Dr. Robello Samuel | Halliburton
TITLE: "Journey Ahead to Cyber Drilling System: Look Around and Look Ahead Engineering"
As the industry moves towards automated drilling system, detailed and comprehensive engineering analyses have also become very critical. Identifying the problems early can lead to better solutions for reducing associated costs and taking remedial action in an interconnected setting. This talk focuses on some key aspects of optimization highlighting the application of comprehensive engineering analyses to improve the overall life of the well. For this, not only detailed engineering analysis is needed to simulate the operation but also holistic optimization of the drilling parameters so as to drill and place the well effectively. Before automation, optimization should be carried out so that invisible loss time can be mitigated and drilling efficiency improved. Data-driven modeling and its application for predicting downhole environments coupled with engineering models could prove to be the future of drilling operations because they provide the potential to optimize highly complex drilling operations.
Dr. Robello Samuel is a Chief Technical Advisor and Technology Fellow, working with Halliburton since 1998, Director of Research at the Well Engineering Center for Inteligent Automation (WeRcia) and adjunct professor at University of Houston. He began his career working on rigs as a drilling engineer for nine years with ONGC and has more than 31 years of experience. He is an SPE Distinguished member, Distinguished Lecturer in 2014, received the SPE Drilling Engineering Award in 2016, and Gulf Coast SPE Drilling Engineering Award in 2013. He has taught on the faculty of various universities (concurrently) and has held an adjunct professor appointment for 13 years, at the University of Houston and 2 years at University of Southern California. He has published more than 170 papers, 12 drilling books, holds 15 patents, and 75 patent pending applications. Samuel holds BS and MS degrees in mechanical engineering, as well as MS and PhD degrees in petroleum engineering. His areas of interest are solving grand drilling challenges, modeling, optimization, data analytics and automation.