Digital Integration to Realize the Limit (RTL) in the Giant Greater Burgan Reservoir

Abstract

KOC-SEK asset has the main goal of maintaining, increasing, and optimizing the production of the Greater Burgan, the largest clastic reservoir in the World. Discovered in 1938, Greater Burgan is a multilayer formation with large hydrocarbon volumes of different oil type (from heavy to light) for which a detailed characterization and exploitation strategy was required to develop a sustained asset production. With the asset facing multiple challenges to maximize recovery and sustain target production field rate, one of these challenges has been to optimize the segregation of a large number of wells into 15 gathering centres. This is to ensure de-bottlenecking and to address back-pressure issues of the production networks while flowing wells in their optimal operational envelope to avoid the rapid depletion of the reservoir and the increasing water production. Due to the vast number of wells, the intricate network, the limitations in the gathering system and the dynamic operations, maintaining and sustaining the reservoir performance requires continuous surveillance, rapid and robust understanding of the different variables at reservoir, well and network level to make timely decisions and maximize reservoir recovery. To support this, a standardized and integrated system based on data analytics and numerical models, has been developed in the context of Realize the Limit (RTL) of the Greater Burgan reservoir as a tool for the quick identification of potential oil gain opportunities, the evaluation of bottlenecks across all the production system, and track and measure the impact of different proposed operational and development scenarios to unlock potential production and support optimum production forecasting. The system has been developed in a digital framework, with inputs from a multi-disciplinary team to define the datasets, calculated parameters and visualization requirements related to reservoir properties, well completion status, operational parameters, and key indicators from subsurface and surface hydraulic models. These has been integrated to identify key performance issues involving several aspects of the reservoir's development and operational plans. Also, the process provides a high-level overview and a platform for all asset groups including management, field development and operations, where observing the same set of results can initiate collective decisions that improve wells, network and facility management and enhancement recommendations.