被动源瑞利波两道法提取频散曲线的质量控制方法

doi:10.11720/wtyht.2019.0299

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Abstract

In recent years,the rapidly developed passive Rayleigh wave technology has the advantage of strong anti-interference capability and less limited construction conditions by using environmental noise as the source,which is more suitable for exploration in urban areas.However,the key factor affecting the imaging accuracy of the passive source method is the extracting quality of the dispersion curves.The current passive source Rayleigh wave method mainly uses the Aki formula to calculate the Rayleigh wave dispersion curve according to the relationship between spatial autocorrelation and time domain cross-correlation.This method has a good extraction effect for long-period observation data (for several months or more).Nevertheless,for practical engineering applications,it is desirable that the data observation period is as short as possible (such as one day or several hours).Under this circumstance,it will lead the zero points of the cross-correlation spectrum to increase or disappear,which will bring errors in the extraction of the dispersion curves when the Aki method is used to pick up them.Aimed at solving this problem,the authors put forward a set of quality control processes,such as using different normalization methods,selecting different window lengths for cross-correlation operations,setting Gaussian filters to filter cross-correlation functions,and selecting spectral zeros,to improve the extracting quality of dispersion curves.The authors combined certain evaluation criteria to verify the reliability of the dispersion curves and achieved the purpose of controlling the quality of the dispersion curves extraction.The passive source numerical simulation of theoretical model testing and the actual field noise data processing in Fengxiang County of Shaanxi show that the quality control method in the dispersion curve extraction is feasible and effective.This study has certain reference value and practical significance for the dispersion curve extraction of passive source Rayleigh wave method.

Key words： Rayleigh wave dispersion curve passive source quality control

Received: 28 May 2019 Published: 28 November 2019

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	Guang-Zhou SHAO
	Liang YUE
	Yuan-Lin LI
	Hua WU

Cite this article:

Guang-Zhou SHAO,Liang YUE,Yuan-Lin LI, et al. A study of quality control of extracting dispersion curves by two-channel method of passive Rayleigh waves[J]. Geophysical and Geochemical Exploration, 2019, 43(6): 1297-1308.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2019.0299 OR https://www.wutanyuhuatan.com/EN/Y2019/V43/I6/1297

Parameters of two-layer increasing velocity model

Distribution diagram of noise source points

Passive Rayleigh wave seismic records of two-layer increasing velocity model

Field surveying line array

Field measured background noise signal
a—field background noise signal on line 6;b—active source seismic signal on line 6

Flow chart of passive source Rayleigh wave data processing

Filtering results of field measured background noise signals
a—spectrum curve of original data;b—spectrum curve of filtered data

Processing results of time domain normalization
a—0~30 s seismic signal after filtering;b—filtered signal spectrum;c—seismic signal after "one-bit" method processed;d—signal spectrum after "one-bit" method processed;e—seismic signal after moving absolute average method processed;f—signal spectrum after moving absolute average method processed

Whitening results of frequency domain normalization
a—seismic signal after "one-bit" method bleached;b—signal spectrum after "one-bit" method bleached;c—seismic signal after moving absolute average method bleached;f—signal spectrum after moving absolute average method bleached

SNR of cross-correlation results after whitening

Influence of window length on cross-correlation results
a—the cross-correlation result with time window length of 1 s;b—the cross-correlation result with time window length of 3 s;c—the cross-correlation result with time window length of 6 s;d—the cross-correlation result with time window length of 12 s

SNR with different time window length

Cross-correlation records after Gauss filtering

Dispersion curves of geophone pairs 1~14 at different m for the theoretical model

Dispersion curve obtained by partial processing for the theoretical model

The degree of approximation between the extracted and the theoretical dispersion curve

Dispersion curves of field measured data with different m

Dispersion curves of Line 6

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