Reservoir characterization based on data incorporation throughout production development

Abstract

The oil and gas industry faces multiple challenges, especially in integrating well acquisition data and production planning into flow models early in projects to improve predictive accuracy. This study emulates the production development of an oilfield from exploration to initial development, focusing on reducing uncertainty and enhancing reservoir characterization. The development process follows an industry-standard data acquisition plan, prioritizing exploratory wells initially and gradually decreasing data acquisition for subsequent wells. Initially, wells were assessed with open-hole profiles, drill stem tests (DST), and production logging tools (PLT). In later stages, data acquisition was simplified to open-hole profiles and production histories.

The project production strategy is iteratively updated with each phase of data incorporation, applied to geostatistical realizations to improve model accuracy. Geological uncertainties are considered, while economic uncertainties are excluded. The methodology is based on a closed-loop field development (CLFD) approach, adapted to enhance reservoir characterization. Preconditioning techniques and adjustments to acquisition scope aimed at improving outcomes were implemented.

The findings demonstrate effective reduction of uncertainty and optimization of production strategy, achieving accurate predictions for key metrics like monetary value, cumulative oil and water production, water injection, and oil recovery factor. The inclusion of dynamic data early in the project proved instrumental in minimizing uncertainty, leading to optimized production strategies and improved reservoir characterization. These results underscore the value of incorporating dynamic data early in project development for enhanced predictive performance in reservoir management.