Method for performing oilfield production operations

• US 8,078,444 B2
• Filed: 12/06/2007
• Issued: 12/13/2011
• Est. Priority Date: 12/07/2006
• Status: Active Grant

• Current Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Original Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Inventors: Rashid, Kashif, Shand, Andrew, Tonkin, Trevor, Letizia, Luca, Howell, Andrew John, Lucas-Clements, Daniel
• Primary Examiner(s): Shah, Kamini S
• Assistant Examiner(s): LUU, CUONG V
• Application Number:
  US11/952,069
• Publication Number:
  US 20080140369A1
• Time in Patent Office: 1,468 Days
• Field of Search: 703/10, 702/12, 166/302, 166/267, 166/245
• US Class Current: 703/10
• CPC Class Codes: E21B 43/00 Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells applicable only to water E03B
• CPC Class Codes: E21B 43/122 Gas lift

Abstract

A method is disclosed for optimal lift resource allocation, which includes optimally allocating lift resource under a total lift resource constraint or a total production constraint, the allocating step including distributing lift resource among all lifted wells in a network so as to maximize a liquid/oil rate at a sink.

Claims

1. A method for lift resource allocation, comprising:

optimally allocating a lift resource under at least one selected from a group consisting of a total lift resource constraint and a total produced gas constraint, allocating the lift resource comprising;

distributing the lift resource among a plurality of lifted wells in a network so as to maximize a liquid/oil rate at a sink;

obtaining lift curve data comprising an operating curve for each of the plurality of lifted wells,

taking a derivative of the operating curve to obtain a derivative curve for each of the plurality of lifted wells,

forming an inverse of the derivative curve to obtain an inverse derivative curve for each of the plurality of lifted wells,

summing the inverse derivative curve of all the plurality of lifted wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint,

solving the single variable problem using the lift curve data to obtain a solution, and

running a network simulator to generate a real network model for determining new wellhead pressures, wherein the new wellhead pressures are compared to previous wellhead pressures used in the solution to the single variable problem.

2. The method of claim 1,

wherein the plurality of lifted wells comprises at least one selected from a group consisting of gas lifted wells, electrical submersible pump (ESP) lifted wells, and chemical injection stimulated wells,

wherein the solution is an optimal allocation of the lift resource comprising at least one selected from a group consisting of injection gas available for the gas lifted wells, power available for the ESP lifted wells, and chemical available for the chemical injection stimulated wells,

wherein running the network simulator to generate the real network model comprises using said optimal allocation of the lift resource to obtain a production value at a sink and the new wellhead pressures at each of the plurality of lifted wells,

and wherein allocating the lift resource further comprises:

repeating said optimal allocation procedure using said new wellhead pressures until there is convergence between the previous wellhead pressures and the new wellhead pressures.

3. The method of claim 1, wherein allocating the lift resource further comprises:

(a) generating a plurality of lift performance curves, for each of the plurality of lifted wells in the network, adapted for describing an expected liquid flow rate for a given amount of lift resource application at given wellhead pressures;

(b) assigning, for each of the plurality of lifted wells in the network, an initial wellhead pressure adapted for setting an operating curve for said each of the plurality of lifted wells;

(c) in response to the initial wellhead pressure assigned to each of the plurality of lifted wells in the network, implementing an allocation procedure to generate optimal lift resource values for the plurality of lifted wells according to the total lift resource constraint so as to maximize a total flow rate;

(d) on the condition that said allocation procedure is completed, running the network simulator with the optimal lift resource values assigned to the plurality of lifted wells of the network model to generate the real network model; and

(e) repeating steps (b) through (d) until there is convergence between the previous wellhead pressures and the new wellhead pressures for all of the plurality of lifted wells in the real network model.

4. A method for lift resource allocation, comprising:

optimally allocating lift resource under at least one selected from a group consisting of a total lift resource constraint and a total produced gas constraint, allocating the lift resource comprising;

distributing the lift resource among a plurality of lifted wells in a network so as to maximize a liquid/oil rate at a sink,

obtaining lift curve data comprising an operating curve for each of the plurality of lifted wells,

taking a derivative of the operating curve to obtain a derivative curve for each of the plurality of lifted wells,

forming an inverse of the derivative curve to obtain an inverse derivative curve for each of the plurality of lifted wells,

summing the inverse derivative curve of all the plurality of lifted wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint,

solving the single variable problem using the lift curve data to obtain a solution, and

generating a real network model for determining new wellhead pressures based on the solution to the single variable problem, wherein the new wellhead pressures are compared to previous wellhead pressures used in the solution to the single variable problem.

