Reservoir Management Optimization Decision Methods

Reservoir management runs through the whole life of petroleum recovery. It aims to enhance oil recovery and to acquire optimum exploitation benefits, In operation, reservoir management faces complicated multi-objective optimum decision-making. It is essential to make optimum decision to realize reservoir management for the complexity, uncertainty and high investment risk in petroleum industry. Therefore, optimization and decision-making is crucial to successful reservoir management. However, in order to control as a whole, it is not wide or systematic on the aspects of how to introduce algorisms existed in other fields into petroleum discipline, of combining actual problems and theoretic methods, of seeking out proper ways to treat with scenarios in reservoir management. Via large and wide literature investigation, this paper, based on the studies of contents, performance process of optimization and decision-making, referred to multi-disciplinary up-to-date achievements such as mathematics, management sciences, and computer science, tries to search out the general process for reservoir management optimization and decision-making, sets up operation models and probes proper model solution methods with strong maneuverability, and adds a key to intelligent reservoir management integration.Through systematic study, this paper achieves following results and recognitions:(1) Influence factors in reservoir management optimization and decision-making are analyzed from the view of management. The general process for optimization and decision-making is put forwarded. And the chief work during each period of the whole reservoir management life is made clear.(2) After classification, influence factors are categorized into two systems: one is development evaluation indices system, the other economic evaluation indices system. Thus, a relatively complete evaluation structure is shaped.(3) Based on the studies of all kinds of methods in optimization and decision-making, combined with the characters in reservoir management, threemethods which match the actual reservoir operation well, Analytic Hierarchy Process, Polytope Algorithm, Genetic Algorithm, are recommended. General pattern for reservoir management optimization and decision-making on the basis of Analytic Hierarchy Process is developed.(4) Almost all the complex decision-making problems contain qualitative and quantitative factors simultaneously. Analytic Hierarchy Process can deal with such problems well. Besides, with little more work, factor sensitivity analysis is carried out. The application case, optimum reservoir planning selection of Baimiao gas field, verifies that Analytic Hierarchy Process is easily available indeed in operation by integrate qualitative and quantitative aspects.(5) Multi-objective model is established for determinative measure programming. Polytope Algorithm is adopted to solve such model. In the case of Nanmazhuang Ma 2 Block, two conditions, oil production increase and water production control are considered. And an optimum plan is determined after comprehensive comparison. At the same time, this case also shows proof that Polytope Algorithm is an effective direct search method to treat multi-objective optimization with constraining conditions.(6) The ambiguity and uncertainty of reservoir actual structure and fluid flow mechanics make it difficult for conventional modeling and algorithms to describe and solve. Thus, according to mechanics of dealing with stochastic phenomena in programming theory, multi-objective stochastic programming model is developed to dispose parameter uncertainty. As a heuristic Monte Carlo approach with powerful global searching, Genetic Algorithm based on stochastic programming is utilized. This paper studies fundamental theory, key technologies. Program procedure of Genetic Algorithm based on stochastic simulation is advanced.