Optimizing Multiple-Field Scheduling and Production Strategy with Reduced Risk

Abstract

Abstract Large, multiple-field Exploration & Production (E&P) assets require long-term commitments of capital that are tied to decisions on facilities, wells, scheduling, and production strategy. The decisions often must be made when there are high uncertainties, leading to risks. This paper presents a system which integrates finite-difference reservoir simulation, an economics model, and a Monte Carlo algorithm with a global optimization search algorithm to identify more optimal reservoir planning and management decision alternatives under conditions of uncertainty, such that the associated risks are managed. The optimization problem is posed with the business goals stated as a general objective function and includes all constraints (economic, reservoir, production, and statistical) that need to be honored. The method is illustrated with an example of an E&P asset with multiple oil fields produced through a common surface network. The formulation of the example problem includes decision variables for the scheduling of reservoir units, the number of wells, and production rate capacities. It incorporates the nonlinear response of the objective to reservoir performance and surface pressure constraint through a flow simulator. The analysis is multi-period, evaluating the impact of predicted performance over time for each decision alternative. The individual reservoir units have uncertainties in hydrocarbon volumes and quality, reservoir deliverability, and costs. Decision solutions for objective functions of net present value (NPV) that mitigate risks are presented.