叠前联合反演技术在渤海中深层储层预测中的应用

APPLICATION OF PRE-STACK JOINT INVERSION TO MID-DEEP RESERVOIR PREDICTION IN BOHAI BAY

渤海A油田中深层砂泥纵波阻抗叠置严重,常规叠后反演手段无法有效预测储层,为此提出叠前联合反演技术思路:通过实钻井数据开展储层敏感性分析,采用坐标旋转技术构建储层识别因子并作为目标曲线,以叠前同时反演获得的纵横波阻抗、密度等弹性参数体作为输入,采用多属性神经网络反演获得全区储层识别因子数据体,从而对砂岩储层厚度及空间展布进行准确预测。该技术获得的目标储层预测结果在纵向与已钻井吻合良好,横向展布符合地质沉积规律认识,为后续钻井提供了重要的参考依据,具有广阔的应用前景。

The sandstone and shale＇s p-impedances are seriously overlapped in the A oilfield of the Bo- hal Bay and thus conventional ways using post-stack seismic attribute and inversion cannot effectively predict sand reservoirs. Here we propose a pre-stack ioint inversion technology for reservoir prediction to solve this problem. Firstly, reservoir sensitivity analysis is carried out based on logging data. Then, we obtain a sand reservoir identification factor using coordinate rotation technique and make i-t a target curve. Finally, we obtain a reservoir identification factor volume of the whole area to describe sand reservoir thickness and lateral distribution through multiple attribute neural network inversion with p-impedance, s-impedance, density, and ratio of p-wave and s-wave data acquired by fine pre- stack simultaneous inversion. Actual application shows that this technique can acquire a good reservoir prediction result, which corresponds well with drilling wells vertically and conforms to geological rule horizontally. The result can play a very important role in subsequent drilling and has a broad applica- tion prospect.