Efficient Optimization Strategies for Developing Intelligent Well Business Cases

Abstract

Abstract In this paper, we evaluate optimization techniques to develop, or support, business cases for Intelligent or Smart Wells. A commercial reservoir simulation platform and two reservoir models based on published work are used. Recommendations are made on which methods are most appropriate for large or small numbers of flow control valves (FCVs), available computing power and other parameters. Optimization techniques are categorized as either Closed Loop or Model Based. Closed Loop or Reactive methods respond to specific, measured properties such as water-cut or gas-oil ratio, by opening or closing downhole flow control valves. Model-Based methods use reservoir models to determine the optimal set of flow control valve positions versus time. They can, therefore, behave in a defensive or proactive manner to delay the production of unwanted fluids, as well as a reactive manner, to choke back sections of the well producing unwanted fluids. In this paper, Closed-Loop and Model-Based methods are compared in terms of computational cost. A simple procedure for defining the constraints used in the optimization process is proposed. The procedure is shown to increase the efficiency of the optimization process significantly.