支持向量机方法识别储集层流体性质

Reservoir Fluid Property Identification with Support Vector Machine Method

在储集层流体识别中首次引入了支持向量机(SVM)方法,对测井得到的各种测量参数和综合解释参数与油、气、水等流体之间的复杂关系进行研究,借助于支持向量机方法,建立了测井参数识别油、气、水等储集层流体的识别模型。实际应用效果表明,支持向量机方法识别储集层流体类型是一种比较切实可行的方法,提高了测井解释油气水的精度,为储集层流体识别提供了一种简单可靠、识别精度高的新方法。

The Support Vector Machine （SVM） Method is first introduced into reservoir fluid property identification, by which the models for identifying oil, gas and water are developed through study of the complex relations between measured logging data and comprehensively interpreted parameters about reservoir fluids. The applied results indicate that SVM method is a feasible, effective and higher accurate way for well logging interpretation of reservoir fluids as a new, simple and reliable method with high accuracy.