Highly repeatable time-lapse seismic with distributed compressive sensing — Mitigating effects of calibration errors
Highly repeatable time-lapse seismic with distributed compressive sensing — Mitigating effects of calibration errors
复制标题
具有分布式压缩传感的高度可重复的时移地震 - 减轻校准误差的影响
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
F. Herrmann
中科院分区：
文献类型：
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作者：
F. Oghenekohwo;F. Herrmann
摘要 最近，我们证明，将联合恢复与针对时移地震定制的低成本非重复随机采样相结合，可以使我们获得高保真度、高可重复性、密集叠前年份和高品位时移。为了得出这个结果，我们假设了经过良好校准的调查——即，我们假设了准确的图后源/接收器位置。不幸的是，在实践中，地震勘测很容易出现校准误差，这是实际和绘图后采集几何形状之间的未知偏差。通过综合实验，我们分析了这些误差对年份和通过压缩抽样调查的联合恢复模型获得的延时数据可能产生的影响。在这些实验的支持下，我们证明，尽管镜头位置存在未知的校准误差，但仍可以获得高度可重复的延时摄影。我们通过研究校准误差的影响来定量评估两种情况的重复性...
Abstract Recently, we demonstrated that combining joint recovery with low-cost nonreplicated randomized sampling tailored to time-lapse seismic can give us access to high-fidelity, highly repeatable, dense prestack vintages, and high-grade time lapse. To arrive at this result, we assumed well-calibrated surveys — i.e., we presumed accurate postplot source/receiver positions. Unfortunately, in practice, seismic surveys are prone to calibration errors, which are unknown deviations between actual and postplot acquisition geometry. By means of synthetic experiments, we analyze the possible impact of these errors on vintages and on time-lapse data obtained with our joint-recovery model from compressively sampled surveys. Supported by these experiments, we demonstrate that highly repeatable time-lapse vintages are attainable despite the presence of unknown calibration errors in the positions of the shots. We assess the repeatability quantitatively for two scenarios by studying the impact of calibration errors o...