Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method

Erecting underground structures in regions with unidentified weak layers, cavities, and faults is highly dangerous and potentially disastrous. An efficient and accurate near-surface exploration method is thus of great significance for guiding construction. In near-surface detection, imaging methods...

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Autores principales:	Ming Peng, Dengyi Wang, Liu Liu, Chengcheng Liu, Zhenming Shi, Fuan Ma, Jian Shen
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	near-surface seismic imaging beamforming underground structure reflection seismic Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/3f1301a99bfe40e78bd8ca64665b33fc
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spelling	oai:doaj.org-article:3f1301a99bfe40e78bd8ca64665b33fc2021-11-25T16:38:44ZNear-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method10.3390/app1122108272076-3417https://doaj.org/article/3f1301a99bfe40e78bd8ca64665b33fc2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10827https://doaj.org/toc/2076-3417Erecting underground structures in regions with unidentified weak layers, cavities, and faults is highly dangerous and potentially disastrous. An efficient and accurate near-surface exploration method is thus of great significance for guiding construction. In near-surface detection, imaging methods suffer from artifacts that the complex structure caused and a lack of efficiency. In order to realize a rapid, accurate, robust near-surface seismic imaging, a minimum variance spatial smoothing (MVSS) beamforming method is proposed for the seismic detection and imaging of underground geological structures under a homogeneous assumption. Algorithms such as minimum variance (MV) and spatial smoothing (SS), the coherence factor (CF) matrix, and the diagonal loading (DL) methods were used to improve imaging quality. Furthermore, it was found that a signal advance correction helped improve the focusing effect in near-surface situations. The feasibility and imaging quality of MVSS beamforming are verified in cave models, layer models, and cave-layer models by numerical simulations, confirming that the MVSS beamforming method can be adapted for seismic imaging. The performance of MVSS beamforming is evaluated in the comparison with Kirchhoff migration, the DAS beamforming method, and reverse time migration. MVSS beamforming has a high computational efficiency and a higher imaging resolution. MVSS beamforming also significantly suppresses the unnecessary components in seismic signals such as S-waves, surface waves, and white noise. Moreover, compared with basic delay and sum (DAS) beamforming, MVSS beamforming has a higher vertical resolution and adaptively suppresses interferences. The results show that the MVSS beamforming imaging method might be helpful for detecting near-surface underground structures and for guiding engineering construction.Ming PengDengyi WangLiu LiuChengcheng LiuZhenming ShiFuan MaJian ShenMDPI AGarticlenear-surfaceseismic imagingbeamformingunderground structurereflection seismicTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10827, p 10827 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	near-surface seismic imaging beamforming underground structure reflection seismic Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	near-surface seismic imaging beamforming underground structure reflection seismic Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Ming Peng Dengyi Wang Liu Liu Chengcheng Liu Zhenming Shi Fuan Ma Jian Shen Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method
description	Erecting underground structures in regions with unidentified weak layers, cavities, and faults is highly dangerous and potentially disastrous. An efficient and accurate near-surface exploration method is thus of great significance for guiding construction. In near-surface detection, imaging methods suffer from artifacts that the complex structure caused and a lack of efficiency. In order to realize a rapid, accurate, robust near-surface seismic imaging, a minimum variance spatial smoothing (MVSS) beamforming method is proposed for the seismic detection and imaging of underground geological structures under a homogeneous assumption. Algorithms such as minimum variance (MV) and spatial smoothing (SS), the coherence factor (CF) matrix, and the diagonal loading (DL) methods were used to improve imaging quality. Furthermore, it was found that a signal advance correction helped improve the focusing effect in near-surface situations. The feasibility and imaging quality of MVSS beamforming are verified in cave models, layer models, and cave-layer models by numerical simulations, confirming that the MVSS beamforming method can be adapted for seismic imaging. The performance of MVSS beamforming is evaluated in the comparison with Kirchhoff migration, the DAS beamforming method, and reverse time migration. MVSS beamforming has a high computational efficiency and a higher imaging resolution. MVSS beamforming also significantly suppresses the unnecessary components in seismic signals such as S-waves, surface waves, and white noise. Moreover, compared with basic delay and sum (DAS) beamforming, MVSS beamforming has a higher vertical resolution and adaptively suppresses interferences. The results show that the MVSS beamforming imaging method might be helpful for detecting near-surface underground structures and for guiding engineering construction.
format	article
author	Ming Peng Dengyi Wang Liu Liu Chengcheng Liu Zhenming Shi Fuan Ma Jian Shen
author_facet	Ming Peng Dengyi Wang Liu Liu Chengcheng Liu Zhenming Shi Fuan Ma Jian Shen
author_sort	Ming Peng
title	Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method
title_short	Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method
title_full	Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method
title_fullStr	Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method
title_full_unstemmed	Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method
title_sort	near-surface geological structure seismic wave imaging using the minimum variance spatial smoothing beamforming method
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3f1301a99bfe40e78bd8ca64665b33fc
work_keys_str_mv	AT mingpeng nearsurfacegeologicalstructureseismicwaveimagingusingtheminimumvariancespatialsmoothingbeamformingmethod AT dengyiwang nearsurfacegeologicalstructureseismicwaveimagingusingtheminimumvariancespatialsmoothingbeamformingmethod AT liuliu nearsurfacegeologicalstructureseismicwaveimagingusingtheminimumvariancespatialsmoothingbeamformingmethod AT chengchengliu nearsurfacegeologicalstructureseismicwaveimagingusingtheminimumvariancespatialsmoothingbeamformingmethod AT zhenmingshi nearsurfacegeologicalstructureseismicwaveimagingusingtheminimumvariancespatialsmoothingbeamformingmethod AT fuanma nearsurfacegeologicalstructureseismicwaveimagingusingtheminimumvariancespatialsmoothingbeamformingmethod AT jianshen nearsurfacegeologicalstructureseismicwaveimagingusingtheminimumvariancespatialsmoothingbeamformingmethod
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Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method

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