Drilling Measurement Valuation

• US 20190330963A1
• Filed: 06/24/2016
• Published: 10/31/2019
• Est. Priority Date: 06/24/2016
• Status: Active Grant

• Current Assignee: Schlumberger Technology Corporation (SLB)
• Original Assignee: Schlumberger Technology Corporation (SLB)
• Inventors: Bailey, William, Omeragic, Dzevat
• Granted Patent: US 11,795,793 B2
• Time in Patent Office: Days
• CPC Class Codes: E21B 43/12 Methods or apparatus for controlling the flow of the obtained fluid to or in wells E21B43/25 takes precedence; valve arrangements E21B34/00
• CPC Class Codes: E21B 47/003 Determining well or borehole volumes
• CPC Class Codes: E21B 49/00 Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
• CPC Class Codes: G01V 2210/663 Modeling production-induced effects
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 17/40 Data acquisition and logging for input to computer G06F3/00

Abstract

Systems, computer-readable media, and methods for valuating measurement data, of which the method includes obtaining a first model of a subsurface volume, determining a baseline control parameter based on the first model, receiving new measurement data measured using a data collection device, the new measurement data representing one or more characteristics of the subsurface volume, and obtaining a second model of the subsurface volume based in part on the new measurement data. The first model is not based on the new measurement data. Further, the method includes determining an enhanced control parameter based on the second model, determining an enhanced value corresponding to the second model using the enhanced control parameter, determining a realized value corresponding to the second model using the baseline control parameter, and calculating a value of the new measurement data by comparing the enhanced value and the realized value.

Claims

1. A method for valuating measurement data, comprising:

obtaining a first model of a subsurface volume;

determining a baseline control parameter based on the first model;

receiving new measurement data measured using a data collection device, the new measurement data representing one or more characteristics of the subsurface volume;

obtaining a second model of the subsurface volume based in part on the new measurement data, wherein the first model is not based on the new measurement data;

determining an enhanced control parameter based on the second model;

determining an enhanced value corresponding to the second model using the enhanced control parameter;

determining a realized value corresponding to the second model using the baseline control parameter; and

calculating a value of the new measurement data by comparing the enhanced value and the realized value.

2. The method of claim 1, wherein the first model comprises a first plurality of uncertainty samples, and the second model comprises a second plurality of uncertainty samples, the second plurality of uncertainty samples being calculated based on the new measurement data.

3. The method of claim 2, wherein the first plurality of uncertainty samples comprises a uniform probability distribution across a zone of uncertainty, and wherein the second plurality of uncertainty samples comprises a Gaussian probability distribution across the zone of uncertainty.

4. The method of claim 2, wherein determining the baseline control parameter comprises applying a risk-aversion factor in an objective function for the first model, and wherein determining the enhanced control parameter comprises applying the risk-aversion factor in an objective function for the second model.

5. The method of claim 1, wherein determining the baseline control parameter comprises selecting the baseline control parameter that maximizes a value corresponding to the first model.

6. The method of claim 1, wherein the baseline control parameter comprises a flowpath area of a flow control device in a completion, and wherein the enhanced control parameter comprises the flowpath area of the flow control device.

7. The method of claim 1, wherein the new measurement comprises a deep-directional-resistivity measurement, and wherein the one or more characteristics comprises an oil-water contact location or a gas-oil contact location.

8. The method of claim 1, further comprising adjusting an operation strategy, a completion design, or a well trajectory based on the new measurement data.

9. A computing system, comprising:

one or more processors; and

a memory system including one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations comprising;

obtaining a first model of a subsurface volume;

determining a baseline control parameter based on the first model;

receiving new measurement data measured using a data collection device, the new measurement data representing one or more characteristics of the subsurface volume;

obtaining a second model of the subsurface volume based in part on the new measurement data, wherein the first model is not based on the new measurement data;

determining an enhanced control parameter based on the second model;

determining an enhanced value corresponding to the second model using the enhanced control parameter;

determining a realized value corresponding to the second model using the baseline control parameter; and

calculating a value of the new measurement data by comparing the enhanced value and the realized value.

10. The system of claim 9, wherein the first model comprises a first plurality of uncertainty samples, and the second model comprises a second plurality of uncertainty samples, the second plurality of uncertainty samples being calculated based on the new measurement data.

11. The system of claim 10, wherein the first plurality of uncertainty samples comprises a uniform probability distribution across a zone of uncertainty, and wherein the second plurality of uncertainty samples comprises a Gaussian probability distribution across the zone of uncertainty.

12. The system of claim 10, wherein determining the baseline control parameter comprises applying a risk-aversion factor in an objective function for the first model, and wherein determining the enhanced control parameter comprises applying the risk-aversion factor in an objective function for the second model.

13. The system of claim 9, wherein determining the baseline control parameter comprises selecting the baseline control parameter that maximizes a value corresponding to the first model.

14. The system of claim 9, wherein the baseline control parameter comprises a flowpath area of a flow control device in a completion, and wherein the enhanced control parameter comprises the flowpath area of the flow control device.

15. The system of claim 9, wherein the new measurement comprises a deep-directional-resistivity measurement, and wherein the one or more characteristics comprises an oil-water contact location.

16. A non-transitory computer-readable medium storing instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations, the operations comprising:

obtaining a first model of a subsurface volume;

determining a baseline control parameter based on the first model;

receiving new measurement data measured using a data collection device, the new measurement data representing one or more characteristics of the subsurface volume;

obtaining a second model of the subsurface volume based in part on the new measurement data, wherein the first model is not based on the new measurement data;

determining an enhanced control parameter based on the second model;

determining an enhanced value corresponding to the second model using the enhanced control parameter;

determining a realized value corresponding to the second model using the baseline control parameter; and

calculating a value of the new measurement data by comparing the enhanced value and the realized value.

17. The medium of claim 16, wherein the first model comprises a first plurality of uncertainty samples, and the second model comprises a second plurality of uncertainty samples, the second plurality of uncertainty samples being calculated based on the new measurement data.

18. The medium of claim 17, wherein the first plurality of uncertainty samples comprises a uniform probability distribution across a zone of uncertainty, and wherein the second plurality of uncertainty samples comprises a Gaussian probability distribution across the zone of uncertainty.

19. The medium of claim 17, wherein determining the baseline control parameter comprises applying a risk-aversion factor in an objective function for the first model, and wherein determining the enhanced control parameter comprises applying the risk-aversion factor in an objective function for the second model.

20. The medium of claim 16, wherein determining the baseline control parameter comprises selecting the baseline control parameter that maximizes a value corresponding to the first model.