RESEARCH ON THE SPATIAL ASSOCIATION BETWEEN ORE DEPOSITS AND FRACTURES

BI Tian-ping; HU Zhi-yong; JIN Cheng-zhu

doi:10.13686/j.cnki.dzyzy.2010.02.013

2010 Vol. 19, No. 2

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Article navigation > Geology and Resources > 2010 > 19(2): 164-169

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BI Tian-ping, HU Zhi-yong, JIN Cheng-zhu. RESEARCH ON THE SPATIAL ASSOCIATION BETWEEN ORE DEPOSITS AND FRACTURES[J]. Geology and Resources, 2010, 19(2): 164-169. doi: 10.13686/j.cnki.dzyzy.2010.02.013

Citation:

BI Tian-ping, HU Zhi-yong, JIN Cheng-zhu. RESEARCH ON THE SPATIAL ASSOCIATION BETWEEN ORE DEPOSITS AND FRACTURES[J]. Geology and Resources, 2010, 19(2): 164-169. doi: 10.13686/j.cnki.dzyzy.2010.02.013

RESEARCH ON THE SPATIAL ASSOCIATION BETWEEN ORE DEPOSITS AND FRACTURES

1.
Department of Geology Engineering, Northeastern University, Shenyang 110004, China;
2.
University of West Florida, FL 32514, USA

Received Date: 09 April 2010

Revised Date: 11 May 2010

Publish Date: 30 June 2010

Abstract

Abstract

This study uses spatial statistical methods to investigate spatial relationship between ore deposits and fractures in Liaoning Province of China. Firstly, Ripley's K-function and bivariate J function find that the ore deposits have a clustering trend around the fractures. Secondly, a conditional intensity formula for ore deposits based on Poisson process is used to model the ore deposits' spatial dependence on the fractures, and the formula of model is fitted in statistics software called R. Finally, the fitted model is used to predict high intensity areas of invisible ore deposits based on locations of visible fractures, which could be used to guide ore deposit exploration.
- bivariate J function /
- Poisson process /
- spatial relationship /
- model fitting