Drilling control

A system comprising:

• a processor;
• memory accessible to the processor;
• processor-executable instructions stored in the memory and executable by the processor to instruct the system to:
• issue control instructions by a controller to control rig equipment for drilling of a borehole in a subsurface environment, wherein the rig equipment comprises a drawworks for control of weight-on-bit of a drillstring disposed in part in the borehole, and wherein the controller comprises a tunable weight-on-bit set point control loop;
• during the drilling of the borehole, receive sensor data as feedback;
• dynamically determine a tuning parameter value for the tunable weight-on-bit set point control loop using the feedback and an agent, wherein the agent comprises a trained machine learning model, and wherein, in a training phase, the trained machine learning model is trained using a controller and plant model and a reward function customized to make the agent prioritize pre-defined drilling behavior;
• determine a control instruction using the controller and the tuning parameter value for the tunable weight-on-bit set point control loop in the tunable weight-on-bit set point control loop;
• and
• issue the control instruction by the controller to control the rig equipment for drilling of the borehole according to the pre-defined drilling behavior.

One or more computer-readable storage media comprising computer-executable instructions executable to instruct a computing system to:

• issue control instructions by a controller to control rig equipment for drilling of a borehole in a subsurface environment, wherein the rig equipment comprises a drawworks for control of weight-on-bit of a drillstring disposed in part in the borehole, and wherein the controller comprises a tunable weight-on-bit set point control loop;
• during the drilling of the borehole, receive sensor data as feedback;
• dynamically determine a tuning parameter value for the tunable weight-on-bit set point control loop using the feedback and an agent, wherein the agent comprises a trained machine learning model, and wherein, in a training phase, the trained machine learning model is trained using a controller and plant model and a reward function customized to make the agent prioritize pre-defined drilling behavior;
• determine a control instruction using the controller and the tuning parameter value for the tunable weight-on-bit set point control loop in the tunable weight-on-bit set point control loop;
• and
• issue the control instruction by the controller to control the rig equipment for drilling of the borehole according to the pre-defined drilling behavior.