Method and system to automatically correct LWD depth measurements
A method for correcting errors in LWD depths includes performing torque and drag model analysis using drillstring weight, downhole friction, weight on bit, thermal expansion, rig heave and tide to produce a corrected time-depth file, wherein the torque and drag model is automatically calibrated using effective block weight, drillpipe wear, and sliding friction; and correcting time-based LWD data using the corrected time-depth file to produce depth-corrected LWD data. A system for correcting errors in LWD depths includes a processor and a memory that stores a program having instructions for: performing torque and drag model analysis using drillstring weight, downhole friction, weight on bit, thermal expansion, rig heave and tide to produce a corrected time-depth file, wherein the torque and drag model is automatically calibrated using effective block weight, drillpipe wear, and sliding friction; and correcting time-based LWD data using the corrected time-depth file to produce depth-corrected LWD data.
1. A method for correcting errors in logging-while-drilling (LWD) depths, comprising:
executing, via a processor, program instructions capable of:
performing torque and drag model analysis using drillstring weight, downhole friction, weight on bit, thermal expansion, rig heave and tide to produce a corrected time-depth file, wherein the torque and drag model is automatically calibrated using effective block weight, drillpipe wear, and sliding friction; and
correcting time-based LWD data using the corrected time-depth file to produce depth-corrected LWD data, wherein the torque and drag model is calibrated by performing:
calibrating the effective block weight to match in-slip actual hookload (ISAH);
calibrating the mud weight to match rotating actual hookload (RAH) and rotating model hookload (RAM); and
calibrating the effective sliding friction to match TIAH/TIMH and TOAH/TOMH, wherein TIAH is trip-in actual hookload, TIMH is trip-in model hookload, TOAH is trip-out actual hookload, and TOMH is trip-out model hookload; and
estimating an uncertainty of a mechanical stretch due to at least one of drillpipe wear and sliding friction by steps comprising determining a scattering of the TIAH and TOAH: and introducing scattering into at least one of the drillpipe wear and the sliding friction to match the scattering of the TIAH and TOAH.
2. The method of claim 1 , wherein the torque and drag model is automatically calibrated using mud weight as an additional factor.
3. The method of claim 1 , further comprising correcting rig heave errors, tide errors, or both rig heave and tide errors in the depth-corrected LWD data.
4. The method of claim 1 , further comprising correcting thermal expansion errors in drillpipe.
5. The method of claim 1 , further comprising estimating uncertainty of depth correction due to mechanical stretch.
6. The method of claim 5 , wherein the estimating of the uncertainty is performed by analyzing a distribution of values of a parameter selected from the group consisting of mud weight, drillpipe wear, sliding friction factor, and a combination thereof, provided TIAH and TOMH are monotonous functions of the combination, wherein TIAH is trip-in actual hookload and TOMH is trip-out model hookload.
7. The method of claim 1 , wherein calibrating the effective drillpipe wear and/or mud weight to match rotating actual hookload (RAH) and rotating model hookload (RAM) comprises calibrating the effective drillpipe wear and/or mud weight to match rotating actual hookload (RAH) and rotating model hookload (RAM).
8. A system for correcting errors in logging-while-drilling (LWD) depths comprising a processor and a memory that stores a program having instructions for:
performing torque and drag model analysis using at least one of drillstring weight, downhole friction, weight on bit, thermal expansion, rig heave and tide to produce a corrected time-depth file, wherein the torque and drag model is automatically calibrated using drillpipe wear; and
correcting time-based LWD data using the corrected time-depth file to produce depth-corrected LWD data, wherein the torque and drag model is calibrated by performing:
calibrating the effective block weight to match in-slip actual hookload (ISAH);
calibrating the effective drillpipe wear to match rotating actual hookload (RAH) and rotating model hookload (RAM) by steps comprising collecting ISAH data, determining a median of the ISAH data collected, and setting the effective block weight to the median of the ISAH data collected; and
calibrating the effective sliding friction to match TIAH/TIMH and TOAH/TOMH, wherein TIAH is trip-in actual hookload, TIMH is trip-in model hookload, TOAH is trip-out actual hookload, and TOMH is trip-out model hookload; and
estimating an uncertainty of a mechanical stretch due to at least one of drillpipe wear and sliding friction by steps comprising determining a scattering of the TIAH and TOAH: and introducing scattering into at least one of the drillpipe wear and the sliding friction to match the scattering of the TIAH and TOAH.
