An Innovative Workflow for Appropriate Selection of Subsurface-Surface Model Integration Scheme Based on Petroleum Production System Nature, User Needs, and Integrated Simulation Performance

Abstract

AbstractThe generation of portfolio of opportunities from hydrocarbon reservoirs requires, because of its nature defined by process, more reliable production scenarios based on better decisions making from the whole petroleum production system (reservoir-wells-surface facilities). Therefore, a truly production forecasting would be obtained if boundary conditions imposed by reservoir, well completion and surface network are considered through integration schemes that allow to emulate, as accurate as possible, operating conditions expected (flow and pressure behavior) from network–well to reservoir.This paper introduces an innovative workflow, developed for explicit simulation of subsurface-surface models, to assist assessment of IAM schemes (Integrated Asset Modeling). This assessment was based on a qualitative algorithm focused on defining the most appropriate subsurface-to-surface integrated modeling, considering the petroleum production system nature and users needs. In addition, a comparative analysis of performance variables from integrated simulation output (computing time, material balance error, among other) was implemented by combining both reservoir-network coupling and balancing methods available in the modeler used (AVOCET™). A test model was considered for the assessment of the proposed workflow.Results showed that better decision making is reached out for integrated petroleum production system simulation when the proposed workflow is implemented, depending on the nature of flow and pressure behavior through the system, simulation performance, and users needs (reservoir, production, or processing engineer). In addition, it is suggested that a comparative assessment can be considered to evaluate reservoir-network simulation performance if both convergence and stability of the integrated model and user expertise is on demand.For the test model, better performance was obtained from coupling scheme at wellhead, with both the lowest computing time and material balance error percentage of fluids, followed by those from bottomhole coupling scheme. As far as reservoir-network balancing methods concern, results showed that balancing controlled by reservoir simulator presented shorter computing time as much as lower oil, water, and gas material balance error percentage, compared with the others reservoir-network balancing methods tested.