【摘要】：水驅(qū)是石油二次開采的一種重要方式,在驅(qū)替過程中,由于油藏地質(zhì)的非均質(zhì)性,使注入水優(yōu)先進(jìn)入高滲透層,高滲路徑一旦見水,這些路徑以外區(qū)域內(nèi)的石油就被高滲路徑短路而無法被驅(qū)替采出。在水驅(qū)中如何進(jìn)行高效合理的開發(fā)油田,提高油田控水穩(wěn)油效果,減緩油田產(chǎn)量遞減,成為了急需解決的問題。而現(xiàn)有的水驅(qū)油藏優(yōu)化控制算法均存在優(yōu)化效果不明顯等問題。本文正是在這種背景下,制定最佳的注入策略,進(jìn)行水驅(qū)油藏優(yōu)化控制算法的研究。在現(xiàn)實(shí)的油藏開發(fā)中是具有一定的指導(dǎo)和應(yīng)用意義的。 在研究油藏動態(tài)系統(tǒng)時(shí),本文以經(jīng)濟(jì)凈現(xiàn)值為目標(biāo)函數(shù),選擇飽和度為狀態(tài)變量,將產(chǎn)油量和注水量作為控制變量,并選擇連續(xù)性方程、邊界限定等作為約束條件,從而建立水驅(qū)油藏優(yōu)化控制的數(shù)學(xué)模型。 根據(jù)油藏的特性,選擇兩類優(yōu)化算法來研究水驅(qū)油藏優(yōu)化問題。一類是有梯度算法即最優(yōu)控制算法,關(guān)于最優(yōu)控制算法的選擇,本文選擇最速下降法,在最速下降法中,梯度的求解是一大難點(diǎn)。本文在伴隨法求解梯度的基礎(chǔ)上,針對伴隨法計(jì)算速度慢且復(fù)雜的缺點(diǎn)對伴隨法做了改進(jìn),以提高計(jì)算的效率和減少計(jì)算的復(fù)雜度,由此形成了改進(jìn)最速下降法。另一類是無梯度類算法即SPSA (Simultaneous Perturbation Stochastic Approximation)算法。該算法主要通過估計(jì)目標(biāo)函數(shù)的近似梯度來逐漸逼近最優(yōu)解,這樣就避免了對于復(fù)變函數(shù)的梯度進(jìn)行復(fù)雜的求解。根據(jù)兩種算法的研究過程,分別設(shè)計(jì)水驅(qū)油藏優(yōu)化仿真程序,用Eclipse建立油藏模型,結(jié)合MATLAB進(jìn)行編程仿真。本文采用的優(yōu)化方法在實(shí)際的油藏優(yōu)化中還是能取得較好的效果,且成本低、耗費(fèi)人力少。
[Abstract]:Water drive is an important way of secondary exploitation of petroleum. Due to the heterogeneity of reservoir geology, the injected water enters into the high permeability zone first, and the high permeability path once the water appears, Oil in areas outside these paths is short-circuited by high permeability paths and cannot be driven out. How to develop oil fields efficiently and reasonably in water drive, improve the effect of controlling water and stabilizing oil production, and slow down the decline of oil production has become an urgent problem to be solved. However, the existing optimal control algorithms for water drive reservoirs have some problems, such as poor optimization effect and so on. It is under this background that the optimal injection strategy is established and the optimal control algorithm for water drive reservoir is studied in this paper. It has certain guiding and application significance in the realistic reservoir development. When studying the reservoir dynamic system, this paper takes the economic net present value as the objective function, selects the saturation as the state variable, takes the oil production and the water injection rate as the control variable, and selects the continuity equation, the boundary limitation and so on as the constraint conditions. Thus the mathematical model of optimal control of water drive reservoir is established. According to the reservoir characteristics, two kinds of optimization algorithms are selected to study the water drive reservoir optimization problem. One is the optimal control algorithm with gradient algorithm. For the selection of optimal control algorithm, this paper chooses the steepest descent method, in which the solution of gradient is a big difficulty. In this paper, the adjoint method is improved to improve the computational efficiency and reduce the computational complexity, aiming at the slow and complex computing speed of the adjoint method, and the improved steepest descent method is formed. The other is the non-gradient class algorithm, the SPSA (Simultaneous Perturbation Stochastic Approximation) algorithm. The algorithm approximates the optimal solution gradually by estimating the approximate gradient of the objective function, thus avoiding the complex solution of the gradient of the complex function. According to the research process of the two algorithms, the water drive reservoir optimization simulation program is designed, the reservoir model is established by Eclipse, and the simulation is carried out with MATLAB. The optimization method adopted in this paper can still achieve good results in the actual reservoir optimization, and the cost is low and the manpower is less.
【學(xué)位授予單位】：西南石油大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TE357.6

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