摘要
随着大庆长垣地区勘探程度的加深,致密砂储层已经成为勘探重点。由于该地区地质问题比较突出,河道砂体横向不连续,单层砂体薄(3~6 m),薄互层比较发育,常规地震属性分析技术难以对砂体进行有效预测。针对敖南地区扶余油层的地质特点,利用快速匹配追踪算法计算速度快、时频分辨率高的特点,探索应用频谱分解技术进行致密砂体预测。研究表明:地震波高频属性对该地区薄单砂有更好的反映,而在低频端薄互层的组合效应变弱,使其与厚砂体得到有效区分。另外,通过与井资料结合进行双重约束,实现了砂体的动态刻画,对原有的有利区进行重新标定,使研究区内的砂体展布越来越清晰。应用证明频谱分解技术完全可以对敖南扶余油层的致密砂体进行有效预测。
As the deepening of the exploration degree in Daqing Placanticline,the tight sandstone reservoir has become the focus of the exploration. But the geological problems in the area are more prominent: the horizontal river sandbodies are not continuous,the single sandbody is thinner( 3-6 m),and the thin interbeds are relatively well developed,so it is difficult for the conventional seismic attribute analysis technology to predict the sandbodies effectively. According to the geological characteristics of Fuyu reservoirs in Aonan area,by means of the advantages of the fast calculation by matching pursuit theory and high time-frequency resolution,the dense sandbody prediction was explored with the help of the spectral decomposing technique. The study achievements show that the high-frequency attribute of the seismic wave has better reflection on the thin single sandbody in the area,and the combined effect of the thin interbeds in the low frequency position becomes weak,so the thick sandbodies can be effectively divided. In addition,combined with the well data,the double constraints were conducted to realize the dynamic characterization of the sandbodies,and furthermore the recalibration of the original favorable areas were determined,thus the spread and distribution of the sandbodies in the study area have been more and more clear. Theapplication proves that the spectral decomposing technique can completely and effectively predict the tight sandbodies in Fuyu oil reservoirs in Aonan region.
出处
《大庆石油地质与开发》
CAS
CSCD
北大核心
2016年第6期132-137,共6页
Petroleum Geology & Oilfield Development in Daqing
基金
国家自然科学基金(41174080
41340039)
关键词
扶余油层
致密砂体
快速匹配追踪
频谱分解
砂体预测
Fuyu oil layer
dense/tight sand body
fast matching pursuit(MP)
spectral decomposition
sandbody prediction
