Halliburton Energy Services, Inc.

Vy Pho

Robert Phillip Darbe

Ketan Chimanlal Bhaidasna

Nazli Demirer

Shahin Tasoujian

Khunsa Hisham

Yuanyan Chen

Umut Zalluhoglu

Bipin Kumar Pillai

Jian Wu

Cili Sun

Yang Liu

Alexander Mathew Keller

Min Wu

Robert Alan Friedrich

Fernando Costa Oliveira Chagas

Shichao Xu

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.

Real-time tool yield calibration of mud motor

A method for calibrating a steering model may comprise estimating an initial condition for one or more variables in the steering model and calibrating the steering model with a Markov Chain Monte Carlo Simulation (MCMC). A drilling system may comprise a bottom hole assembly, a drill string connected to the bottom hole assembly, and an information handling system connected to the bottom hole assembly. The information handling system may be configured to process one or more measurements from the bottom hole assembly, calibrate a steering model based at least in part on the one or more measurements, adjust a control logic based at least in part on the steering model, and adjust the bottom hole assembly based at least in part on the control logic.

Probabilistic model calibration and estimation for drilling steering control

A computer-implemented method for drilling a curve section of a wellbore in a subsurface formation. The method comprises obtaining a curvature setpoint. The method comprises obtaining drilling process feedback from a drilling assembly drilling the curve section of the wellbore. The method comprises updating a scheduling parameter vector based on the drilling process feedback. The method comprises updating a controller, wherein the controller is configured with the scheduling parameter vector. The method comprises determining an error based on the curvature setpoint and the drilling process feedback. The method comprises inputting the error into the controller. The method comprises determining, via the controller, steering decisions based on the error and the scheduling parameter vector.

Robust linear parameter varying control design for automated curvature cruise

Systems and methods of the present disclosure are directed to systems and methods for controlling a wellbore drilling apparatus where the system may include a surface controller and a downhole controller. In certain instances, control of the drilling apparatus may be transferred from the surface controller to the downhole controller. The control of the drilling apparatus may be transferred to the downhole controller as the surface control monitors operation of the drilling operation. The surface controller may also send a command that transfers control of the drilling apparatus from the downhole controller to the surface controller.

Closed loop fully autonomous directional drilling

Aspects of the subject technology relate to systems and methods for improving mud motor trajectory controls. Systems and methods are provided for receiving control data from a mud motor trajectory controller, predefining a plurality of control modes based on the control data from the mud motor trajectory controller, achieving desired slide rotate ratios and toolface angles by solving an established objective function that mathematically represents operational preferences and system constraints for a selected control mode of the plurality of control modes, generating a modulation procedure that converts the slide-rotate ratios to a binary slide and rotate control sequence, and applying the modulation procedure to generate the binary slide and rotate control sequence.

Slide-rotate ratio mode optimization for mud motor trajectory control

A curvature cruise controller has been designed to maintain a desired curvature when drilling a curve section of a wellbore. The curvature cruise controller utilizes a model-based controller (such as an LQR controller) to generate steering inputs based on the desired curvature and attitude setpoints and real time measurements. The model-based controller is configured with a wellbore propagation model that characterizes the tool's response dynamics. The curvature cruise controller utilizes real time drilling operation parameters measurements to tune the model-based controller.

Model-based curvature cruise control design

Current disclosure proposes calibration methodology that uses the knowledge learned from historical data and real-time data to update a simplified physics-based borehole propagation model for real time steering control of a directional drilling system. The proposed methodology updates model parameters of the simplified physics-based model in real time through a process of setting up and optimizing an objective function, which indicates the difference between the estimated trajectory and the feedback from the real-time data. Penalizing terms, which prevent the parameters from deviating drastically from the prior knowledge of the parameter, and various components of the objective function are learned from the historical data. As a result, the updated model can accurately estimate and predict the system behavior allowing an input sequence of the system to be accurately mapped to the output response.

Techniques for calibrating borehole propagation model for direction drilling in real time

A method and system for estimating a wellbore curvature. The method may include disposing a rotary steerable system (RSS) into a borehole, storing a real-time curvature estimation for the borehole in an information handling system, wherein the information handling system is disposed on the RSS, taking a first attitude measurement at a first sensor, and taking a second attitude measurement at a second sensor. The method may further include applying a filter to at least the first attitude measurement and the second attitude measurement to form a filtered measurement set, performing a curvature estimation with the filtered measurement set to form an estimated curvature signal, comparing the estimated curvature signal to a curvature set point to find a difference, and adjusting at least one operating parameter of the RSS based on the difference.

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Houston, TX, United States of America

Vy Pho