Distinguished Author Series articles are general, descriptive representations that summarize the state of the art in an area of technology by describing recent developments for readers who are not specialists in the topics discussed. Written by individuals recognized as experts in the area, these articles provide key references to more definitive work and present specific details only to illustrate the technology. Purpose:to inform the general readership of recent advances in various areas of petroleum engineering.
This paper presents the application of optimization techniques in reservoir management to determine the best development plan that maximizes the economic performance of an asset. A distinguishing characteristic of this approach is that it can evaluate all feasible scenarios for a specific financial objective within a set of well-defined constraints. The output of this integrated workflow is a complete set of decisions that drive capital investment, development scheduling, production, hydrocarbon recovery, and, ultimately, economic performance of the asset.
The conventional approach to reservoir management often considers a limited number of development options because of the complexity of the events within an investment plan and the time required for the evaluation. Input into the decision-making process traditionally comes in the form of sensitivity analyses from reservoir simulation, cost engineering, wellbore planning, pipeline networking, and project economic-analysis tools. These technologies are used to simulate performance by examining a specific development scenario, calculating future production, and performing a discounted cash-flow analysis to assess the return on the required investment.
The exact scheduling of new infrastructure and production facilities as well as the drilling and stimulation of additional wells is critical to maximizing economic performance, especially if remaining reserves are material in size. These discrete events sometimes receive little attention. While the industry's ability to predict asset performance and assimilate several diverse perspectives together has significantly advanced, many reservoir-management decisions still are based on heuristics, rules of thumb, analogs to other assets, and ease of execution.
Use of optimization techniques is not new in the energy business. However, in reservoir management, the technology must cope with more nonlinear phenomena within the physical system, complex and realistic objective functions and constraints, and discrete decisions that occur at distinct points over the asset life. The use of mixed-integer nonlinear programming algorithms can be useful in these situations. These algorithms implicitly construct a tree of all possible development plans and then efficiently prune the branches to eliminate candidates that can be shown to be nonoptimal.
The effectiveness of optimization technology is illustrated by applying it to the ongoing expansion of a regional complex of gas reservoirs. The approach is used to determine the development schedule of the different reservoirs and the timing of their wells, the timing and staging of compression, and the development of satellites to meet a contract specification.