Hybrid Tomography and Full Waveform Inversion Velocity Model Updating for Shallow Velocity Anomalies

G. Hilburn, J. Mao, J. Sheng, S. Baldock, M. Hart
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Abstract

Summary Geologically reasonable, data-driven velocity model building is a critical process for seismic imaging, particularly when the velocity is strongly heterogeneous within a layer or structure. When such features are prominent in the shallow, disruption of the signal may propagate through a significant portion of the image. A hybrid tomography-FWI workflow incorporating image-guided tomography and phase-only reflection full-waveform inversion is proposed as a method for generating robust and detailed model updates in these situations. Application to a narrow azimuth streamer survey demonstrates the effectiveness of the method in yielding detailed model updates and simplified geological structures in the final image.
浅层速度异常的混合层析和全波形反演速度模型更新
从地质学上讲,数据驱动的速度模型建立是地震成像的关键过程,特别是当层或结构内的速度非常不均匀时。当这些特征在浅层中突出时,信号的中断可以通过图像的很大一部分传播。本文提出了一种结合图像引导层析成像和纯相位反射全波形反演的混合层析成像- fwi工作流程,作为在这些情况下生成鲁棒且详细的模型更新的方法。在窄方位角拖缆测量中的应用表明,该方法在生成详细的模型更新和最终图像中的简化地质结构方面是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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