Real-time tool yield calibration of mud motor
A method that may comprise disposing a bottom hole assembly into a formation, wherein the bottom hole assembly comprises a mud motor, identifying a first segmented data set for a slide mode of the mud motor, and identifying a second segmented data set for a rotate mode of the mud motor. The method may further comprise calibrating the mud motor at least in part using a Reversible Jump Markov Chain Monte Carlo (RJMCMC), wherein the RJMCMC uses at least in part the first segmented data set and the second segmented data set.
1 . A method comprising:
disposing a bottom hole assembly that comprises a steering sub into a formation taking a plurality of directional data measurements with one or more sensors disposed on the bottom hole assembly, wherein the plurality of directional data measurements comprises one or more slide modes and one or more rotate modes that are performed by the steering sub;
segmenting the plurality of directional data measurements into the one or more slide modes and the one or more rotate modes using at least in part a Reversible Jump Markov Chain Monte Carlo (RJMCMC);
calibrating the steering sub in real time based at least in part on the segments to determine a tool yield between one or more steering inputs and responses measured in the plurality of directional data measurements; and
steering the bottom hole assembly with the calibrated steering sub.
2 . The method of claim 1 , wherein the one or more steering inputs are a toolface measurement or a steering ratio.
3 . The method of claim 1 , wherein the RJMCMC removes noise from the plurality of directional data measurements.
4 . The method of claim 1 , wherein the segmenting of the plurality of directional data measurements is determined using one or more perturbations, wherein the one or more perturbations are a death move, a birth move, or an update move.
5 . The method of claim 1 , further comprising cataloging the tool yield.
6 . The method of claim 1 , further comprising applying a weight to each of the plurality of directional data measurements.
7 . The method of claim 1 , further comprising removing one or more duplicates and one or more outliers from the plurality of directional data measurements.
8 . The method of claim 1 , further comprising identifying an initial noise level form the plurality of directional data measurements.
9 . A system comprising:
a bottom hole assembly that comprises:
a steering sub that steers the bottom hole assembly; and
one or more sensors that take a plurality of directional data measurements that comprise one or more slide modes and one or more rotate modes that are performed by the steering sub; and
an information handling system configured to:
segment the plurality of directional data measurements into the one or more slide modes and the one or more rotate modes using a Reversible Jump Markov Chain Monte Carlo (RJMCMC);
calibrate the steering sub in real time based at least in part on the segments to determine a relationship between one or more steering inputs and responses measured in the plurality of directional data measurements; and
steer the bottom hole assembly with the calibrated steering sub.
10 . The system of claim 9 , wherein the one or more steering inputs are a toolface measurement or a steering ratio.
11 . The system of claim 9 , wherein the RJMCMC removes noise from the plurality of directional data measurements.
12 . The system of claim 9 , wherein the segmenting of the plurality of directional data measurements is determined using one or more perturbations.
13 . The system of claim 12 , wherein the one or more perturbations are a death move, a birth move, or an update move.
14 . One or more non-transitory machine-readable media including instructions executable by a processor, instructions comprising:
instructions to take a plurality of directional data measurements with one or more sensors disposed on a bottom hole assembly, wherein the plurality of directional data measurements comprises one or more slide modes and one or more rotate modes that are performed by a steering sub;
instructions to segment the plurality of directional data measurements into the one or more slide modes and the one or more rotate modes using a Reversible Jump Markov Chain Monte Carlo (RJMCMC);
instructions to calibrate the steering sub in real time based at least in part on the segments to determine a relationship between one or more steering inputs and responses measured in the plurality of directional data measurements; and
instructions to steer the bottom hole assembly with the calibrated steering sub.
15 . The machine-readable media of claim 14 , wherein the one or more steering inputs are a toolface measurement or a steering ratio.
16 . The machine-readable media of claim 14 , wherein the RJMCMC removes noise from the plurality of directional data measurements.
17 . The machine-readable media of claim 14 , wherein the segmenting of the plurality of directional data measurements is determined using one or more perturbations.
18 . The machine-readable media of claim 17 , wherein the one or more perturbations are a death move, a birth move, or an update move.
19 . The machine-readable media of claim 14 , further comprising instructions to apply a weight to each of the plurality of directional data measurements.
20 . The machine-readable media of claim 14 , further comprising instructions to remove one or more duplicates and one or more outliers from the plurality of directional data measurements.