5. The method of claim 4, wherein allocating the lift resource further comprises:

extracting lift performance curves,

solving an optimal allocation procedure to determine an optimal allocation of the lift resource,

using said optimal allocation of the lift resource to obtain a production value at a sink and new well head pressures of the plurality of lifted wells; and

repeating said optimal allocation procedure using said new wellhead pressures until there is convergence between the previous wellhead pressures and the new wellhead pressures.

6. The method of claim 4, wherein allocating the lift resource further comprises:

(a) generating a plurality of lift performance curves, for each of the plurality of lifted wells in the network, adapted for describing an expected liquid flow rate for a given amount of lift resource application at given wellhead pressures;

(b) assigning, for each of the plurality of lifted wells in the network, an initial wellhead pressure adapted for setting an operating curve for said each of the plurality of lifted wells;

(c) in response to the initial wellhead pressure assigned to each of the plurality of lifted wells in the network, implementing an allocation procedure to generate optimal lift resource values for the plurality of lifted wells according to the total lift resource constraint so as to maximize a total flow rate;

(d) on the condition that said allocation procedure is completed, running the network simulator with the optimal lift resource values assigned to the plurality of lifted wells of the network model to generate the real network model; and

(e) repeating steps (b) through (d) until there is convergence between the previous wellhead pressures and the new wellhead pressures for all of the plurality of lifted wells in the real network model.

7. A method for lift resource allocation, comprising:

optimally allocating lift resource under at least one selected from a group consisting of a total lift resource constraint and a total produced gas constraint, allocating the lift resource comprising;

distributing the lift resource among a plurality of lifted wells in a network so as to maximize a liquid/oil rate at a sink, allocating the lift resource further comprising;

(a) generating a plurality of lift performance curves, for each of the plurality of lifted wells in the network, adapted for describing an expected liquid flow rate for a given amount of lift resource application at given wellhead pressures;

(b) assigning, for each of the plurality of lifted wells in the network, an initial wellhead pressure adapted for setting an operating curve for said each of the plurality of lifted wells;

(c) taking a derivative of the operating curve to determine a derivative curve for said each well;

(d) forming an inverse of the derivative curve to obtain an inverse derivative curve for said each well;

(e) summing the inverse derivative curve of all the plurality of wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint;

(f) in response to the initial wellhead pressure assigned to each of the plurality of lifted wells in the network, implementing an allocation procedure to generate optimal lift resource values for the plurality of lifted wells according to the total lift gas constraint so as to maximize a total flow rate;

(g) on the condition that said allocation procedure is completed, running the network simulator with the optimal lift resource values assigned to the plurality of lifted wells of the network model to generate the real network model; and

(h) repeating steps (b) through (d) until there is convergence between the previous wellhead pressures and the new wellhead pressures for all of the plurality of lifted wells in the real network model.

8. A program storage device readable by a machine tangibly embodying a program of instructions executable by the machine to perform method steps for lift resource allocation, said method steps comprising:

optimally allocating lift resource under at least one selected from a group consisting of a total lift resource constraint and a total produced gas constraint allocating the lift resource comprising;

distributing the lift resource among a plurality of lifted wells in a network so as to maximize a liquid/oil rate at a sink, the

obtaining lift curve data comprising an operating curve for each of the plurality of lifted wells,

taking a derivative of the operating curve to obtain a derivative curve for each of the plurality of lifted wells,

forming an inverse of the derivative curve to obtain an inverse derivative curve for each of the plurality of lifted wells,

summing the inverse derivative curve of all the plurality of lifted wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint,

solving the single variable problem using the lift curve data to obtain a solution, and

generating a real network model for determining new wellhead pressures based on the solution to the single variable problem, wherein the new wellhead pressures are compared to previous wellhead pressures used in the solution to the single variable problem.

9. The program storage device of claim 8, wherein allocating the lift resource further comprises:

extracting lift performance curves,

solving an optimal allocation procedure to determine an optimal allocation of the lift resource,

using said optimal allocation of the lift resource to obtain a production value at a sink and new well head pressures of the plurality of lifted wells; and

repeating said optimal allocation procedure using said new wellhead pressures until there is convergence between the previous wellhead pressures and the new wellhead pressures.

10. The program storage device of claim 8, wherein allocating the lift resource further comprises:

(a) generating a plurality of lift performance curves, for each of the plurality of lifted wells in the network, adapted for describing an expected liquid flow rate for a given amount of lift resource application at given wellhead pressures;

(b) assigning, for each of the plurality of lifted wells in the network, an initial wellhead pressure adapted for setting an operating curve for said each of the plurality of lifted wells;

(c) in response to the initial wellhead pressure assigned to each of the plurality of lifted wells in the network, implementing an allocation procedure to generate optimal lift resource values for the plurality of lifted wells according to the total lift gas constraint so as to maximize a total flow rate;

(d) on the condition that said allocation procedure is completed, running the network simulator with the optimal lift resource values assigned to the plurality of lifted wells of the network model to generate the real network model; and

(e) repeating steps (b) through (d) until there is convergence between the previous wellhead pressures and the new wellhead pressures for all of the plurality of lifted wells in the real network model.

