Seismic Attributes and Acoustic Inversion for Shallow Marine Slope Stratigraphy Analysis

J. Son, Rebecca Boon, Julien Kuhn de Chizelle
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Abstract

Geophysical seismic surveys have been used in marine site characterization for subsea engineering and the design of offshore structures. Signal processing plays a key role in obtaining seismic attributes from observed seismic data to identify subsurface geological features within complex shallow sediments. Instantaneous amplitude, phase, and frequency are the most widely used seismic attributes to indicate geological features, but those time-domain data are too limited to define an accurate subsurface model in depth. Therefore, seismic inversion is also required to generate additional geospatial subsurface model information to aid in shallow stratigraphy interpretation. In this paper, we applied both geophysical signal processing and stochastic seismic inversion to a high-resolution multichannel seismic dataset from the Eastern North American Margin (ENAM). Seismic attributes from the Hilbert transform and inversion modeling results (acoustic impedance and modeling uncertainty) were integrated to define better geological horizons and discontinuities. The results show the integrated geophysical subsurface models can support seismic interpretation and improve shallow marine site characterization.
浅海斜坡地层地震属性与声波反演分析
地球物理地震调查已被用于海底工程和海上结构设计的海洋场地表征。信号处理是从观测地震资料中获取地震属性,识别复杂浅层沉积物地下地质特征的关键。瞬时振幅、相位和频率是最广泛用于指示地质特征的地震属性,但这些时域数据太有限,无法定义精确的地下深度模型。因此,地震反演还需要生成额外的地理空间地下模型信息,以帮助浅层地层解释。在本文中,我们将地球物理信号处理和随机地震反演应用于北美东部边缘(ENAM)的高分辨率多通道地震数据集。希尔伯特变换和反演建模结果的地震属性(声阻抗和建模不确定性)相结合,以确定更好的地质层位和不连续面。结果表明,综合地球物理地下模型可以支持地震解释,改善浅海测点特征。
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