Development Optimization Using Reservoir Response Surfaces: Methods for Integrating Facility and Operational Options

The objective of a field development optimization process, or workflow, is to investigate various options and determine a course of action that will deliver the largest expected value from an asset. The analysis is often complicated by uncertainty in important inputs. Ideally, operators desire workflows and tools that integrate reservoir engineering and optimization principles in a fast-solving model that can be used to explore the full range of the uncertain inputs. This need is acute in the screening and concept selection stage where the primary objective is to determine the sensitivity of competing concepts to the sources of uncertainty. In these early stages, model results can be used to determine whether additional information should be collected, and to narrow down the number of competing options. The objective of this research is the development of a workflow and tool that integrates reservoir response surfaces within a project optimization model that contains facility and operational options, and to use this model to investigate the impacts of uncertainty on decision making. The integration of technical options is critical because a static view of capital investment and facility constraints causes a systematic undervaluation and can introduce error to development decisions. The new workflow and integrated reservoir-economic optimization tool developed in this research leverage methods and engineering work products that are already known to industry, for example, experimental design (ED) and response surface methods (RSMs). A demonstration is provided for a gas flood project using a stylized reservoir. Specifically, we investigate the selection of initial well configurations and injection capacities while simultaneously accounting for the options to update these decisions after production information is acquired in the early periods of production. The workflow is used to optimize the development of a gas flood. As a second step, the workflow is used to solve a value of information problem.