چكيده به لاتين
Abstract:
Considering that the main purpose of reservoirs management is optimal recovery and achieving more income with the least cost, for development of oil and gas reservoirs, and the drilling of new wells (including exploratory, developmental and injection wells and even wells used in enhanced recovery) is the first step in recovery of reservoirs, thus the number and location optimizing of the wells and drilling pattern of these wells can increase the production rate and the rate of recovery coefficient, and maximize the economic benefit of oil production, which depends on numerous complex parameters with a lot of uncertainties. Due to the important economic role of the oil industry and the high capitalization of the oil industry and its high capital risk, decisions should be optimized at each level of reservoir development. Simulation and optimization of the location of oil wells is one of the major challenges facing major oil companies, which can be viewed from two points that are the main thesis approach: from the point of geology and reservoir science and resources, and from the point of operating costs and current and future investment. Due to the complexity of oil reservoir simulation models such as geological issues, production operations and other constraints, there is a need to find an optimization method that can be with a reduction in computational cost, it also has a good accuracy and speed. The objective is optimal well placement over the lifetime of the reservoir, in order to maximize production and profit from recovery, taking into account physical and economic constraints. The presented mathematical model in the issue is single objective, which the NPV maximization in selecting the location of the wells has been done, taking into account with uncertainty in the research. In this regard, Parallel Genetic Paradigm has been used to speed up the optimizer in order to avoid increasing the computational load of the problem of locating and prolonging the run-time. In the proposed model, the location of oil wells in the fields with aquifer is optimized. In this study,firs the sensitivity analysis on variables and control parameters (number and location of wells, rates, ...) of various oil and gas reservoirs were performed, then with an automatic optimization method, the serial genetic optimization algorithm and then parallel genetics, optimization of the number of produced wells and then the location of the wells is done, As a result of optimization, the wells are diverted from the aquifer and the number of simulator runs is significantly reduced in parallel processing. In the following, important parameters affecting parallelization of the genetic algorithm are investigated and compared.
Keywords: Oil well placement, Parallel genetic algorithm, Optimization, Simulation, Development of oil fields.
