A method for predicting and optimizing an ROP for oil and gas drilling based on Bayesian optimization includes: acquiring raw drilling data according to a preset sampling period, constructing an initial sample data set based on the raw drilling data, constructing an ROP prediction model based on the initial sample data set, and predicting an ROP at a next sample point through a Gaussian process regression based on the ROP prediction model. The present invention realizes rapid analysis of historical drilling data and accurate prediction of an ROP range at a sample point in a feasible domain. The method can obtain an optimized ROP and an optimized engineering parameter through Bayesian optimization, and obtain an engineering parameter corresponding to an optimal ROP. The method has few restrictions on the drilling engineering parameter and the raw formation parameter, improves prediction accuracy, and avoids the problem of blurred parameter value boundaries.

A method for predicting and optimizing an ROP for oil and gas drilling based on Bayesian optimization includes: acquiring raw drilling data according to a preset sampling period, constructing an initial sample data set based on the raw drilling data, constructing an ROP prediction model based on the initial sample data set, and predicting an ROP at a next sample point through a Gaussian process regression based on the ROP prediction model. The present invention realizes rapid analysis of historical drilling data and accurate prediction of an ROP range at a sample point in a feasible domain. The method can obtain an optimized ROP and an optimized engineering parameter through Bayesian optimization, and obtain an engineering parameter corresponding to an optimal ROP. The method has few restrictions on the drilling engineering parameter and the raw formation parameter, improves prediction accuracy, and avoids the problem of blurred parameter value boundaries.

Disclosed are methods, systems, and computer-readable medium to perform operations including: receiving real-time drilling data of a drilling operation of drilling a wellbore; using the drilling data to calculate at least one indicator of a borehole cleaning efficiency of the drilling operation; detecting, based on the least one indicator of the borehole cleaning efficiency, a drilling problem with the drilling operation; determining a corrective action to avoid or mitigate the drilling problem; and performing the corrective action to avoid or mitigate the drilling problem.

Disclosed are methods, systems, and computer-readable medium to perform operations including: receiving real-time drilling data of a drilling operation of drilling a wellbore; using the drilling data to calculate at least one indicator of a borehole cleaning efficiency of the drilling operation; detecting, based on the least one indicator of the borehole cleaning efficiency, a drilling problem with the drilling operation; determining a corrective action to avoid or mitigate the drilling problem; and performing the corrective action to avoid or mitigate the drilling problem.

The invention relates to a method performed by a control device for controlling a feeding distance and feeding rate in a rock drilling unit. The rock drilling unit comprising: a feeding device for feeding at least one drill rod and a drill bit in an axial direction; a rotating device; and a distance and rate measuring device comprising at least one rotational target wheel configured to be driven by the feeding device and at least one sensor device connected to the control device, the method comprising: controlling the feeding device to move in the axial direction; determining the feeding distance from a first position and the feeding rate of the feeding device from the rotational motion of the at least one rotational target wheel; and controlling the feeding device depending on the determined feeding distance and feeding rate of the feeding device.

The invention relates to a method performed by a control device for controlling a feeding distance and feeding rate in a rock drilling unit. The rock drilling unit comprising: a feeding device for feeding at least one drill rod and a drill bit in an axial direction; a rotating device; and a distance and rate measuring device comprising at least one rotational target wheel configured to be driven by the feeding device and at least one sensor device connected to the control device, the method comprising: controlling the feeding device to move in the axial direction; determining the feeding distance from a first position and the feeding rate of the feeding device from the rotational motion of the at least one rotational target wheel; and controlling the feeding device depending on the determined feeding distance and feeding rate of the feeding device.

The aspects described herein assist in mitigating vibrations arising from torsional energy accumulating on a drill string in a wellbore during drilling operations. A first sensor obtains torque measurement data at or near the top drive of the drilling rig. A second sensor may obtain weight on bit information. The controller receives the measured data, combines it with a first gain to obtain a first output value and a second gain to obtain a second output value. The first output value is provided to the top drive to adjust a speed of operation of the top drive, and the second output value is provided to the axial drive providing motion along a vertical axis of the drilling rig to adjust a speed of the vertical motion. In combination, the adjustments to the top drive and axial drive movements mitigate stick-slip in an automated manner more effectively than either individually.

Drilling parameters for a wellbore operation can be determined based on resonance speeds. For example, a system can receive real-time data for a drilling operation that is concurrently occurring with receiving the real-time data. The system can determine, for a drilling depth, a rotations-per-minute (RPM) value corresponding to a resonance speed based on a weight-on-bit (WOB) value and the real-time data. The system can generate a plot of the WOB value and the RPM value corresponding to the resonance speed. The system can determine drilling parameters for the drilling operation based on the plot. The drilling parameters can exclude, for the WOB value, the RPM value corresponding to the resonance speed.

Drilling parameters for a wellbore operation can be determined based on resonance speeds. For example, a system can receive real-time data for a drilling operation that is concurrently occurring with receiving the real-time data. The system can determine, for a drilling depth, a rotations-per-minute (RPM) value corresponding to a resonance speed based on a weight-on-bit (WOB) value and the real-time data. The system can generate a plot of the WOB value and the RPM value corresponding to the resonance speed. The system can determine drilling parameters for the drilling operation based on the plot. The drilling parameters can exclude, for the WOB value, the RPM value corresponding to the resonance speed.

Methods and systems for determining caving volume estimations based on logging data and geomechanical models are provided. For example, a system can receive image log data measured during a drilling operation in a wellbore. The system can receive an identification of a breakout in a subterranean formation around the wellbore. The system can determine, using the image log data, a breakout angular width for the breakout. The system can determine a breakout depth for the breakout. The system can determine a caving volume based on the breakout depth and the breakout angular width substantially contemporaneously with the drilling operation. The system can output the caving volume estimation for use in substantially contemporaneously adjusting a drilling parameter for the drilling operation.