Determining optimal infill well placements is a complex problem that depends on reservoir properties and specifications of well and surface network. A numerical simulation is often the most appropriate method to evaluate the feasibility of the candidates. An integrated asset model of A field in the Middle East is built that couples a subsurface reservoir model with a surface network model. The integrated asset model is used to find optimal locations of 10 infill wells which are scheduled to drill in the future.
This paper proposes a step-wised approach for finding multiple infill well locations considering constraints of surface network. Firstly, an optimization process is conducted for all infill wells using an evolution strategy. Next, the same process is repeated exclusive of some wells, whose locations are already determined from the 1st optimization. This step improves an efficiency of the optimization and therefore, gives increased cumulative oil production results. Finally, integrated asset models are constructed for the 5 best cases, and elevation profiles of flowlines and trunklines are extracted from a geographic information system (GIS) at this time.
The optimal well locations are quite far from previous producing wells. It is good for avoiding production interferences, although these locations have negative impacts on delivering produced fluid to a facility because of pressure losses. The integrated asset model could evaluate several effects simultaneously and could give practical infill well locations for the target field.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.