Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition

Microseismic monitoring is an important technology used to evaluate hydraulic fracturing, and denoising is a crucial processing step. Analyses of the characteristics of acquired three-component microseismic data have indicated that the vertical component has a higher signal-to-noise ratio (SNR) than...

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Autores principales:	Zhili Chen, Peng Wang, Zhixian Gui, Qinghui Mao
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	three-component microseismic data denoising method re-constrain VMD constrained optimization polarization analysis 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/4afb998a4faa4406b8d5e50ec3ecf521
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spelling	oai:doaj.org-article:4afb998a4faa4406b8d5e50ec3ecf5212021-11-25T16:41:37ZThree-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition10.3390/app1122109432076-3417https://doaj.org/article/4afb998a4faa4406b8d5e50ec3ecf5212021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10943https://doaj.org/toc/2076-3417Microseismic monitoring is an important technology used to evaluate hydraulic fracturing, and denoising is a crucial processing step. Analyses of the characteristics of acquired three-component microseismic data have indicated that the vertical component has a higher signal-to-noise ratio (SNR) than the two horizontal components. Therefore, we propose a new denoising method for three-component microseismic data using re-constrain variational mode decomposition (VMD). In this method, it is assumed that there is a linear relationship between the modes with the same center frequency among the VMD results of the three-component data. Then, the decomposition result of the vertical component is used as a constraint to the whole denoising effect of the three-component data. On the basis of VMD, we add a constraint condition to form the re-constrain VMD, and deduce the corresponding solution process. According to the synthesis data analysis, the proposed method can not only improve the SNR level of three-component records, it also improves the accuracy of polarization analysis. The proposed method also achieved a satisfactory effect for field data.Zhili ChenPeng WangZhixian GuiQinghui MaoMDPI AGarticlethree-component microseismic datadenoising methodre-constrain VMDconstrained optimizationpolarization analysisTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10943, p 10943 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	three-component microseismic data denoising method re-constrain VMD constrained optimization polarization analysis Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	three-component microseismic data denoising method re-constrain VMD constrained optimization polarization analysis Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Zhili Chen Peng Wang Zhixian Gui Qinghui Mao Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition
description	Microseismic monitoring is an important technology used to evaluate hydraulic fracturing, and denoising is a crucial processing step. Analyses of the characteristics of acquired three-component microseismic data have indicated that the vertical component has a higher signal-to-noise ratio (SNR) than the two horizontal components. Therefore, we propose a new denoising method for three-component microseismic data using re-constrain variational mode decomposition (VMD). In this method, it is assumed that there is a linear relationship between the modes with the same center frequency among the VMD results of the three-component data. Then, the decomposition result of the vertical component is used as a constraint to the whole denoising effect of the three-component data. On the basis of VMD, we add a constraint condition to form the re-constrain VMD, and deduce the corresponding solution process. According to the synthesis data analysis, the proposed method can not only improve the SNR level of three-component records, it also improves the accuracy of polarization analysis. The proposed method also achieved a satisfactory effect for field data.
format	article
author	Zhili Chen Peng Wang Zhixian Gui Qinghui Mao
author_facet	Zhili Chen Peng Wang Zhixian Gui Qinghui Mao
author_sort	Zhili Chen
title	Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition
title_short	Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition
title_full	Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition
title_fullStr	Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition
title_full_unstemmed	Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition
title_sort	three-component microseismic data denoising based on re-constrain variational mode decomposition
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/4afb998a4faa4406b8d5e50ec3ecf521
work_keys_str_mv	AT zhilichen threecomponentmicroseismicdatadenoisingbasedonreconstrainvariationalmodedecomposition AT pengwang threecomponentmicroseismicdatadenoisingbasedonreconstrainvariationalmodedecomposition AT zhixiangui threecomponentmicroseismicdatadenoisingbasedonreconstrainvariationalmodedecomposition AT qinghuimao threecomponentmicroseismicdatadenoisingbasedonreconstrainvariationalmodedecomposition
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Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition

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