Predicting drillability based on electromagnetic emissions during drilling

Patent metadata

Field	Value
Publication number	US-10344533-B2
Application number	US-201315030273-A
Country	US
Kind code	B2
Filing date	Oct 18, 2013
Priority date	Oct 18, 2013
Publication date	Jul 9, 2019
Grant date	Jul 9, 2019

Abstract

An embodiment of a method of predicting drilling assembly performance includes: acquiring measurements of electromagnetic (EM) radiation emitted due to destruction of formation materials by a drilling assembly during a drilling operation; selecting input parameters, the input parameters including drilling assembly parameters, operational parameters, and the measurements of the EM radiation; supplying the input parameters to a mathematical drillability model; and generating a rock drillability parameter using the drillability model and the input parameters, the rock drillability parameter providing an indication of drilling performance.

First claim

What is claimed is:

1. A method of predicting drilling assembly performance, comprising:
acquiring measurements of electromagnetic (EM) radiation emitted due to destruction of formation materials by a drilling assembly during a drilling operation, the acquired measurements of EM radiation emitted due to destruction of formation materials indicative of the type of the formation materials, wherein EM radiation measurements are obtained using a first sensor configured to measure a low frequency component of the EM radiation, a second sensor configured to measure a medium frequency component of the EM radiation, and a third sensor configured to measure a high frequency component of the EM radiation;
selecting input parameters from the acquired measurements of EM radiation;
supplying the input parameters to a mathematical drillability model;
generating a rock drillability parameter using the drillability model and the input parameters, the rock drillability parameter providing an indication of drilling performance;
selecting operating conditions for at least one of the drilling operation and a subsequent drilling operation based on the drillability model; and
performing at least one of the drilling operation and the subsequent drilling operation.

2. The method of claim 1 , wherein the mathematical drillability model is a neural network model.

3. The method of claim 1 , wherein the EM radiation is emitted as a result of crack formation and rock crushing in a region below a drill bit of the drilling assembly.

4. The method of claim 1 , wherein the operational parameters include a selected rate of penetration (ROP), and the drillability parameter includes a prediction of drill bit wear over time as a function of the ROP.

5. The method of claim 1 , wherein the input parameters are selected for a subsequent drilling operation, and the drillability parameter is generated based on the input parameters for the subsequent operation and the measurements of the EM radiation acquired during the drilling operation.

6. The method of claim 1 , wherein the operational parameters are provided by at least one surface control unit configured to at least one of monitor and control the operational parameters of the drilling operation.

7. The method of claim 6 , wherein the operational parameters and the measurements of the EM radiation are supplied and the rock drillability parameter is generated in real time during the drilling operation.

8. A system for predicting drilling assembly performance, the system comprising:
a drilling assembly including a drill bit connected to a drill string, the drilling assembly configured to be disposed in a borehole and perform a drilling operation;
a sensor device operatively associated with the drilling assembly, the sensor device configured to measure electromagnetic (EM) radiation emitted due to destruction of formation materials by the drill bit during the drilling operation and acquire measurement of the EM radiation, wherein EM radiation measurements are obtained using a first sensor of the sensor device configured to measure a low frequency component of the EM radiation, a second sensor of the sensor device configured to measure a medium frequency component of the EM radiation, and a third sensor of the sensor device configured to measure a high frequency component of the EM radiation; and
a processor in communication with the plurality of sensors, the processor configured to:
select input parameters from the acquired measurements of EM radiation;
supply the input parameters to a mathematical drillability model; and
generate a rock drillability parameter using the drillability model and the input parameters, the rock drillability parameter providing an indication of drilling performance.

9. The system of claim 8 , wherein the mathematical drillability model is a neural network model.

10. The system of claim 8 , wherein the processor is configured to receive the measurements of the EM radiation from a downhole processing unit, receive at least the operational parameters from a surface control unit, and provide the rock drillability parameter to the surface control unit.

11. The system of claim 10 , wherein the surface control unit is configured to adjust operating conditions of the drilling operation in real time based on the rock drillability parameter.

12. The system of 8 , wherein the sensor device includes a sensor configured to measure electric currents that flow in a closed circuit between the drilling assembly and a region below the drill bit during drilling.

13. The system of claim 8 , wherein the operational parameters include a selected rate of penetration (ROP), and the drillability parameter includes a prediction of drill bit wear over time as a function of the ROP.

14. A non-transitory computer readable media storing instructions for execution by a processing circuit performing a method comprising:
acquiring measurements of electromagnetic (EM) radiation emitted due to destruction of formation materials by a drilling assembly during a drilling operation, the acquired measurements of EM radiation emitted due to destruction of formation materials indicative of the type of the formation materials, wherein EM radiation measurements are obtained using a first sensor configured to measure a low frequency component of the EM radiation, a second sensor configured to measure a medium frequency component of the EM radiation, and a third sensor configured to measure a high frequency component of the EM radiation;
selecting input parameters from the acquired measurements of EM radiation;
supplying the input parameters to a mathematical drillability model; and
generating a rock drillability parameter using the drillability model and the input parameters, the rock drillability parameter providing an indication of drilling performance;
selecting operating conditions for at least one of the drilling operation and a subsequent drilling operation based on the drillability model; and
performing at least one of the drilling operation and the subsequent drilling operation.

15. The non-transitory computer readable media storing instructions for execution by a processing circuit performing a method of claim 14 , wherein the mathematical drillability model is a neural network model.

16. The non-transitory computer readable media storing instructions for execution by a processing circuit performing a method of claim 14 , wherein the operational parameters are provided by at least one surface control unit configured to at least one of monitor and control the operational parameters of the drilling operation.

17. The non-transitory computer readable media storing instructions for execution by a processing circuit performing a method of claim 16 , wherein the operational parameters and the measurements of the EM radiation are supplied and the rock drillability parameter is generated in real time during the drilling operation.

18. The non-transitory computer readable media storing instructions for execution by a processing circuit performing a method of claim 14 , further comprising selecting operating conditions for at least one of the drilling operation and a subsequent drilling operation based on the drillability model.

Assignees

• Baker Hughes Inc
• Dubinsky Zarema
• Baker Hughes A Ge Co Llc

Inventors

• Dashevsky Yuliy A
• Terentev Sergey A
• Dorovsky Vitaly N
• Dubinsky Vladimir

Classifications

• G06F2111/10

  Numerical modelling · CPC title

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• E21B12/02

  Wear indicators · CPC title

• E21B45/00

  Measuring the drilling time or rate of penetration · CPC title

• E21B10/36

  Percussion drill bits ({with helical conveying portion E21B10/445;} characterised by wear resisting parts E21B10/46) · CPC title