Near surface sediments introduce low frequency noise into gravity models

IF 2.6 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Applied Computing and Geosciences Pub Date : 2023-09-01 DOI:10.1016/j.acags.2023.100131
G.A. Phelps, C. Cronkite-Ratcliff
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Abstract

3D geologic modeling and mapping often relies on gravity modeling to identify key geologic structures, such as basin depth, fault offset, or fault dip. Such gravity models generally assume either homogeneous or spatially uncorrelated densities within modeled rock bodies and overlying sediments, with average densities typically derived from surface and drill-hole sampling. The noise contributed to the gravity anomaly by these density assumptions is zero in the homogeneous case and typically <200 μGal in the uncorrelated case. Rock bodies and sediments, however, show both a range of densities and spatial correlation of these densities, in both surface and drill-hole samples, and this correlation causes an increase in power in the low frequency content of the resulting gravity anomaly. Spatial correlation of densities can be modeled as a Gaussian random field (GRF), with the random field parameters derived from drill-hole and geologic map data. Data from alluvial fan sediments in southern Nevada indicate correlation lengths of up to 300 m in the vertical dimension and kilometers in the horizontal dimension. The resulting GRF density models show that the noise contributed to the measured gravity anomaly is of low frequency and can be several mGal in amplitude, contradicting the common attribution of lower frequencies to deeper sources. This low-frequency noise increases in power with an increase in sediment thickness. Its presence increases the ambiguity of interpretations of subsurface geologic body shape, such as basin analyses that attempt to quantify concealed basement fault depths, offsets, and dip angles. In the southwestern United States, where basin analyses are important for natural resource applications, such ambiguity increases the uncertainty of subsequent process modeling.

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近地表沉积物将低频噪声引入重力模型
三维地质建模和制图通常依赖于重力建模来识别关键的地质构造,如盆地深度、断层偏移或断层倾角。这种重力模型通常假设在模拟的岩体和上覆沉积物中密度均匀或在空间上不相关,其平均密度通常来自地面和钻孔取样。这些密度假设对重力异常的贡献在均匀情况下为零,在不相关情况下通常为<200 μGal。然而,在地表和钻孔样品中,岩体和沉积物都显示出密度范围和这些密度的空间相关性,这种相关性导致所产生的重力异常的低频含量的功率增加。密度的空间相关性可以建模为高斯随机场(GRF),随机场参数来源于钻孔和地质图数据。来自内华达州南部冲积扇沉积物的数据表明,相关长度在垂直维度上可达300米,在水平维度上可达公里。由此得到的GRF密度模型表明,导致测量重力异常的噪声频率较低,振幅可达几mGal,这与通常将较低频率归因于较深来源的观点相矛盾。这种低频噪声的功率随着沉积物厚度的增加而增加。它的存在增加了对地下地质体形状解释的模糊性,例如试图量化隐伏基底断层深度、偏移量和倾角的盆地分析。在美国西南部,盆地分析对自然资源应用很重要,这种模糊性增加了后续过程建模的不确定性。
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来源期刊
Applied Computing and Geosciences
Applied Computing and Geosciences Computer Science-General Computer Science
CiteScore
5.50
自引率
0.00%
发文量
23
审稿时长
5 weeks
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