【摘要】 为了准确预测储层物性参数,提高地震资料定量解释精度,本文借鉴模拟退火法AVA同步反演方法,提出了一种基于叠前AVA同步反演的储层物性参数预测方法,该方法在综合考虑岩石密度、纵横波速度等弹性参数与孔隙度等物性参数的空间关系基础上,采用Kohenon自组织神经网络储层参数分类,多层感知器(MLP)预测等方法实现了储层物性参数的定量预测,并对预测结果给出了定量评价。将本文方法应用于A探区的储层物性参数定量预测,预测结果验证了方法的有效性。更多还原

【Abstract】 In order to accurately predict reservoir physical properties and raise quantitative interpretation precision for the seismic data,in this paper a reservoir physical property prediction technique was proposed based on simulated annealing pre-stack AVA simultaneous inversion method,by integratedly considering the space relation between elastic parameters (such as rock density,P-wave and S-wave velocity) and physical properties (porosity and so no),Kohenon self-organized neural network reservoir parameter classification,Multilayer perceptron and other prediction methods were utilized to realize the quantitative prediction for the reservoir physical properties,and quantitative evaluation was made for prediction results.The technique proposed in this paper was applied in the reservoir parameter quantitative prediction for A Exploration area,and the prediction results verified the effectiveness of the technique.更多还原