Data Analytics in Reservoir Engineering

Data analytics has been broadly applied to a variety of areas within the oil and gas industry including applications in geoscience, drilling, completions, reservoir, production, facility, and operations. However, we limit our discussion here primarily to reservoir engineering applications.

This book describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering. It also outlines the methodology and guidelines for building robust models for reporting, diagnosis, prediction, and recommendations, and it provides an overview with examples of successful applications of data analytics in reservoir engineering and illustrate advantages and pitfalls these methods

Sathish Sankaran is EVP of Engineering and Technology at Xecta Digital Labs. Prior to that he served as Engineering Manager of Advanced Analytics and Emerging Technology for Anadarko Petroleum Corporation. His work focuses on modeling and optimizing hydrocarbon production from reservoir to process plant, with emphasis on blending physics and data-driven methods.

Sebastien Matringe is currently Director of Reservoir Engineering at Hess Corporation. He previously held various leadership and engineering positions at Newfield Exploration, Quantum Reservoir Impact and Chevron. He holds a "Diplome d'inge-nieur" in Fluid Mechanics from ENSEEIHT in France and MS and PhD degrees in Petroleum Engineering from Stanford University. Additional authors of this book are Mohamed Sidahmed, Xian-Huan Wen, Luigi Saputelli, Andrei Popa and Serkan Dursun.

Mohamed Sidahmed serves as Machine Learning and Artificial Intelligence R&D Manager for Shell. He also serves as Director on the Board of Petroleum Data-Driven (PD2A) Technical Section of the SPE and Program Evaluator for ABET, dedicated STEM PEV contributing to the profession.