Abstract: The previous methods based on neural network are difficult to predict the water saturation of next year based on the data of the given years.A new method combining the neural networks with the principle of implicit curve can effectively handle the above problem.First,the vector data of every year are mapped into a closed curve,and a virtual explicit function is constructed on the constraint points.Then,the explicit function is approximated by a backpropagation neural network.Finally,the isoline of the neural network is extracted from the simulation surface.The predicted data can be obtained by the inverse mapping of the isoline.Some experiment results verified the effectiveness of this method.

Key words: backpropagation neural network, implicit curve, well log data, prediction, time vector serial, well log curve, numerical simulation

摘要： 我国东部油田已普遍进入高含水开发阶段,因此,以剩余油形成的主要地质控制因素为线索,深化油藏开发地质研究已成为研究的重点.以胜利油区高含水油田为例,在低级序构造、储层精细刻画和剩余油定量描述等开发地质研究方面取得了明显进展.陆相水驱油藏剩余油富集区主要受低级序断层、夹层和物性差异等油藏非均质性的控制,因而重点形成了低级序断层精细描述与预测、河流相储层构型、夹层描述与预测、储层优势通道描述与预测等先进技术,并且建立了分割性约束的精细数值模拟模型,增加了空间流体拟合条件,使得剩余油富集区的定量描述更加符合油藏实际动态.

关键词: 油藏开发地质, 剩余油富集, 控制因素, 低级序断层, 河流相储层, 油藏描述