基于离心窗倾角扫描的曲率属性提取

Curvature attribute based on dip scan with eccentric window

体曲率属性作为三维地震资料构造解释的重要工具,在识别地层弯曲、地层不连续性,以及裂缝预测方面呈现了不可或缺的作用,因此如何高质量的提取该属性成为一个需要关注的问题.体曲率属性提取质量的关键在于倾角扫描的精度,本文提出了一种基于离心窗的倾角扫描方法,该离心窗是在空间为中心偏离分析点的四个旋转窗口,时间上为包含分析点的五个纵向滑动窗口,通过变换不同的窗口进行高精度倾角估计,并采用最小二乘拟合插值求取真实倾角.该方法避免了多窗扫描对小断层构造的忽略以及噪声的过大影响,同时在处理中对倾角数据进行中值滤波,去掉噪点影响.将由离心窗倾角扫描方法所计算的倾角数据体应用到曲率属性的计算中,在恢复构造细节和提高信噪比方面均展现了较好的效果.

Volume curvature attribute has formed an integral part of seismic interpretation projects because of its efficient utility in detecting seismic discontinuity,seismic curve,especially in predicting fracture reservoir.So it′s necessary to enhance the accuracy of curvature attribute calculation.The key technique is to estimate dip vector exactly and subtly.This paper presents an eccentric window scan method.It involves four eccentric lateral windows and five vertical slipping windows.Then the least square method is used to interpolate accurate dip value.The eccentric scan method avoids ignoring detailed information and the heavy impact of noise.In addition,we use a median filter to dip data so as to remove some noise while preserving the details.Curvature attribute calculated with the dip data scanned from this eccentric window proves a better effect in faults or other geological structure recognition.Meanwhile the signal to noise ratio is increased compared with multi window scan method.