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基于改進(jìn)量子遺傳算法的油田井位及數量?jì)?yōu)化
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長(cháng)江大學(xué) 石油工程學(xué)院 湖北 武漢,,

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TP301.6

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Oilfield well location and quantity optimization based on improvedquantum genetic algorithm
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    摘要:

    布井的數量及位置的選取是油田開(kāi)發(fā)中至關(guān)重要的一環(huán)。一項最優(yōu)的布井方案受到地質(zhì)情況、油藏驅動(dòng)方式、流體特性、油田設備規格以及多種經(jīng)濟參數指標的影響,是一個(gè)具有多決策變量的優(yōu)化問(wèn)題,傳統的數學(xué)優(yōu)化方法在處理這類(lèi)問(wèn)題時(shí),很難找到一個(gè)合適的目標函數來(lái)滿(mǎn)足優(yōu)化條件。量子算法作為量子計算與智能算法相結合的產(chǎn)物,其優(yōu)秀的尋優(yōu)能力以及良好泛化能力,在處理目標函數性態(tài)復雜的優(yōu)化問(wèn)題時(shí)較傳統方法有著(zhù)更好的表現。因此,本文利用MATLAB建立油藏數值模擬模型,將井的數量和井位作為變量,以油田凈現值為目標函數結合改進(jìn)的量子遺傳算法(Quantum Genetic Algorithm,QGA)對井位進(jìn)行優(yōu)化。通過(guò)與傳統布井方式的對比,所提出的方法有更好的經(jīng)濟效益,同時(shí)擺脫了傳統布井方式對于經(jīng)驗的依賴(lài),具有很好的移植性。

    Abstract:

    The selection of the number and location of well is a vital part of oilfield development. An optimal well placement scheme is affected by geological conditions, reservoir driving methods, fluid characteristics, oilfield equipment specifications, and various economic parameters. It is an optimization problem with multiple decision variables. Traditional mathematical optimization methods are dealing with this type. When it comes to problems, it is difficult to find a suitable objective function to satisfy the optimization conditions. As a product of quantum computing and intelligent algorithms, quantum algorithm has excellent performance and good generalization ability, and it has better performance than traditional methods in dealing with complex optimization problems of objective function. Therefore, this paper uses MATLAB to establish a reservoir numerical simulation model, taking the number of wells and well position as variables, and optimizing the well position with the improved net QGA with the net present value of the oilfield as the objective function. Compared with the traditional well-drilling method, the proposed method has better economic benefits, and at the same time, it has got rid of the dependence of traditional well-placed methods on experience and has good portability.

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郭武豪,江厚順,謝昊.基于改進(jìn)量子遺傳算法的油田井位及數量?jì)?yōu)化計算機測量與控制[J].,2019,27(2):156-159.

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歷史
  • 收稿日期:2018-07-26
  • 最后修改日期:2018-08-15
  • 錄用日期:2018-08-15
  • 在線(xiàn)發(fā)布日期: 2019-02-14
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