【摘要】 地震、测井资料联合反演技术，是利用地震、测井数据的互补特性，从井间地震数据中反演地层的物性参数。共分三步进行：①查清井间地层构造形态，应用Born近似反散射线性反演技术，从叠前或叠后地震记录中得到反映层速度界面的反射系数剖面，效果相当于叠前或叠后的偏移剖面，并用作非线性反演的井间几何形态约束信息；②求取井间地震波参数，应用最优拟合牛顿法非线性反演技术，分别得到地层反射系数、波阻抗和介质速度参数；③求取地层物性参数，先应用神经网络技术从测井资料中求取井中物性参数，并以此作为非线性反演的井参数约束信息，在非线性反演地震波参数基础上，应用神经网络定量分析，从井间地震资料中分别得到地层的孔隙率、渗透率和含水饱和度参数的空间分布信息。该技术为实用的系列软件包，有I860微机版本和高档工作站版本。现已处理实际地震剖面近1000km。本技术特色为2．5维线性波动方程反演、二维非线性波动方程反演和神经网络分析的联合应用。地质效果特点是分层分辨率可以与井参数逐层对比，现已在多个油田使用。更多还原

【Abstract】 Technique for reservoir parameter inversion using seismic and log data derivesreservoir physical parameters from reciprocal log and cross-boreh0le seismic data.The technique involves the following major steps:. Ascertaining the structural shape of cr0ssmborehole formations- One can de-rive reflection coefficient section embodying interval velocity interfaces fromprestack or poststack seismic data by using B0rn approximate backscattering linear.inversion; and such section is equivalent to prestack or poststack migrated sectionin effect and is taken as a restraint of cross-borehole structure shape in nonlinearinversion.. Obtainment of cross borehole seismic wave parameters. Parameters such asreflection coefficient,wave impedance and velocity can be estimated respectively bymaking nonlinear inversion with optimal-fitting Newton method.. Formation physical parameter estimation. With the use of neural networktechnique,borehole physlcal parameters are derived from log data,and then they areused as the restraints for borehole parameters of nonlinear inversion. After the non-Iinear inversion of seismic wave parameters,with the aid of neural network quanti-tative analysis,one can derive the spatial distributions of formation parameters in-cluding Porosity,permeability and water saturation degree.Practical software package series of the technique includes versions for I86Ocomputer and advanced workstation. The technique has been used to satisfactorilyprocess seismic data of 1OOOkm. The technique is characterized by 2. 5-D linear waveequation inversion,and joint use of 2-D nonlinear wave equation inversion and neu-ral network analysis- Geologic horizon resolution is nicely equivalent to that of logdata. The technique has been used in some oil fields very successfully.更多还原