Recognition and reconstruction of coherent energy with application to deep seismic reflection data
Recognition and reconstruction of coherent energy with application to deep seismic reflection data
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DOI：
10.1190/1.1444763
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发表时间：
2000-03
期刊：
影响因子：
3.3
通讯作者：
M. Baan;A. Paul
中科院分区：
文献类型：
--
作者：
M. Baan;A. Paul
深地震反射数据中的反射往往仅在公共中点道集中的有限数量的道上可见。为了防止堆栈退化，必须消除任何非相干反射能量。本文提出了一种遥感标准分类技术来提高数据质量。它包含一种识别技术，用于检测和提取共同镜头集合和最终堆栈中的相干能量。该技术使用所选地震相位的统计数据来获取其存在的似然分布。该似然分布与原始数据相乘会产生“清理”部分。将该技术应用于深部地震反射实验的数据，大大提高了所有反射体的可见度。由于识别技术无法产生“缺失”数据的估计，因此通过重建方法对其进行了扩展。提出了两种方法：识别后应用相似加权局部倾斜堆栈，以及在线性？ -p 域。在这两种情况下，叠加过程提高信噪比的能力与仅直接选择特定地震相位相结合。识别和重建的联合应用产生的数据图像比单一技术的应用更清晰地显示反射体。
Reflections in deep seismic reflection data tend to be visible on only a limited number of traces in a common midpoint gather. To prevent stack degeneration, any noncoherent reflection energy has to be removed. In this paper, a standard classification technique in remote sensing is presented to enhance data quality. It consists of a recognition technique to detect and extract coherent energy in both common shot gathers and final stacks. This technique uses the statistics of a picked seismic phase to obtain the likelihood distribution of its presence. Multiplication of this likelihood distribution with the original data results in a “cleaned up” section. Application of the technique to data from a deep seismic reflection experiment enhanced the visibility of all reflectors considerably. Because the recognition technique cannot produce an estimate of “missing” data, it is extended with a reconstruction method. Two methods are proposed: application of semblance weighted local slant stacks after recognition, and direct recognition in the linear ? - p domain. In both cases, the power of the stacking process to increase the signal-to-noise ratio is combined with the direct selection of only specific seismic phases. The joint application of recognition and reconstruction resulted in data images which showed reflectors more clearly than application of a single technique.