SVM算法在渤海湾盆地南堡凹陷火山岩储层流体预测中的应用

Application of SVM algorithm in fluid prediction of volcanic reservoirs in Nanpu Sag,Bohai Bay Basin

火山岩储层受岩相、岩性、储集空间类型等多因素影响,流体识别难度大,是测井解释的难题之一,亟需建立一种方便快捷识别方法。为此,针对渤海湾盆地南堡凹陷火山岩储层特征,采用机器学习的SVM(支持向量机)算法对未知储层进行流体预测。研究表明:①综合应用岩心、测井、录井等资料对流体敏感特征参数寻优,单信息敏感参数为声波时差、补偿密度、深侧向电阻率,多信息融合参数为自然伽马相对值、全烃比值、烃气密度指数、烃气湿度指数,以上7种参数参与模型建立;②使用SVM算法进行火山岩流体预测,将储层流体分为油层、油水同层和水层3类,选取测井、录井敏感参数,训练可靠样本库,预测库正判率达90%。SVM算法预测应用表明,SVM算法计算复杂程度低,泛化推广能力强,可快速识别火山岩流体性质,为油气成藏规律分析和地质储量动用开发提供可靠依据。

Volcanic rock reservoirs are affected by many factors such as lithofacies,lithology,and reservoir space types,and fluid identification is difficult,which is one of the difficulties in well logging interpretation.It is urgent to establish a convenient and quick identification method.For this reason,the SVM(Support Vector Machine)algorithm of machine learning is used to predict the fluids of unknown reservoirs for the volcanic rock reservoirs in the Nanpu Sag of the Bohai Bay Basin.The research shows that:①Comprehensive application of core,well logging,mud logging and other data to optimize fluid sensitive characteristic parameters,single information sensitive parameters are acoustic time difference,compensation density,resistivity,multiinformation fusion parameters are natural gamma relative value,total hydrocarbon Ratio,hydrocarbon gas density index,hydrocarbon gas humidity index,the above seven parameters participate in the model establishment;②Using the SVM algorithm for volcanic fluid prediction,the reservoir fluid is divided into three types:oil layer,oil-water layer and water layer.Sensitive parameters of well logging and mud logging are selected,and a reliable sample library is trained.The correct judgment rate of the prediction library reaches 90%.The prediction application of SVM algorithm shows that it has low calculation complexity and strong generalization ability,which can quickly identify the fluid properties of volcanic rocks and provide a reliable basis for the analysis of oil and gas accumulation rules and the production and development of geological reserves.