9. The system of claim 8 , wherein the torque and drag model is automatically calibrated using at least one of effective block weight, sliding friction, and mud weight as an additional factor.
10. The system of claim 8 , wherein the program further comprises instructions for correcting rig heave errors, tide errors, or both rig heave and tide errors in the depth-corrected LWD data.
11. The system of claim 8 , wherein the torque and drag model is calibrated by further performing calibrating the mud weight to match rotating actual hookload (RAH) and rotating model hookload (RAM).
12. The system of claim 8 , wherein the program further comprises instructions for estimating uncertainty of depth correction due to mechanical stretch.
13. The system of claim 12 , wherein the estimating of the uncertainty is performed by analyzing a distribution of values of a parameter selected from the group consisting of mud weight, drillpipe wear, sliding friction factor, and a combination thereof, provided TIAH and TOMH are monotonous functions of the combination, wherein TIAH is trip-in actual hookload and TOMH is trip-out model hookload.
14. The system of claim 8 , wherein the program further comprises calibrating the effective mud weight to match rotating actual hookload (RAH) and rotating model hookload (RAM) comprises calibrating the effective drillpipe wear and/or mud weight to match rotating actual hookload (RAH) and rotating model hookload (RAM).
15. A non-transitory computer-readable medium containing computer instructions stored therein for causing a computer processor to perform:
performing torque and drag model analysis using tide to produce a corrected time-depth file, wherein the torque and drag model is automatically calibrated using at least one of effective block weight, drillpipe wear, and sliding friction; and
correcting time-based LWD data using the corrected time-depth file to produce depth-corrected LWD data, wherein the torque and drag model is calibrated by performing:
calibrating the effective block weight to match in-slip actual hookload (ISAH);
calibrating the effective drillpipe wear and mud weight to match rotating actual hookload (RAH) and rotating model hookload (RAM); and
calibrating the effective sliding friction to match TIAH/TIMH and TOAH/TOMH, wherein TIAH is trip-in actual hookload, TIMH is trip-in model hookload, TOAH is trip-out actual hookload, and TOMH is trip-out model hookload; and
estimating an uncertainty of a mechanical stretch due to at least one of drillpipe wear and sliding friction by steps comprising determining a scattering of the TIAH and TOAH; and
introducing scattering into at least one of the drillpipe wear and the sliding friction to match the scattering of the TIAH and TOAH.
16. The non-transitory computer-readable medium of claim 15 , wherein the torque and drag model is automatically calibrated using mud weight as an additional factor.
17. The non-transitory computer-readable medium of claim 15 , wherein the program further comprising instructions for correcting rig heave errors, tide errors, or both rig heave and tide errors in the depth-corrected LWD data.
18. The non-transitory computer-readable medium of claim 15 , wherein the torque and drag analysis further uses at least one of mud weight, drillstring weight, downhole friction, weight on bit, thermal expansion, rig heave and drillpipe wear to produce a corrected time-depth file.
19. The non-transitory computer-readable medium of claim 15 , wherein the program further comprising instructions for estimating uncertainty of depth correction due to mechanical stretch.
20. The non-transitory computer-readable medium of claim 19 , wherein the estimating of the uncertainty is performed by analyzing a distribution of values of a parameter selected from the group consisting of mud weight, drillpipe wear, sliding friction factor, and a combination thereof, provided TIAH and TOMH are monotonous functions of the combination, wherein TIAH is trip-in actual hookload and TOMH is trip-out model hookload.
21. The non-transitory computer-readable medium of claim 20 , wherein the parameter is the sliding friction factor.
22. The non-transitory computer-readable medium of claim 15 , wherein the program further comprises instructions for estimating an uncertainty of a mechanical stretch due to sliding friction, the instructions for estimating the uncertainty comprising:
determining a distribution profile of parameter values for (TIMH-TIAH)/(TIMH) and (TOAH-TOMH)/TOMH; and
calculating a spread and a mean of the parameter values.
23. The non-transitory computer-readable medium of claim 15 , wherein the instructions for calibrating the effective block weight to match in-slip actual hookload (ISAH) comprise instructions for:
collecting ISAH data;
determining a median of the ISAH data collected; and
setting the effective block weight to the median of the ISAH data collected.