Smart reservoir management in the oil and gas industry

Abstract The oil and gas (O&G) industry is facing intense pressure to improve operational efficiencies as oil and gas prices continue to fluctuate. Many O&G companies are now rushing into a digital transformation race where digital technologies would be used to create new—of transform traditional—processes. This chapter focuses on the exploration and production part of the O&G industry (the upstream sector), which is primarily concerned with finding and producing crude oil and natural gas. It argues that the current analytical workflow and decision-making process are suboptimal and inadequate for full digital transformation. Higher levels of machine intelligence and automation are needed to bring extreme efficiency to O&G operations. Furthermore, augmentation (e.g., ability to infuse engineering experience into advanced analytics and data-driven solutions) is an absolute necessary component of any smart reservoir management framework, and, therefore, it is a critical element of the digital transformation itself. This chapter proposes specific methods for a more intelligent automation of the upstream business. It presents several (multidisciplinary) case studies that demonstrate the value of automated data processing, systematic engineering and geological workflows, and predictive analytics.