Development of Heterogeneous Immature Brownfield with Waterdrive Using Dynamic Opportunity Index: A Case Study from Iraqi Oilfields

Abstract

Abstract The developing of an immature brown oilfield through determining the optimal number and locations of infill wells pose extreme challenges due to high costs of drilling wells and uncertainty of geological and reservoir characteristic parameters. The improper well placement may lead to project failure. This paper presents a methodology to identify reservoir layers with high potential opportunities for optimal infill well placement in Nahr Umr reservoir of Subba oilfield. A full field numerical flow simulation model was constructed to assist in simulation the opportunity index and generate opportunity index (OI) which has been determined depending on static and dynamic properties. The generated OI maps for each layer in the reservoir assist in delineating the reservoir regions with favorable infill wells placement. This methodology was efficient, easy to apply and less time consuming as well as it reduce the uncertainty inherent to infill well placement. The presence of water aquifer drive and needing for waterflooding after few years of field life to maintain the field pressure, make the infill drilling with economic viability very crucial element in the field development plan. The performance of new wells, tested at different places of the field in the simulation model, had produced high watercut. It is very important to determine the reservoir opportunities zones in order to enhance sweeping efficiency and increase oil production rate from infill well. In this study a combination of extracted parameters from both static and dynamic models were used to generate opportunity index maps through writing codes into classic property calculator in the Eclipse-FloViZ commercial simulator software. In this case study of Nahr Umr reservoir in Subba oilfield the results showed distinct identification reservoir potential regions for each layer at the reservoir at last time step of history match. These regions showed high OI values that reflected the actually mapped oil in each layer at that time.