of computers · CPC title

• G05B13/041

  in which a variable is automatically adjusted to optimise the performance · CPC title

• E21B43/122 Primary

  Gas lift · CPC title