公开(公告)号：US5444619A

公开(公告)日：1995-08-22

申请号：US128069

申请日：1993-09-27

申请人： Josiah C. Hoskins ,  Joshua M. Ronen

发明人： Josiah C. Hoskins ,  Joshua M. Ronen

IPC分类号： E21B49/00 ,  G01V1/30 ,  G01V1/00 ,  G06F17/15

CPC分类号： G01V1/306 ,  E21B49/00 ,  G01V2210/632

摘要： A system and method for predicting oil reservoir properties throughout the reservoir using well data and seismic data. While the reservoir properties in the vicinity of a well borehole are usually known (i.e. by well logging), the reservoir properties between wells are unknown and difficult to estimate. Because the relationships between reservoir properties and seismic data is seldom obvious, the method uses Artificial Neural Networks (ANN's) to estimate these relationships. First, the method calculates the intersections between the seismic data and wellbore date, i.e. seismic reflectors are correlated to geological markers in the wellbores. Second, the method estimates the significance between seismic attributes and borehole properties. Next, the method models or calibrates the relationship between reservoir properties and seismic attributes by training an ANN using seismic attributes and wellbore data close to the intersections. Finally, the trained ANN uses the seismic attributes to predict the reservoir properties between wells. Advantageously, statistic methods are used to estimate the confidence of the predictions.

摘要翻译： 使用井数据和地震资料预测整个油藏油藏性质的系统和方法。 虽然井眼附近的储层性质通常是已知的（即通过测井），井之间的储层性质是未知的，并且难以估计。 由于储层性质与地震资料之间的关系很少见，该方法使用人工神经网络（ANN）来估计这些关系。 首先，该方法计算地震数据与井筒日期之间的交点，即地震反射器与井筒中的地质标记相关。 第二，该方法估计了地震属性与钻孔性质之间的意义。 接下来，该方法通过使用邻近交叉点的地震属性和井眼数据训练ANN来建模或校准油藏性质与地震属性之间的关系。 最后，训练有素的ANN使用地震属性来预测油井之间的油藏性质。 有利的是，统计学方法用于估计预测的置信度。