Method and system of simulating and optimizing land seismic operations

• US 6,028,819 A
• Filed: 12/14/1998
• Issued: 02/22/2000
• Est. Priority Date: 12/16/1997
• Status: Expired due to Fees

• Current Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Original Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Inventors: Mullarkey, Peter W., Canter, Peter H., Highnam, Peter T., Brooks, Ruven E., Kenyon, Astrid S., Morrice, Douglas J.
• Primary Examiner(s): Oda, Christine
• Assistant Examiner(s): JOLLY, ANTHONY S
• Application Number:
  US09/210,975
• Time in Patent Office: 435 Days
• Field of Search: 367/13, 367/56, 367/73, 367/55, 367/63, 367/74, 367/37
• US Class Current: 367/37
• CPC Class Codes: G01V 1/003 Seismic data acquisition in general, e.g. survey design G01V1/3808, G01V1/42 take precedence

Abstract

A method and system for simulating and optimizing land seismic survey operations. The method and system utilizes spatially referenced data and nonspatial data relevant to land seismic survey operations such as high resolution satellite and airborne imagery and uses discrete event information about land seismic survey operation to simulate a land seismic survey. The output of the simulation is a detailed list of survey events. Mathematical optimization techniques are used to enhance the efficiency of the survey execution via optimal route planning and optimal allocation of survey logistical components. The invention uses a discrete event simulator which is an object-oriented software program with survey geometry objects that represent the survey design, resources objects that represent resources needed to conduct survey operations and manager objects to coordinate the resource objects within the specified survey geometry.

Claims

1. A computer implemented method for simulating and optimizing land seismic survey operations, the method comprising the steps of:

a. obtaining spatially referenced data and nonspatial data relevant to a land seismic survey operation;

b. inputting discrete event information about the land seismic survey operation;

c. simulating a land seismic survey utilizing the spatially referenced data, the nonspatial data and the discrete event information; and

d. optimizing the simulated land seismic survey.

2. The method according to claim 1, wherein the spatially referenced data is high resolution digital imagery.

3. The method according to claim 1, wherein the spatially referenced data is in the form of a high resolution digital terrain map.

4. The method according to claim 3, further comprising storing the high resolution digital terrain map in a geographical information system.

5. The method according to claim 4, wherein the high resolution digital terrain map stored in the geographical information system contains pixels, and each pixel on the map is labeled with information relevant to the land seismic survey.

6. The method according to claim 1, wherein the inputting discrete event information step comprises allowing a user to adjust parameters that control complex dynamic behaviors of discrete events.

7. The method according to claim 6, wherein the complex dynamic behaviors of the discrete events include stochastic processes.

8. The method according to claim 7, wherein the stochastic processes include:

a. breakdown rates;

b. weather-related delays; and

c. travel times.

9. The method according to claim 1, wherein the simulating step permits a user to perform trade-off analyses for different routes, different crews, and different equipment options of the land seismic survey.

10. The method according to claim 1, wherein the output of the simulating step is a detailed listing of events to occur prior to and during the land seismic survey.

11. The method according to claim 10, wherein in the optimizing step, the detailed listing of events is used to optimize and order the events to occur during the land seismic survey.

12. The method according to claim 1, wherein the optimizing step is accomplished using mathematical programming techniques.

13. The method according the claim 1, further comprising inputting historical operations data to improve accuracy of the simulating and optimizing steps.

14. The method according to claim 1, wherein the simulating step is accomplished using a discrete event simulator.

15. The method according to claim 14, wherein the discrete event simulator is an object oriented software program with objects comprising:

a. survey geometry objects that represent survey design;

b. resources objects that represent resources needed to conduct survey operations; and

c. manager objects to coordinate the resource objects with the survey geometry objects.

16. The method according to claim 15, wherein the resource objects are selected from the group consisting of:

transport vehicles, layout crews, recording crews, signal crews, packing crews, trouble shooting crews and mechanics crews.

17. The method according to claim 15, further comprising modeling interactions between the survey geometry objects, resources objects and manager objects using an operations cycle model.

18. The method according to claim 17, wherein the operations cycle model comprises:

a. duration of survey operations cycle;

b. a daily operations cycle;

c. an individual operations cycle for a single resources object; and

d. a collective operations cycle for multiple resources objects.

19. The method according to claim 18, wherein the duration of survey operations cycle comprises:

a. mobilization;

b. signal generation and recording; and

c. demobilization.

20. The method according to claim 18, wherein the daily operations cycle comprises:

a. startup;

b. production; and

c. shutdown.

21. The method according to claim 20, wherein the startup comprises travel to the survey site, turning on equipment, testing the equipment, diagnosing problems and repairing problems.

