Data-driven methods and systems for improving oil and gas drilling and completion processes

A method, implemented at a computer system that includes at least one processor, for optimizing resource allocation at a hydrocarbon extraction site, the method comprising:

• accessing a drilling and completion report that includes current operational description data for at least one hydrocarbon extraction task that implements a hydrocarbon extraction rig at the drilling and completions site;
• instantiating a natural language processing unit configured to analyze and mine the accessed drilling and completion report for specific portions of operational description data;
• accessing one or more portions of historical operational data and production forecast data related to the at least one rig;
• instantiating a machine learning unit configured to analyze the current and historical rig operation data to identify drilling and completion phase and non-productive time periods during which the hydrocarbon extraction task is halted or is producing below a specified minimum productivity level;
• and
• generating an optimized rig scheduling sequence for the at least one rig that optimizes an objective function by allocating resources to the hydrocarbon extraction task during times when productivity is projected to be above the specified minimum production level,
• wherein the at least one rig is operated according to the optimized rig scheduling sequence.

A system for managing a drilling and completions process at a hydrocarbon extraction site, comprising:

• at least one piece of drilling and completions equipment;
• one or more hardware sensors operatively connected to the piece of drilling and completions equipment;
• one or more processors;
• one or more computer-readable media that store computer-executable instructions which, when executed, perform the following:
• access data generated by one or more hardware sensors implemented by one or more pieces of drilling and completion equipment at the hydrocarbon extraction site;
• format the accessed sensor data into a form readable by at least one data mining algorithm;
• mine the formatted sensor data to identify one or more characteristics related to the one or more pieces of drilling and completion equipment;
• access one or more portions of historical data related to the hydrocarbon extraction site relating to the one or more pieces of drilling and completion equipment, wherein the accessed historical data is integrated with the formatted sensor data;
• compute one or more drilling and completion performance indicators configured to identify inefficiencies based on the characteristics identified for the drilling and completion equipment and the integrated historical and sensor data;
• and
• upon identifying the at least one drilling and completion inefficiency, perform at least one remediation step to resolve the at least one identified inefficiency.