11. A program storage device readable by a machine tangibly embodying a program of instructions executable by the machine to perform method steps for lift resource allocation, said method steps comprising:

optimally allocating lift resource under at least one selected from a group consisting of a total lift resource constraint and a total produced gas constraint allocating the lift resource comprising distributing the lift resource among a plurality of lifted wells in a network so as to maximize a liquid/oil rate at a sink, allocating further comprising;

(a) generating a plurality of lift performance curves, for each of the plurality of lifted wells in the network, adapted for describing an expected liquid flow rate for a given amount of lift resource application at given wellhead pressures;

(b) assigning, for each of the plurality of lifted wells in the network, an initial wellhead pressure adapted for setting an operating curve for said each of the plurality of lifted wells;

(c) taking a derivative of the operating curve to determine a derivative curve for said each well;

(d) forming an inverse of the derivative curve to obtain an inverse derivative curve for said each well;

(e) summing the inverse derivative curve of all the plurality of wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint;

(f) in response to the initial wellhead pressure assigned to each of the plurality of lifted wells in the network, implementing an allocation procedure to generate optimal lift resource values for the plurality of lifted wells according to the total lift gas constraint so as to maximize a total flow rate;

(g) on the condition that said allocation procedure is completed, running the network simulator with the optimal lift resource values assigned to the plurality of lifted wells of the network model to generate the real network model; and

(h) repeating steps (b) through (d) until there is convergence between the previous wellhead pressures and the new wellhead pressures for all of the plurality of lifted wells in the real network model.

12. A program storage device readable by a machine tangibly embodying a program of instructions executable by the machine to perform method steps for resource allocation, said method steps comprising:

optimally allocating lift resource under at least one selected from a group consisting of a total lift resource constraint and a total produced gas constraint allocating the lift resource comprising;

distributing the lift resource among a plurality of lifted wells in a network so as to maximize a liquid/oil rate at a sink,

obtaining lift curve data comprising an operating curve for each of the plurality of lifted wells,

taking a derivative of the operating curve to obtain a derivative curve for each of the plurality of lifted wells,

forming an inverse of the derivative curve to obtain an inverse derivative curve for each of the plurality of lifted wells,

summing the inverse derivative curve of all the plurality of lifted wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint,

solving the single variable problem using the lift curve data to obtain a solution, and

running a network simulator to generate a real network model for determining new wellhead pressures, wherein the new wellhead pressures are compared to previous wellhead pressures used in the solution to the single variable problem.

13. The program storage device of claim 12, wherein the plurality of lifted wells comprises at least one selected from a group consisting of gas lifted wells, electrical submersible pump (ESP) lifted wells, and chemical injection stimulated wells, wherein the solution is an optimal allocation of the lift resource comprising at least one selected from a group consisting of injection gas available for the gas lifted wells, power available for the ESP lifted wells, and chemical available for the chemical injection stimulated wells, wherein running the network simulator to generate the real network model comprises using said optimal allocation of the lift resource to obtain a production value at a sink and the new wellhead pressures at each of the plurality of lifted wells, and wherein allocating the lift resource further comprises:

repeating said optimal allocation procedure using said new wellhead pressures until there is convergence between the previous wellhead pressures and the new wellhead pressures.

14. The program storage device of claim 12, wherein allocating the lift resource further comprises:

(a) generating a plurality of lift performance curves, for each of the plurality of lifted wells in the network, adapted for describing an expected liquid flow rate for a given amount of lift resource application at given wellhead pressures;

(b) assigning, for each of the plurality of lifted wells in the network, an initial wellhead pressure adapted for setting an operating curve for said each of the plurality of lifted wells;

(c) in response to the initial wellhead pressure assigned to each of the plurality of lifted wells in the network, implementing an allocation procedure to generate optimal lift resource values for the plurality of lifted wells according to the total lift gas constraint so as to maximize a total flow rate;

(d) on the condition that said allocation procedure is completed, running the network simulator with the optimal lift resource values assigned to the plurality of lifted wells of the network model to generate the real network model; and

(e) repeating steps (b) through (d) until there is convergence between the previous wellhead pressures and the new wellhead pressures for all of the plurality of lifted wells in the real network model.

