Abstract

Global Geology 2015, 18(4) 232- DOI: ISSN: 1673-9736 CN: 22-1371/P

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	Keywords
	shear- wave splitting
	particle swarm optimization
	Pearson correlation coefficient
	shrinkage factor
	Authors
	ZHOU Chao
	FENG Xuan
	ZHANG Bing
	LU Xiaoman
	JIN Zelong and XU Cong
	PubMed
	Article by ZHOU Chao
	Article by FENG Xuan
	Article by ZHANG Bing
	Article by LU Xiaoman
	Article by JIN Zelong and XU Cong

Fracture property identification method based on shrinkage factor particle swarm optimization

ZHOU Chao, FENG Xuan, ZHANG Bing, LU Xiaoman, JIN Zelong and XU Cong

1�� College of Geo- Exploration Science and Technology�� Jilin University�� Changchun 130026�� China; 2�� Baixian Company��Northeast Electric Power Design Institute Co��Ltd�� of China Power Engineering Consulting Group�� Changchun 130021��China

Abstract��

In the multi- wave and multi- component seismic exploration��shear- wave will be split into fast wave and slow wave�� when it propagates in anisotropic media�� Then the authors can predict polarization direction and density of crack and detect the development status of cracks underground according to shear- wave splitting phe- nomenon�� The technology plays an important role and shows great potential in crack reservoir detection�� In this study��the improved particle swarm optimization algorithm based on shrinkage factor is combined with the Pear- son correlation coefficient method to obtain the fracture azimuth angle and density�� The experimental results show that the modified method can improve the convergence rate��accuracy��anti- noise performance and compu- tational efficiency��

Keywords�� shear- wave splitting particle swarm optimization Pearson correlation coefficient shrinkage factor

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