Drilling Limiters, Drilling Process Automation, and Drilling Data - Relating Downhole Measurements to Surface Process Automation

A new information management system connects a detailed, time-based well delivery plan to drilling operation management systems embedded in the rig controls to progress well construction safety, quality, delivery, and cost performance for an operator and drilling contractor. The technology team collected surface and downhole data and integrated it into a process to improve how drilling practices are evaluated, optimized, and refined within the well delivery plan. Drilling team operational practices have evolved over decades of experience and are the starting point for drilling operations process automation. Building on the authors’ work, the paper focuses on the integration of downhole data into documenting performance and using process control concepts to develop and refine drilling operations practices. The impact of wellbore environmental variables on drilling system performance will be explored to improve the automated processes available through the rig control systems. Identifying and addressing the drilling limiters using the high-resolution data enables drilling teams to standardize and automate practices for execution across basins using automated drilling systems. Higher frequency downhole data was captured over two horizontal hole sizes and 12 wells using different measurement tools and placement in the bottom hole assembly. The data is used to identify and quantify drilling limiters, many of which could not be identified from surface measurements. This guided drilling process automation work to address the dysfunctions. The resulting refinements are integrated into a time-based, sequenced drilling plan. The study identified many limiters, including motor back-drive, hole quality in slides, BHA bending due to hole quality, salt creep, hole breakout, and challenges with surface measurements. The data will be presented in repetitive tasks performed across a well. The time-sequenced, detailed implementation plan manages the order of these repetitive tasks. It refines the processes throughout the well cycle based on knowledge gained from surface and downhole data. The plan is based on drilling a stand of pipe as a cycle accounting for operations and systems to safely produce the desired result in wellbore quality, placement, and cycle time. The current state of the rig systems will be linked to the downhole behaviors and key drilling limiters for operations as different tasks are performed, such as on/off-bottom operations, sliding, rotating, and transitions between tasks. The authors will outline how they used process measurement data taken downhole and at the surface to identify and quantify drilling limiters, some of which could not be identified from surface parameters. Finally, the authors will outline a practical method for applying process improvement to the drilling system and explore opportunities for rig automation and drilling system redesign based on the repetitive tasks performed across a well.