Integrating Spatial Autocorrelation Analysis Using Ambient Noise and Gravity Measurements for Subsurface Characterization

Abstract This study investigates the application of SPatial AutoCorrelation (SPAC) analysis using seismic noise and gravity surveying as a novel geophysical workflow for characterizing subsurface structure of urban areas. The primary objective is to determine subsurface's velocity through seismic noise analysis and, subsequently, estimate their density values using well established empirical relationships. The calculated density values will serve as inputs to refine gravity measurements and enhance subsurface modeling for the investigated area. The proposed methodology was applied to King Fahd University of Petroleum and Minerals (KFUPM) campus in Dhahran, Saudi Arabia. Seismic noise was recorded using a network of broadband wireless sensors spatially distributed within the campus. The analysis of seismic noise recorded at different aperture arrays allowed the determination of phase velocities in a wide frequency range. By inverting this information, the shear-wave velocities of soils (Vs) were extracted at various depths. Exploiting empirical relationships proposed in literature for similar geological environments, the 1D shear-wave velocity profiles were converted to density estimates with depth. These values served as effective inputs to review gravity results available in KFUPM campus and enhance the accuracy of the proposed 2D gravity models. Moreover, the velocity models derived from the SPAC method can be used to constrain and refine the number of subsurface layers interpreted from the gravity data. The derived shear wave velocity and density profiles revealed subsurface structures with distinct seismic properties corresponding to sedimentary sequences and possible tectonic features beneath the campus. The results revealed an ENE-WSW trend contrasting with the primary NNW-SSE joint set observed on the campus. This ENE-WSW orientation aligns with the horizontal stress axis σH, which related to regional intraplate stresses from the Arabian-Eurasian collision, highlighting complex interactions between regional and local tectonic forces. The result of the study makes the combination of SPAC analysis with gravity measurements a promising approach to investigate complex geological environments in urban areas.

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Published
2025-09-16
DOI
https://doi.org/10.2118/227226-ms
Primary Topic
Seismic Waves and Analysis
Type
article
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article

Integrating Spatial Autocorrelation Analysis Using Ambient Noise and Gravity Measurements for Subsurface Characterization

Pantelis Soupios, Alexandros Stampolidis, Maria Manakou, Panagiotis Kirmizakis
Seismic Waves and Analysis
article

Integrating Spatial Autocorrelation Analysis Using Ambient Noise and Gravity Measurements for Subsurface Characterization

Pantelis Soupios, Alexandros Stampolidis, Maria Manakou, Panagiotis Kirmizakis
article en

Abstract

Abstract This study investigates the application of SPatial AutoCorrelation (SPAC) analysis using seismic noise and gravity surveying as a novel geophysical workflow for characterizing subsurface structure of urban areas. The primary objective is to determine subsurface's velocity through seismic noise analysis and, subsequently, estimate their density values using well established empirical relationships. The calculated density values will serve as inputs to refine gravity measurements and enhance subsurface modeling for the investigated area. The proposed methodology was applied to King Fahd University of Petroleum and Minerals (KFUPM) campus in Dhahran, Saudi Arabia. Seismic noise was recorded using a network of broadband wireless sensors spatially distributed within the campus. The analysis of seismic noise recorded at different aperture arrays allowed the determination of phase velocities in a wide frequency range. By inverting this information, the shear-wave velocities of soils (Vs) were extracted at various depths. Exploiting empirical relationships proposed in literature for similar geological environments, the 1D shear-wave velocity profiles were converted to density estimates with depth. These values served as effective inputs to review gravity results available in KFUPM campus and enhance the accuracy of the proposed 2D gravity models. Moreover, the velocity models derived from the SPAC method can be used to constrain and refine the number of subsurface layers interpreted from the gravity data. The derived shear wave velocity and density profiles revealed subsurface structures with distinct seismic properties corresponding to sedimentary sequences and possible tectonic features beneath the campus. The results revealed an ENE-WSW trend contrasting with the primary NNW-SSE joint set observed on the campus. This ENE-WSW orientation aligns with the horizontal stress axis σH, which related to regional intraplate stresses from the Arabian-Eurasian collision, highlighting complex interactions between regional and local tectonic forces. The result of the study makes the combination of SPAC analysis with gravity measurements a promising approach to investigate complex geological environments in urban areas.

King Fahd University of Petroleum and Minerals (SA), Aristotle University of Thessaloniki (GR)
Openalex Percentile: Top 74%
Seismic Waves and Analysis
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