22. The method according to claim 20, wherein production comprises signal generation and recording activities.

23. The method according to claim 20, wherein shutdown comprises deciding when to stop tasks for the day, preparing equipment for shutdown, logging data, and travelling back to base camp from a survey site.

24. The method according to claim 15, wherein each object comprises its own operation cycle.

25. The method according to claim 24, wherein the object comprising its own operations cycle is selected from the group consisting of transport vehicles, layout crews, recording crews, signal crews, packing crews, troubleshooting crews and mechanics personnel.

26. The method according to claim 18, wherein the collective operations cycle for multiple resource objects comprises an operations cycle for shooting and recording objects.

27. The method according to claim 26, wherein the operations cycle for shooting and recording objects comprises:

a. preparing transport vehicle to pickup equipment prepared by packing crews;

b. preparing to drop-off receiver equipment for installation by layout crews;

c. installing receiver equipment by layout crews for use by recording crews;

d. sending signals by signal crews which are captured by an installed set of receiving equipment; and

e. preparing available equipment by packing crews for pickup by the transport vehicles.

28. The method according to claim 17, wherein the operations cycle model controls behavior of the object.

29. The method according to claim 28, wherein the operations cycle model accounts for uncertainty in the behavior of the object by using probability distributions.

30. The method according to claim 1, wherein steps a through e are performed prior to the land seismic survey.

31. The method according to claim 1, wherein steps a through e are performed during the land seismic survey.

32. The method according to claim 1, further comprising:

a. performing steps a through e for a first set of discrete events;

b. saving the results of the optimizing step for the first set of discrete events;

c. changing one or more of the first set of discrete events so as to form a second set of discrete events;

d. repeating steps a through e using the second set of discrete events and saving the results of the optimizing step for the second set of discrete events; and

e. allowing a user to compare the results for the first and second set of discrete events.

33. The method according to claim 4, wherein the high resolution terrain map is used to scout sites prior to bidding a price for the land seismic survey.

34. The method according to claim 33, further comprising allowing a user to view the terrain map interactively on a computer screen.

35. The method according to claim 14, wherein the output of the discrete event simulator provides timing estimates for the survey and breakdown probabilities.

36. The method according to claim 14, wherein the discrete event simulator allows a user to investigate impact of changing a parameter of a discrete event.

37. The method according to claim 14, wherein the discrete event simulator produces an event list of survey events as they occur, the event list being displayed to the user on the terrain map as a two-dimensional display of motion of survey components over an area of the survey site.

38. The method according to claim 14, wherein using historical operations information is used by the discrete event simulator to assess survey risk based on information from the historical operations.

39. The method according to claim 1, wherein optimizing comprises using mathematical programming techniques to optimize simulating a land seismic survey and determining optimal locations for survey bases, field equipment and optimal equipment and crew routing.

42. The method according to claim 1, wherein the high resolution digital imagery is selected from the group consisting of satellite and airborne sensors.

43. The method according to claim 42, wherein the satellite and airborne sensors contain sensor types selected from the group consisting of optical, laser and radar sensors.

44. The method according to claim 1, wherein the nonspatial data is selected from the group consisting of personnel experience and historical data.

45. The method according to claim 30, further comprising saving the optimizing step results and using the results to develop a price for the land seismic survey.

46. The method according to claim 31, further comprising saving the optimizing step results and using the results to alter tactical decisions while the survey is being performed.

40. Computer executable software code stored on a computer readable medium, the code for simulating and optimizing land seismic survey operations comprising:

a. code to obtain spatially referenced data and nonspatial data relevant to a land seismic survey operation;

b. code to input discrete event information about the land seismic survey operation;

c. code to simulate the land seismic survey events utilizing the spatially referenced data, the nonspatial data and the discrete event information; and

d. code to optimize and order simulated survey events.

41. A computer-readable medium having computer-executable software code stored thereon, the code for simulating and optimizing land seismic survey operations comprising:

a. code to obtain spatially referenced data and nonspatial data relevant to a land seismic survey operation;

b. code to input discrete event information about the land seismic survey operation;

c. code to simulate the land seismic survey events utilizing the spatially referenced data, the nonspatial data and the discrete event information; and

d. code to optimize and order simulated survey events.

47. A system for simulating and optimizing land seismic survey operations comprising:

a. a memory means for storing spatially referenced data and nonspatial data relevant to a land seismic survey;

b. a processor means for;

i. simulating a land seismic survey utilizing the spatially referenced data, the nonspatial data and the discrete event information;

ii. optimizing the simulated land seismic survey; and

c. a user interface and display means for;

i. allowing a user to input discrete event information about the land seismic survey operation;

ii. displaying progress of the simulation to the user as it is being generated;

iii. displaying optimized results of the simulation to the user.