Large Scale Subsurface and Surface Integrated Asset Modeling - An Effective Outcome Driven Approach

Abstract

Abstract Identifying opportunities in the installed capacity and proactively mitigating the limiting factors are paramount objectives for pursuing profitable production assurance. Although integrated asset modeling has been the de facto technology for supporting production planning and optimization work processes, its application is not fully adopted as it presents challenges when attempted to be used in a large-scale of multiple oil and gas assets. This paper describes ADNOC’s innovative approach to develop a large scale subsurface to surface integrated asset modeling (LSSSIAM) solution by focusing on the desired business outcome. The paper introduces a new concept of right complexity modeling (RCM) to drive the type and level of complexity of the model/simulation based on the desired business outcome and other factors that influence the quality of the decision-making process. The methodology has been applied on a large-scale of multiple assets for effective production assurance that integrates the subsurface to the surface physical phenomena as required by the desired business outcome—the technical assurance of production plans within the context of a country. For the presented example, the proposed methodology resulted in the design of a solution where the subsurface phenomena are represented with a data-driven model to specifically address the requirements of the decision-making process which the solution supports. This resulted in the development of a first-of-its-kind countrywide production model that rigorously considers the properties and physics from the wells to the point of supply while also considering the subsurface phenomena as related to the production potential of the reservoirs and wells. The solution leverages the rigor of first-principle reservoir models to obtain a data-driven proxy model suitable for integration with a first-principle model covering more than 7,000 wells, multiple network and asset facilities, and a supply point transfer countrywide network. The solution can run in a matter of seconds, allowing for the optimization of a desired objective function or the effective analysis of operational scenarios, which can include short- and mid-term production assurance, opportunities identification to increase production to capture value opportunities from a country-wide production capacity context, and compensating for possible shortfalls resulting from unplanned operational disturbances in other assets.