Minimizing Gathering Centers Water Production by Utilizing a Digital Twin of the Asset: A KOC North Kuwait Case Study

Abstract Increasing water production in a mature asset is one of the critical issues facing most fields around the world. Subsurface uncertainties and poor water injection strategies have led to a significant and unintended increase in water-cut. This paper will discuss in detail how a digital twin of the well and surface network model was utilized to significantly reduce water production while maintaining or increasing oil production. Custom-built workflows were created, employing advanced algorithms to identify optimum criteria, such as changing parameters in artificial lift, wellhead chokes, or closing low oil-producing wells. The algorithm performed several thousand iterations, taking into consideration water handling costs and current oil prices while optimizing production. A dedicated Automated Water Production Optimization (AWPO) workflow was created to achieve the goal of minimizing water production. This workflow is part of a larger system that integrates well modeling, surface network modeling, calibration of chokes and surface pipeline networks. Custom-built workflows check the quality of well models and real-time data. The input to the AWPO workflow is a calibrated surface network model. A simulated annealing algorithm is utilized to optimize water production. The algorithm runs several thousand iterations to adjust artificial lift parameters, choke settings, and even closing of wells while maintaining current oil production rates or slightly reducing oil production, but only when the ratio of water handling cost to current crude oil price is significantly high. This means that even though oil production may slightly reduce, there will be a large reduction in water handling costs. The workflow ensures that all operational constraints, such as pumps being within the operational envelope, motor load within set tolerable limits, and flowing bottomhole pressure above bubble point pressure, are honored. Current, optimized, and total costs of optimization are calculated at the back end. The AWPO workflow runs on a daily basis for eight gathering centers, accounting for more than half a million barrels of oil production and over a million barrels of water production per day. Current runs have shown that AWPO recommendations result in a reduction of several thousand barrels of water production and save thousands of dollars in water handling costs. The workflow plays a significant role by providing specific actions to the field development and production operations teams on which wells to target and what actions to take to reduce water production. Many existing methodologies have mainly concentrated on targeting the subsurface domain or completion technology to reduce water production. The approach used in this paper, which involves utilizing custom-built automated workflows and algorithms with a digital twin of the well and surface network model to minimize water production, is a pioneering idea.