METHODS AND SYSTEMS FOR REAL-TIME MONITORING AND PROCESSING OF WELLBORE DATA

• US 20130292178A1
• Filed: 05/07/2012
• Published: 11/07/2013
• Est. Priority Date: 05/07/2012
• Status: Active Grant

• Current Assignee: Halliburton Energy Services Incorporated (Halliburton Company)
• Original Assignee: Halliburton Energy Services Incorporated (Halliburton Company)
• Inventors: Gonzalez, Peter, Burress, Charlotte N., Galliano, Clint C.
• Granted Patent: US 9,255,473 B2
• Time in Patent Office: Days
• US Class Current: 175/50
• CPC Class Codes: E21B 41/00 Equipment or details not covered by groups E21B15/00 - E21B40/00
• CPC Class Codes: E21B 44/00 Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
• CPC Class Codes: E21B 45/00 Measuring the drilling time or rate of penetration
• CPC Class Codes: E21B 47/07 Temperature
• CPC Class Codes: E21B 49/003 by analysing drilling variables or conditions E21B49/005 takes precedence; systems specially adapted for monitoring a plurality of drilling variables or conditions E21B44/00
• CPC Class Codes: E21B 7/00 Special methods or apparatus for drilling
• 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 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

Apparatus and methods for monitoring and processing wellbore data are disclosed. An integrated digital ecosystem comprises an applied fluid optimization specialist and one or more sensors communicatively coupled to the applied fluid optimization specialist. The applied fluid optimization specialist receives data relating to performance of subterranean operations from the one or more sensors and interprets the data received. The applied fluid optimization specialist then regulates the performance of subterranean operations based on the interpretation of the data received.

Claims

1. An integrated digital ecosystem comprising:

an applied fluid optimization specialist;

one or more sensors communicatively coupled to the applied fluid optimization specialist;

wherein the applied fluid optimization specialist receives data relating to performance of subterranean operations from the one or more sensors;

wherein the applied fluid optimization specialist interprets the data received from the one or more sensors; and

wherein the applied fluid optimization specialist regulates the performance of subterranean operations based on the interpretation of the data received.

2. The system of claim 1, wherein the data relating to performance of subterranean operations is selected from a group consisting of hole depth, bit depth, block position, hookload, True Vertical Depth, time/date activity, temperature, fluid flow rates into system components, fluid flow rates out of system components, fluid density, Riser flow in, stand pipe pressure, rotary RPM, torque, choke pressure, bottom hole temperature, rate of penetration, running speed, Pressure While Drilling, Equivalent Mud Weight, pit volumes, pit volume change, and a combination thereof.

3. The system of claim 1, further comprising an applied fluid optimization Modeling and Planner communicatively coupled to the applied fluid optimization specialist, wherein the applied fluid optimization Modeling and Planner develops an execution plan prior to performance of subterranean operations.

4. The system of claim 1, wherein data relating to performance of subterranean operations is data relating to an inventory control system, and wherein the applied fluid optimization specialist manages inventory using the data relating to the inventory control system.

5. The system of claim 1, wherein data relating to performance of subterranean operations is data relating to drilling cuttings'"'"' characteristics, and wherein the applied fluid optimization specialist regulates drilling operations using the data relating to drilling cuttings'"'"' characteristics.

6. The system of claim 1, wherein data relating to performance of subterranean operations is data relating to drilling operations and is selected from a group consisting of density, viscosity, Particle Size Distribution (“

PSD”

), oil/water ratio, electrical stability, percentage of solid content, Chloride concentration, Cation concentration, and pH.

7. A method of optimizing performance of subterranean operations comprising:

monitoring performance of a subterranean operation;

determining whether the subterranean operation is being performed at an optimal level;

identifying one or more causes for the subterranean operation not being performed at an optimal level; and

generating an intervention if the subterranean operation is not being performed at an optimal level,

wherein level of intervention depends on the one or more causes for the subterranean operation not being performed at an optimal level.

8. The method of claim 7, wherein the level of intervention is selected from a group consisting of a low level intervention, a medium level intervention, and a high level intervention.

9. The method of claim 7, wherein determining whether the subterranean operation is being performed at an optimal level comprises comparing simulated rig data with actual rig data.

10. The method of claim 7, further comprising communicating the intervention to a Point of Contact, wherein the Point of Contact handles the intervention.

11. The method of claim 7, wherein the subterranean operation is selected from a group consisting of a drilling operation and a hole cleaning operation.

12. The method of claim 11, wherein the subterranean operation is the drilling operation, wherein determining whether the subterranean operation is being performed at an optimal level comprises comparing one or more simulated drilling parameters with actual drilling parameters;

and wherein the drilling parameters are selected from a group consisting of downhole pressure, mud weight, drillahead hydraulics, flow rates, standpipe pressure, unit of gas, rate of penetration, torque and a combination thereof.

13. The method of claim 11, wherein the subterranean operation is the hole cleaning operation;

wherein the hole cleaning operation is performed by a rig; and

wherein determining whether the subterranean operation is being performed at an optimal level comprises determining whether the rig is sliding.

14. The method of claim 7, wherein determining whether the subterranean operation is being performed at an optimal level comprises determining whether there is at least one of an excessive surge pressure, an excessive swab pressure, influx, Pack-Off, wellbore breathing, hole enlargement, lost returns, and a combination thereof.

15. A method of optimizing performance of a subterranean operation comprising:

providing one or more sensors;

wherein the one or more sensors gather data relating to performance of the subterranean operation;

monitoring data gathered by the one or more sensors to identify one or more operational conditions;

identifying need for an intervention based on the one or more identified operational conditions;

determining an intervention level based on the gathered data;

generating an intervention corresponding to the determined intervention level; and

responding to the intervention based on the intervention level.

16. The method of claim 15, wherein the one or more operational conditions are selected from a group consisting of excessive Surge pressure, excessive Swab pressure, influx, Pack-Off, wellbore breathing, hole enlargement, and lost returns.

17. The method of claim 15, wherein the subterranean operation is a drilling operation.

18. The method of claim 15, wherein monitoring data gathered by the one or more sensors to identify one or more operational conditions comprises comparing actual data with simulated data to identify the one or more operational conditions.

19. The method of claim 15, wherein the intervention level is selected from a group consisting of a low level intervention, a medium level intervention, and a high level intervention.

20. The method of claim 19, wherein responding to the intervention based on the intervention level comprises:

probing the system to continue to monitor the identified operational condition if a low level intervention is generated;

at least one of compiling a list of mitigation options to resolve the condition and notifying an operator about the condition if a medium level intervention is generated; and

at least one of issuing a notification of a significant adverse event, compiling a list of mitigation options to resolve the condition and notifying the operator about the condition if a high level intervention is generated.