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盆地演化、油气系统演化以及油气的运移聚集充满了混沌与非线性特征 ,单纯使用传统的地下流体动力学方程 ,无法实现油气运聚的模拟和评价。作者探讨了将传统动力学模拟与人工神经网络模拟结合起来的的途径与方法 ,即在三维构造 地层体的动态模拟基础上 ,采用单元体模型使非均质的复杂通道体系转化为有限个简单均质体后 ,再利用传统动力学模拟来对相态和驱动力求解 ,然后运用人工神经网络技术来解决单元体之间的油气运移方向、运移速率和运移量等问题。利用所编制的软件对珠三凹陷的油气二次运移和聚集进行了动态模拟 ,有效地揭示油气运聚的复杂机理和过程。
Evolution of basin, evolution of oil and gas system and migration and accumulation of oil and gas are full of chaos and non-linear features. The simulation and evaluation of hydrocarbon migration and accumulation can not be realized simply by using the traditional subsurface hydrodynamics equations. The author explores ways and means of combining traditional dynamics simulation with artificial neural network simulation. Based on the dynamic simulation of three-dimensional structural stratigraphy, the author uses unit cell model to transform heterogeneous complex channel system into finite simple After the homogeneous body, the traditional dynamics simulation is used to solve the phase and the driving force, and then the artificial neural network technology is used to solve the problems such as the hydrocarbon migration direction, the migration rate and the migration amount between the units. The software was used to simulate the secondary migration and accumulation of oil and gas in the Pearl River Delta and reveal the complicated mechanism and process of hydrocarbon migration and accumulation effectively.