Abstract
Technology Focus The drilling industry is changing. Equipment providers, service companies, and drilling contractors are redefining the boundaries of their business interests, and these boundaries are evidently quite porous. Over the past year, workshops and symposia have made it clear that consideration of data and digitalization plays an important role in transforming companies in the drilling industry. Systems automation requires a digital backbone and offers significant performance, cost, and safety benefits. It is not surprising, therefore, that companies are exploring data-analytics techniques and drilling systems automation and that this exploration will define the new boundaries (if any remain) between segments of the well-drilling and -completion industry. The selected papers on drilling systems automation and management pick out various themes in this transformation. One paper deals with close collaboration between operator, drilling contractor, and service company in automating aspects of a drilling operation. Another paper deals with combined modeling and real-time surveillance and the required awareness by rig crews when operating rig-control systems. The third selection deals with the propagation of uncertainty in drilling and the development of a strategy to optimize performance against risk. These papers, and the alternative papers, illustrate the integration and collaboration that are necessary for drilling systems automation and management, which is transforming the traditional roles of equipment providers, service companies, and drilling contractors. One story that is somewhat obscured in the selected papers is that human-factors engineering will play an increasingly important role in our industry as we take care in specifying the role played in automated systems by crews both on the rig and remote to the rig. Recommended additional reading at OnePetro: www.onepetro.org. SPE 183022 Detection of Failures and Interpretation of Causes During Drilling Operations by Pål Skalle, IPT, NTNU, et al. SPE 184168 Using Bayesian Network To Develop Drilling Expert Systems by Abdullah S. Al-Yami, Saudi Aramco, et al. SPE/IADC 184611 Improving Torque-and-Drag Prediction Using the Advanced-Spline-Curves Borehole Trajectory by Mahmoud F. Abughaban, Colorado School of Mines, et al.
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