Field data have proven that, when drilling extended laterals in the Midland Basin, the rate of penetration (ROP) will significantly decline after the rig's surface torque limit is reached. A high-specification drilling system was introduced to combat drilling torque issues which, in turn, produced record-setting performance. The approach is to identify which factors have the highest impact on drilling torque when using a motor-driven RSS (rotary steerable system) to drill a lateral longer than 10,000 ft. The field dataset analyzed included trajectory design, simulated torque and drag (T&D) versus actual values, hole cleaning effect, mid-lateral cleanup cycle effect, drilling parameters, target formation, and drilling fluids. The outcomes of torque reduction methods are explained in detail, and the final solution is verified with field results. Furthermore, an improvement plan to double the record lateral drilling speed in the Midland basin while staying within rig's capacity, is also discussed. When drilling laterals longer than 10,000 ft, a motor-driven RSS can produce an ROP of 300 to 400 ft/hr until the mid-lateral point where surface torque reaches 28,000 to 30,000 ft.lbf. This is also close to the torque limit of 5-in. drillpipe. Comparisons between on-bottom and off-bottom torque suggest an oil-based mud (OBM) system yields lower off-bottom torque and friction than a water-based mud (WBM). Simulated and actual T&D data were studied to find that wellbores with tangent profile in the intermediate section, commonly seen in pad well design for anti-collision, contribute to higher bottomhole assembly (BHA) side forces and friction after the wells drill into lateral section. Drilling parameters also plays a significant role in torque induction since they affect interactions between bit and rock. On the formation side, stringers such as limestone reduce torque. Analysis also concluded that mid-lateral cleanup cycles have minimal impact on torque reduction, and OBM is necessary to extend drilling performance in long lateral wells. An RSS powered by a high-specification motor drilled a 7,000-ft lateral in just 21 hours to set a new high mark in the Permian Basin.

Oil and gas companies are increasingly using data analytics to improve drilling performance. This paper provides an example of using a business intelligence (BI) tool to analyze drilling data in the Permian Basin. The BI tool helped to improve operation decisions through the use of a visual report. A database, consisting of massive amounts of historical drilling data, is analyzed using the BI tool to better understand drilling performance and predict average operations performance in the area. A historical drilling database is created based on the bottomhole assembly (BHA) run data and analyzed by the BI tool to review the well performance, in addition to identifying any hazards and summarizing the optimum drilling system during the planning phase. With the help of the BI tool, the drilling database can be displayed in an interactive way to further understand the drilling performance in the area; e.g., the top performing drill bit, drilling system, downhole mud motor configuration, and estimated drilling time for the section of interest. As a result, engineers will find it easier to identify the potentially top performing wells along with drilling hazards in offset wells. The engineers can evaluate the well details and identify the best drilling practices to optimize drilling performance and eliminate downhole incidents. Using the BI tool helps reduce the data mining time and offers a fast, improved method for gaining technical insights into the drilling operation. These descriptive analytics help to simplify the complex data sets, which are valuable for uncovering patterns that offer data set understanding. With the visualization results, experts can focus on data diagnostics analytics to make suggestions for drilling operation improvements and corrections. Furthermore, these analytical data can be used as inputs for more advanced predictive (forecast drilling performance) or prescriptive analytics (drilling optimization) that deliver real-time insights for making improved business decisions.