15. A computer system adapted for lift resource allocation, comprising:

a processor; and

apparatus adapted to be executed on the processor for optimally allocating lift resource under at least one selected from a group consisting of a total lift resource constraint and a total produced gas constraint, the apparatus comprising further apparatus adapted to be executed on the processor for;

distributing the lift resource among a plurality of lifted wells in a network so as to maximize a liquid/oil rate at a sink,

obtaining lift curve data comprising an operating curve for each of the plurality of lifted wells,

taking a derivative of said each operating curve to obtain a derivative curve for each of the plurality of lifted wells,

forming an inverse of the derivative curve to obtain an inverse derivative curve for each of the plurality of lifted wells,

summing the inverse derivative curve of all the plurality of lifted wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint,

solving the single variable problem using the lift curve data to obtain a solution, and

running a network simulator to generate a real network model for determining new wellhead pressures, wherein the new wellhead pressures are compared to previous wellhead pressures used in the solution to the single variable problem.

16. The computer system of claim 15, the apparatus comprising further apparatus adapted to be executed on the processor for:

obtaining lift curve data comprising an operating curve for each of the plurality of lifted wells,

taking a derivative of the operating curve to obtain a derivative curve for each of the plurality of lifted wells,

forming an inverse of the derivative curve to obtain an inverse derivative curve for each of the plurality of lifted wells,

summing the inverse derivative curve of all the plurality of lifted wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint,

solving the single variable problem using the lift curve data to obtain a solution, and

generating a real network model for determining new wellhead pressures based on the solution to the single variable problem, wherein the new wellhead pressures are compared to previous wellhead pressures used in the solution to the single variable problem.

17. The computer system of claim 15, the apparatus comprising further apparatus adapted to be executed on the processor for:

extracting lift performance curves,

solving an optimal allocation procedure to determine an optimal allocation of the lift resource,

using said optimal allocation of the lift resource to obtain a production value at a sink and new well head pressures of the plurality of lifted wells; and

repeating said optimal allocation procedure using said new wellhead pressures until there is convergence between the previous wellhead pressures and the new wellhead pressures.

18. The computer system of claim 15, the apparatus comprising further apparatus adapted to be executed on the processor for:

(a) generating a plurality of lift performance curves, for each of the plurality of lifted wells in the network, adapted for describing an expected liquid flow rate for a given amount of lift resource application at given wellhead pressures;

(b) assigning, for each of the plurality of lifted wells in the network, an initial wellhead pressure adapted for setting an operating curve for said each of the plurality of lifted wells;

(c) in response to the initial wellhead pressure assigned to each of the plurality of lifted wells in the network, implementing an allocation procedure to generate optimal lift resource values for the plurality of lifted wells according to the total lift gas constraint so as to maximize a total flow rate;

(d) on the condition that said allocation procedure is completed, running the network simulator with the optimal lift resource values assigned to the plurality of lifted wells of the network model to generate the real network model; and

(e) repeating steps (b) through (d) until there is convergence between the previous wellhead pressures and the new wellhead pressures for all of the plurality of lifted wells in the real network model.

19. A computer system adapted for lift resource allocation, comprising:

a processor; and

apparatus adapted to be executed on the processor for optimally allocating lift resource under at least one selected from a group consisting of a total lift resource constraint and a total produced gas constraint, the apparatus comprising further apparatus adapted to be executed on the processor for distributing the lift resource among a plurality of lifted wells in a network so as to maximize a liquid/oil rate at a sink, the apparatus comprising further apparatus adapted to be executed on the processor for;

(a) generating a plurality of lift performance curves, for each of the plurality of lifted wells in the network, adapted for describing an expected liquid flow rate for a given amount of lift resource application at given wellhead pressures;

(b) assigning, for each of the plurality of lifted wells in the network, an initial wellhead pressure adapted for setting an operating curve for said each of the plurality of lifted wells;

(c) taking a derivative of the operating curve to determine a derivative curve for said each well;

(d) forming an inverse of the derivative curve to obtain an inverse derivative curve for said each well;

(e) summing the inverse derivative curve of all the plurality of lifted wells to convert a multiple variable problem with a linear inequality constraint into a single variable problem with a linear equality constraint;

(f) in response to the initial wellhead pressure assigned to each of the plurality of lifted wells in the network, implementing an allocation procedure to generate optimal lift resource values for the plurality of lifted wells according to the total lift gas constraint so as to maximize a total flow rate;

(g) on the condition that said allocation procedure is completed, running the network simulator with the optimal lift resource values assigned to the plurality of lifted wells of the network model to generate the real network model; and

(h) repeating steps (b) through (d) until there is convergence between the previous wellhead pressures and the new wellhead pressures for all of the plurality of lifted wells in the real network model.