Description
Data analytics is fundamentally transforming industries. In recent years, there is a growing application of digital technologies in oil and gas exploration and production. At the same time, oil and gas operations are becoming increasingly complicated with modern facility infrastructures, complex reservoirs, increased regulatory requirements, changing workforce demographics, the fast pace of unconventional-field development and ultimately with much more competition. Data Analytics in Reservoir Engineering focuses on how best to use data analytics to transform the decision-making process in characterizing reservoir parameters, model reservoir behavior and forecast performance.
Features & Benefits
- Demonstrates how data analytics can transform reservoir characterization and modeling
- Equips engineers to apply advanced analytics in forecasting reservoir performance
- Addresses modern challenges in complex reservoirs and unconventional field development
- Supports data-driven decision-making in high-stakes, fast-paced operational environments
- Bridges traditional engineering methods with digital tools to enhance reservoir understanding
Audience
- Reservoir engineers integrating data science into traditional workflows
- Petroleum engineers focused on modeling and performance forecasting
- Data scientists and analysts working in oil and gas applications
- Technical managers seeking improved decision-making tools for E&P operations
- Students and researchers exploring the intersection of reservoir engineering and analytics
About the Authors
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 Principal Advisor for Subsurface Technologies at Hess Corporation. He previously held various leadership and engineering positions at Newfield Exploration, Quantum Reservoir Impact and Chevron. He holds a ""Diplome d'ingenieur"" in Fluid Mechanics from ENSEEIHT in France and MS and PhD degrees in Petroleum Engineering from Stanford University.
Mohamed Sidahmed serves as Machine Learning and Artificial Intelligence R&D Manager for Shell. He also serves as Program Evaluator for ABET, dedicated STEM PEV contributing to the profession. There he contributes to the quality of technical education in collaboration with professionals from academia, industry and government.
Luigi Saputelli serves as a Reservoir Engineering Expert Advisor to the Abu Dhabi National Oil Company (ADNOC) with 30 years of experience. He has held various positions as Reservoir Engineer (integrated reservoir modeling, simulation, improved oil recovery projects, field development, researcher), Drilling Engineer (drilling and well planning projects, drilling rig automation) and Production Engineer (production modeling, engineering and operations workflow automation projects), in various operators and services companies around the world including PDVSA, Hess and Halliburton.
Xian-Huan Wen is a Chevron Fellow and the Team Leader of Reservoir Simulation and Optimization Research in Chevron Energy Technology Company. Wen holds a PhD degree in Water Resources Engineering from the Royal Institute of Technology, Sweden and a PhD degree in Civil Engineering from the Technical University of Valencia, Spain. Wen has authored or coauthored more than 80 papers and holds two US patents.
Andrei Popa currently serves as Reservoir Management Consultant within the Upstream Capability, Reservoir Management Framework Team. In addition to working for Chevron, Andrei has served as an Adjunct Associate Professor at University of Southern California for the last 11 years, where he has taught Applied Reservoir Engineering and Advanced Natural Gas Engineering. He has more than 23 years of experience leading artificial intelligence and machine learning projects and cross-functional teams focused on delivering complex optimization solutions and conceptual models across Chevron enterprise.
Serkan Dursun is Leader of Artificial Intelligence Center of Excellence CoP in Hydrocarbon Management Division at Saudi Aramco. He was Principal Data Scientist at Marathon Oil, Data Scientist at Schlumberger and Senior Technologist at Halliburton. He served as Adjunct Professor at University of Houston. He has 11 publications in IEEE & SPE and holds 9 US patents. He has special interest in Artificial General Intelligence (AGI), Conversational AI, and Explainable AI (XAI).
Details
Type: Softcover
Size: 6x9
Pages: 96
Published: 2020
ISBN: 9781613998205
