【摘要】 碳酸盐岩岩溶储层非均质性和各向异性强,采用井震联合方法对储层次生孔隙度进行了预测。首先利用成像测井数据评价碳酸盐岩储层次生孔隙参数,然后运用模糊神经网络技术建立次生孔隙参数与井旁道地震属性之间的关系模型,进而预测全工区储层次生孔隙度分布。采用井震联合方法预测的次生孔隙发育带与钻遇优质储层的井点吻合,预测结果在研究区块有一定的可用性。更多还原

【Abstract】 Evaluation of secondary pore developing zone is difficult be- cause of its strong heterogeneity and anisotropy in carbonate karst reservoirs.So a single data cannot make an accurate and complete evaluation.Aiming at the problem,firstly,the imaging logging da- ta was used to evaluate the secondary pore parameters of carbonate reservoirs.Then,the obscure neural network technology was uti- lized to establish the relationship model between the secondary pore parameters and the seismic attributes of well-side traces.Finally, the porosity distribution of secondary pores all over the working ar- ea was predicted.The prediction shows that the secondary pore de- veloping zone by seismic-logging method is in good accordance with the high quality reservoirs drilled.Therefore,the predicted results are feasible in the area.更多还原