Using Data-Driven Technologies to Accelerate the Field Development Planning Process for Mature Field Rejuvenation

Abstract

Abstract A data-driven technology and associated workflow for fast identification of field development opportunities in mature oil fields is presented, which accelerates the subsurface field development planning process and reduces the time requirement from months to weeks. Standard workflows in geology and engineering have been automated or machine-assisted, enabling field rejuvenation opportunities to be identified without requiring full-field simulation models. This technology is ideally suited for large, complex oil fields with large data sets (e.g. thousands of wells producing over many decades), and has been deployed in cases of brownfield rejuvenation, asset evaluation during acquisition activities, and as an independent validation system within internal review programs for large oil companies. The opportunities generated using these techniques are subject to a rigorous technical vetting by experienced subject matter experts, with the highest confidence opportunities being matured and high- graded. A case study is presented for a large, stratigraphically complex waterflood in North America, wherein a subsurface field development plan was prepared using these techniques, with specific opportunities in well operations, production uplift, recompletion targeting pay-behind-pipe, infill and step-out drilling locations, and waterflood optimization.