石油钻采工艺
石油鑽採工藝
석유찬채공예
OIL DRILLING & PRODUCTION TECHNOLOGY
2015年
2期
8-11
,共4页
赵广渊%苏玉亮%任龙%郝永卯%李政%王文东
趙廣淵%囌玉亮%任龍%郝永卯%李政%王文東
조엄연%소옥량%임룡%학영묘%리정%왕문동
多分支水平井%智能优化%遗传算法%正交设计%适应值%交叉概率%变异概率
多分支水平井%智能優化%遺傳算法%正交設計%適應值%交扠概率%變異概率
다분지수평정%지능우화%유전산법%정교설계%괄응치%교차개솔%변이개솔
multi-branch horizontal well%intelligent optimization%genetic algorithm%orthogonal design%fitness value%crossover probability%mutation probability
多分支水平井参数优化设计是一个多目标最优化问题,采用传统的优化方法求解复杂程度依赖于优化对象数目,且容易产生局部收敛。基于多分支水平井的油藏数值模拟技术,以生产净现值为目标函数,应用遗传算法建立了多分支水平井参数智能优化设计方法,并编程实现了优化设计的全程自动化。优化过程中,利用正交设计原理生成种群初值,避免了初始种群的随机盲目性;根据个体适应值大小选择交叉和变异概率,保证了种群的多样性和算法的全局收敛能力。以珠江口盆地某海上低渗透油藏为例进行了多分支水平井参数优化设计,结果表明:遗传算法优化具有全局智能搜索寻优的特点,优化结果比传统优化算法有较大提高,具有较强的优越性和实用性。
多分支水平井參數優化設計是一箇多目標最優化問題,採用傳統的優化方法求解複雜程度依賴于優化對象數目,且容易產生跼部收斂。基于多分支水平井的油藏數值模擬技術,以生產淨現值為目標函數,應用遺傳算法建立瞭多分支水平井參數智能優化設計方法,併編程實現瞭優化設計的全程自動化。優化過程中,利用正交設計原理生成種群初值,避免瞭初始種群的隨機盲目性;根據箇體適應值大小選擇交扠和變異概率,保證瞭種群的多樣性和算法的全跼收斂能力。以珠江口盆地某海上低滲透油藏為例進行瞭多分支水平井參數優化設計,結果錶明:遺傳算法優化具有全跼智能搜索尋優的特點,優化結果比傳統優化算法有較大提高,具有較彊的優越性和實用性。
다분지수평정삼수우화설계시일개다목표최우화문제,채용전통적우화방법구해복잡정도의뢰우우화대상수목,차용역산생국부수렴。기우다분지수평정적유장수치모의기술,이생산정현치위목표함수,응용유전산법건립료다분지수평정삼수지능우화설계방법,병편정실현료우화설계적전정자동화。우화과정중,이용정교설계원리생성충군초치,피면료초시충군적수궤맹목성;근거개체괄응치대소선택교차화변이개솔,보증료충군적다양성화산법적전국수렴능력。이주강구분지모해상저삼투유장위례진행료다분지수평정삼수우화설계,결과표명:유전산법우화구유전국지능수색심우적특점,우화결과비전통우화산법유교대제고,구유교강적우월성화실용성。
Parameter optimization design for multi-branch horizontal well is an issue of multi-objective optimization.The complexity of optimization method solution using traditional method depends on the number of optimized objects, and local convergence may occur easily. Based on reservoir numerical simulation technique for multi-branch horizontal well and taking the net present value of production as the objective function, the intelligent optimization design method for parameters of multi-branch horizontal well was established using genetic algorithm and the whole-course automaton of optimization design was achieved by programming. During optimizing, the orthogonal design principle was used to generate the initial value of the population, which avoided the random blindness of initial population. The probability of crossover and mutation was selected according to individual fitness value, which ensured the diversity of the population and global convergence ability of the algorithm. An offshore low-permeability oil reservoir at Zhujiang River Mouth Basin was used as an example to carry out optimization design for parameters of multi-branch horizontal well, and the result showed that the genetic algorithm optimization had a feature of global intelligent search optimization, and the optimization results were improved greatly compared with traditional optimization algorithm. So this method has significant superiority and practicability.