Novel Integrated Approach for Waterflood Optimization in Mature Multilayer Reservoirs with Advanced Well Completions Using Capacitance Resistance Model

Abstract

Waterflooding is a widely-used secondary oil recovery technique employed in the oil industry. In mature oil fields, waterflooding becomes increasingly essential in order to maximize oil recovery and extend field life, but optimizing its performance remains a complex and challenging task. In recent years, there has been growing interest in developing integrated approaches combining reservoir simulation, well modeling, and data-driven techniques to improve waterflood performance. The Capacitance–Resistance Model (CRM) has been proven to be a fast and effective tool for predicting waterflooding and reservoir characterization. Previous studies have successfully applied CRM to waterflood management to increase oil recovery. This paper develops a novel integrated and iterative workflow for waterflooding optimization in mature fields using the CRM for multilayer reservoirs equipped with Interval Control Valves (ICVs). The proposed approach, which integrates geological and well data with CRM results, was validated using a benchmark field model named the Olympus. This new workflow will help to put connected injection and production wells in different groups to reduce computational costs. In addition, this workflow can be used to determine the optimized number and proper location of the ICVs inside production wells. We determined the workover programs for existing wells, such as installing sensors and ICVs, deepening the wells, or plug-backs. Finally, it can be used for determining optimal water injection rates and well control strategies, such as valve openings in different production layers. As a result, the oil recovery factor increased, and the NPV was maximized, respecting the Olympus field's economic and operational constraints.