一种基于叠前反演的孔隙度预测方法  

A porosity prediction method based on pre-stack inversion

作　　者：周单[1,2] 朱童[1,2] 胡华锋[1,2] 唐金良[1] 

机构地区：[1]中国石油化工股份有限公司石油物探技术研究院,南京211103 [2]中国地质大学(武汉)地球内部多尺度成像湖北省重点实验室,武汉430074

出　　处：《物探化探计算技术》2015年第4期472-477,共6页Computing Techniques For Geophysical and Geochemical Exploration

基　　金：基础研究重大项目前期研究专项(2011ZX05049);国家重点基础研究发展计划(2011CB201002);中国地质大学(武汉)地球内部多尺度成像湖北省重点实验室开放基金项目(SMIL-2014-04)

摘　　要：非线性反演方法在储层预测中得到了广泛地应用,但其通常只采用叠后波阻抗反演结果和叠后属性进行预测,进而忽略了叠前道集中包含的岩性信息。这里提出了一种基于叠前反演的储层预测方法,可以有效地利用叠前信息进行储层预测。首先对叠前道集进行针对性处理,使其满足叠前反演的要求,其次改进横波估算方法获得高精度的横波数据,并针对叠前数据进行子波提取,然后通过叠前反演获得纵波、横波阻抗和密度信息,最后结合叠前属性,采用概率神经网络方法(PNN)来反演储层孔隙度参数,该方法克服了叠后波阻抗反演进行储层预测造成的多解性问题,并提高了储层识别的精度,预测结果与测井一致,证明该方法正确有效。The nonlinear inversion method is widely used in reservoir prediction, but it usually only use post--stack imped- ance inversion results and post--stack seismic attributes, which ignore lithological characters contained in pre--stack gathers. A porosity prediction method is proposed based on pre--stack inversion which use pre--stack information effectively to charac- terize reservoir in this paper. First, the object--oriented processing measures are made for pre--stack gathers to meet the re- quirements of pre--stack inversion. Second, high accuracy of shear wave data can be obtained with the improved method of es- timating shear wave. The wavelet can be then extracted from pre--stack gathers. Finally, inverting reservoir porosity by prob- abilistic neural network method using pre--stack properties combined with p--wave impedance, s--wave impedance and density information which obtained by pre--stack seismic inversion. Contrasted with post--stack impedance inversion, this method o- vercomes the multiple solution problem and improve the precision of reservoir recognition. The prediction results are consistent with log, which proved that the method is correct and effective.

关 键 词：叠前反演 概率神经网络 孔隙度反演 储层预测 

分 类 号：P631.4[天文地球—地质矿产勘探]