Approaches to directional drilling

A system comprising:

• a processor;
• memory accessible by the processor;
• processor-executable instructions stored in the memory and executable to instruct the system to:
• receive a well plan and determining a plurality of sections of the well plan;
• receive data from surface and downhole to determine a current location of a drill bit, the drill bit located on a bottom hole assembly of a drill string;
• analyze the well plan to automatically derive a plurality of trajectory constraints that are associated with each of the plurality of sections of the well plan;
• identify, based on a prior section of the plurality of sections and a future section of the plurality of sections, a current context at the current location of the drill bit, wherein the current context includes a current activity status of the bottom hole assembly;
• determine a plurality of trajectory candidates that pertain to respective paths from the current location of the drill bit to respective targets included within each of the plurality of sections of the well plan based on a consideration of the plurality of trajectory constraints;
• identify a plurality of trajectory contexts, each trajectory context of the plurality of trajectory contexts associated with at least one trajectory candidate of the plurality of trajectory candidates, wherein the plurality of trajectory contexts includes a plurality of candidate activity statuses associated with drilling the associated trajectory candidate of the plurality of trajectory candidates;
• generate a plurality of ranking properties for ranking of the plurality of trajectory candidates;
• apply a machine learning model to historical data, the plurality of ranking properties and the plurality of trajectory candidates, the machine learning model outputting an additional ranking property;
• add the additional ranking property to the plurality of ranking properties;
• assign, for the plurality of trajectory candidates, a plurality of weights based on the plurality of trajectory contexts, wherein, based on the plurality of trajectory contexts associated with the plurality of trajectory candidates, a first weight of the plurality of weights for a first trajectory candidate of the plurality of trajectory candidates is different than a second weight of the plurality of weights for a second trajectory candidate of the plurality of trajectory candidates, wherein assigning the plurality of weights results in a plurality of weighted ranking properties;
• generate a total cost for each trajectory candidate of the plurality of trajectory candidates, each trajectory candidate of the plurality of trajectory candidates associated with a cost function of a plurality of cost functions, each cost function of the plurality of cost functions including at least one weighted ranking property of the plurality of weighted ranking properties;
• using the total cost, generate a plurality of rankings, each ranking of the plurality of rankings associated with one of the plurality of trajectory candidates, wherein the plurality of rankings rank the plurality of trajectory candidates with respect to at least one other trajectory candidate of the plurality of trajectory candidates;
• using the plurality of rankings for each of the plurality of trajectory candidates, determine a working plan that includes an optimal path from the current location of the drill bit to reach a final target, wherein the working plan includes hardware specific drill command sequences to direct the drill bit along the optimal path;
• communicate the hardware specific drill command sequences to control the bottom hole assembly of the drill string to access the final target from the current location;
• and
• execute the hardware specific drill command sequences to steer the drill bit to the final target.

A non-transitory computer-readable storage medium storing instructions that when executed by a computer, which includes a processor performs a method, the method comprising:

• receiving a well plan and determining a plurality of sections of the well plan;
• receiving data from surface and downhole to determine a current location of a drill bit, the drill bit located on a bottom hole assembly of a drill string;
• analyzing the well plan to automatically derive a plurality of trajectory constraints that are associated with each of the plurality of sections of the well plan;
• identifying, based on a prior section of the plurality of sections and a future section of the plurality of sections, a current context at the current location of the drill bit, wherein the current context includes a current activity status of the bottom hole assembly;
• determining a plurality of trajectory candidates that pertain to respective paths from the current location of the drill bit to respective targets included within each of the plurality of sections of the well plan based on a consideration of the plurality trajectory constraints;
• identifying a plurality of trajectory contexts, each trajectory context of the plurality of trajectory contexts associated with at least one trajectory candidate of the plurality of trajectory candidates, wherein the plurality of trajectory contexts includes a plurality of candidate activity statuses associated with drilling the associated trajectory candidate of the plurality of trajectory candidates;
• generating a plurality of ranking properties for ranking of the plurality of trajectory candidates;
• applying a machine learning model to historical data, the plurality of ranking properties and the plurality of trajectory candidates, the machine learning model outputting an additional ranking property;
• adding the additional ranking property to the plurality of ranking properties;
• assigning, for the plurality of trajectory candidates, a plurality of weights based on the plurality of trajectory contexts, wherein, based on the plurality of trajectory contexts associated with the plurality of trajectory candidates, a first weight of the plurality of weights for a first trajectory candidate of the plurality of trajectory candidates is different than a second weight of the plurality of weights for a second trajectory candidate of the plurality of trajectory candidates, wherein assigning the plurality of weights results in a plurality of weighted ranking properties;
• generating a total cost for each trajectory candidate of the plurality of trajectory candidates, each trajectory candidate of the plurality of trajectory candidates associated with a cost function of a plurality of cost functions, each cost function of the plurality of cost functions including at least one weighted ranking property of the plurality of weighted ranking properties;
• using the total cost, generating a plurality of rankings, each ranking of the plurality of rankings associated with one of the plurality of trajectory candidates, wherein the plurality of rankings rank the plurality of trajectory candidates with respect to at least one other trajectory candidate of the plurality of trajectory candidates;
• using the plurality of rankings for each of the plurality of trajectory candidates, determining a working plan that includes an optimal path from the current location of the drill bit to reach a final target, wherein the working plan includes hardware specific drill command sequences to direct the drill bit along the optimal path;
• communicating the hardware specific drill command sequences to control the bottom hole assembly of the drill string to access the final target from the current location;
• and
• executing the hardware specific drill command sequences to steer the drill bit to the final target.