微地震相分析在河流储层精细描述中的应用

Application of nlicroseismic facies in fine description of fluvial reservoir

传统地震相分析满足不了目前油田勘探开发的需要。神经网络微地震相分析将神经网络应用于高质量三维地震数据体中,可对单一反射同相轴进行波形信号分析和训练,建立模型地震道,并对实际地震道分类,进而得到在平面和剖面上精度较高的微地震相分布。采用该方法并结合测井资料,在研究区块中建立的微地震相分布图能够清晰地表现出该区块的沉积微相特征,且较好地解释了工区内2口井的产能差异,表明神经网络微地震相分析是可靠和有效的。

Traditional seismic facies analysis can not satisfy the needs of current exploration and development in oil fileds. Used in high quality seismic data volume, neural network microseismic facies technology can analyze and train the seismic waves of one single reflection , establish model seismic tracks that were used to classify the seismic tracks, and obtain high precise microseismic facies vertically and horizontally. Combined with logging data, the established mieroseismic facies of the working area showed clearly the deposi-tional microfacies of target zone and explained the gas production difference between two wells, which had confirmed that the technology was reliable and efficient.