PERFORMING ENTERPRISE PLANNING AND ECONOMICS ANALYSIS FOR RESERVOIR-RELATED SERVICES

• US 20100161361A1
• Filed: 02/18/2009
• Published: 06/24/2010
• Est. Priority Date: 12/23/2008
• Status: Abandoned Application

• Current Assignee: Schlumberger Technology Corporation (SLB)
• Original Assignee: Schlumberger Technology Corporation (SLB)
• Inventors: Lynch, Irving R., Spears, Carl Francis, Back, Michael John, Ai, Tao
• Application Number:
  US12/372,971
• Publication Number:
  US 20100161361A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

To perform economics management, data relating to reservoir-related services is received from a plurality of data sources. The received data is mapped into a cube-based data structure. In response to a query, data is retrieved from the cube-based data structure.

Claims

1. A method executed by at least one computer of performing economics management for reservoir-related services, comprising:

receiving data relating to reservoir-related services from a plurality of data sources;

mapping the received data into a cube-based data structure; and

in response to a query, retrieving data from the cube-based data structure.

2. The method of claim 1, wherein the reservoir-related services include any one or more of the following:

exploration, drilling, infrastructure building at well sites, well completion, hydrocarbon production, storage of hydrocarbons, distribution, and marketing and sales of hydrocarbons.

3. The method of claim 1, wherein mapping the received data into the cube-based data structure comprises mapping the received data into an online analytic processing (OLAP) cube data structure.

4. The method of claim 3, wherein the query comprises an OLAP query, the method further comprising processing the data retrieved from the cube-based data structure in response to the OLAP query.

5. The method of claim 1, wherein the cube-based data structure has dimensions selected from at least some of the following:

economic results, reserves results, production forecasts, key performance indicators, price outcomes, project outcomes, time, attributes, versions, currency, and economic and financial results.

6. The method of claim 1, further comprising:

generating a workflow relating to the economics management for reservoir-related services.

7. The method of claim 6, wherein generating the workflow comprises generating the workflow to receive the data from the plurality of sources and to map the received data into the cube-based data structure, wherein the cube-based data structure is a cube-based data warehouse.

8. The method of claim 7, wherein the generated workflow further comprises a step to synchronize different formats of the received data from the plurality of sources to a standard format.

9. The method of claim 8, wherein the generated workflow further comprises a step of performing calculations on the received data after synchronizing the received data.

10. The method of claim 1, further comprising:

causing calculations performed on the received data to be run on multiple processors.

11. The method of claim 10, wherein the multiple processors include processors in multiple machines connected to a network.

12. The method of claim 11, further comprising:

searching for machines on which a particular software has been loaded to perform the calculations.

13. A computer system comprising:

at least one storage to store a workflow specifying tasks to be performed relating to management of a reservoir containing fluids; and

at least one processor to;

execute the workflow that specifies mapping of data received from multiple data sources into a cube-based data structure.

14. The computer system of claim 13, wherein the workflow further specifies synchronization of different formats of the received data into a standard format.

15. The computer system of claim 13, wherein the at least one processor is to further:

receive an online analytical processing (OLAP) query, and in response to the query, access the cube-based data structure.

16. The computer system of claim 13, wherein the at least one processor is to receive the workflow from a client computer.

17. The computer system of claim 13, wherein the workflow further specifies calculations to be performed on the received data, and wherein the at least one processor is to select multiple machines to perform the calculations.

18. The computer system of claim 17, wherein the at least one processor is to select the multiple machines to perform the calculations by identifying the machines that contain a component of an economics management tool.

19. An article comprising at least one computer-readable storage medium containing instructions that when executed cause at least one computer to:

execute a client component of an economics management tool;

present, by the client component of the economics management tool, a graphical user interface; and

in response to interactive input from a user, create a workflow relating to economics management relating to reservoir-related services, wherein the workflow specifies mapping of data into a cube-based data structure.

20. The article of claim 19, wherein the instructions when executed cause the at least one computer to further send the workflow to a server computer for execution on the server computer.

21. The article of claim 19, wherein the workflow specifies calculations to be performed on the data received from data sources, and wherein the calculations are to be calculated on multiple processors.

22. The article of claim 19, wherein the cube-based data structure is an online analytical processing (OLAP) cube data structure.