Improved spatial understanding of induced seismicity hazard from the discretization of a curved fault surface

IF 2.1 3区 地球科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computational Geosciences Pub Date : 2024-02-22 DOI:10.1007/s10596-024-10276-z
Kevin L. McCormack, Philip J. Smith
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Abstract

In some geomechanical treatments of induced seismicity, the fault surface is idealized to be a plane. We depart from this assumption by comparing a discretization model and a kriging model, both of which allow the incorporation of rugosity, roughness, and curvature into the fault surface and subsequent geomechanical models of hazard. We test the Hogback Flexural Faults of the San Juan Basin, which could potentially pose a problem for induced seismicity in a carbon sequestration project in the northwestern portion of the basin. The discretization model emmeshes data about the location of the fault surface in three-dimensional space into hexagonally close-packed spheres. Each sphere that contains enough data is termed a region and Bayes’ Law is used to find a distribution of strikes and dips that describe the data within the region. The kriging model uses Gaussian processes to interpolate and extrapolate a surface through all data points. The results show that the discretized regions possess, in general, lower Coulomb failure functions, but the uncertainty in the distributions, i.e., the ranges, becomes greater as the discretization increases due to overfitting. The majority of the uncertainty in both the discretization model and the kriging model is contained in the geomechanical priors. Finally, the discretization and kriging of the fault surface elucidates locations with higher Coulomb failure functions.

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通过对弯曲断层面的离散化改进对诱发地震危害的空间理解
在一些诱发地震的地质力学研究中,断层面被理想化为一个平面。我们偏离了这一假设,比较了离散化模型和克里金模型,这两种模型都可以将凹凸、粗糙度和曲率纳入断层面以及随后的地质力学危险模型中。我们对圣胡安盆地的霍格贝克挠性断层进行了测试,该断层有可能对盆地西北部的碳封存项目造成诱发地震问题。离散化模型将三维空间中断层表面位置的数据emmeshes到六边形紧密堆积的球体中。每个包含足够数据的球体被称为一个区域,贝叶斯定律用于找到描述区域内数据的走向和倾角分布。克里金模型使用高斯过程,通过所有数据点插值和外推一个曲面。结果表明,离散化区域一般具有较低的库仑失效函数,但由于过度拟合,随着离散化程度的增加,分布(即范围)的不确定性也随之增大。离散化模型和克里金模型的大部分不确定性都包含在地质力学先验中。最后,断层面的离散化和克里格法阐明了库仑失效函数较高的位置。
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来源期刊
Computational Geosciences
Computational Geosciences 地学-地球科学综合
CiteScore
6.10
自引率
4.00%
发文量
63
审稿时长
6-12 weeks
期刊介绍: Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing. Papers treating similar topics but with applications to other fields in the geosciences, such as geomechanics, geophysics, oceanography, or meteorology, will also be considered. The journal provides a platform for interaction and multidisciplinary collaboration among diverse scientific groups, from both academia and industry, which share an interest in developing mathematical models and efficient algorithms for solving them, such as mathematicians, engineers, chemists, physicists, and geoscientists.
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