Two Quantity Estimation Models of Mineral Resource Potential Area

Article Preview

Abstract:

The estimation of the mineral resources area (target area) number is an important part of mathematical geology. Total resource depends not only on the scale of the single target mineralization but is also proportional to the number of target area. In this paper, the target area quantitative algorithm was studied based on the domestic and abroad opinions. The Petersen capture model and Poisson model were introduced into the estimation of resource maternal capacity. In order to meet the requirements of the two models, sampling plan were re-designed and improved. Take 1/200,000 gold mines and metal (Cu, Ag, Pb, Zn) mineral resources prediction in Hebei Province as an example, two practical estimation models of the resource maternal capacity were established. Calculation shows that the results of Petersen capture model and Poisson model were similar and can be as an effective predictor of district resource capacity. Therefore, the bottleneck of regional resource total forecasting calculation method is solved.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2292-2298

Citation:

Online since:

August 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] He Xuan-sen. Random Process. Beijing: People Post Press. (2009), p.25.

Google Scholar

[2] Li Chun-hua, Lu Lai-jun, Bi Ming-li, Wang Miao, Zhao Guo-lei. Global Geology. Vol 29(1) (2010), p.70.

Google Scholar

[3] Wang Rui-ting , Mao Jing-wen , Ren Xiao-hua , et. al. Chinese Geology , Vol 32 (2005), p.168.

Google Scholar

[4] Zhao Zhen-yu, Wang Shi-cheng, Xu Ya-ming , eta. World Geology, Vol 21 (3) (2002), p.283.

Google Scholar

[5] Pan Guo-cheng. Geological Bulletin Of China. Vol 29(10) (2010), p.1413.

Google Scholar

[6] Li Chun-hua , Lu Lai-jun , Wang Di-xiu. Journal of Jilin University: Earth Science Edition, Vol 40(2) (2010), p.461.

Google Scholar

[7] Chen Jun-gang , Zhang Jian-xun , Huang Yong-nian, Li Jing-rong. Journal Of Ningbo Universtty. Vol 18(4) (2005), p.421.

Google Scholar

[8] Shou Ji-lin, Tarafdar E U, Li Yan-mei. Journal of Biomathematics, Vol 13(1) (1998), p.9.

Google Scholar

[9] Wang Shi-cheng, Yang Yi-heng. Qualitative Data Analysis Of Mineral Re-sources Prognosis Of Synthetic Information. Changchun: Jilin Univercity Press. (1999), p.33.

Google Scholar

[10] Peter A. Rona , Steven D. Scott. Economic Geology, Vol 88(8) (1993), p. (1935).

Google Scholar

[11] Zhao Peng-da, Hu Wang-liang. Xinjiang Geology. Vol 10(2) (1992), p.93.

Google Scholar

[12] Chen Yu-chuan. The Gold Deposit Metallogeny In China. Beijing: Geological Publishing House, (2001), p.5.

Google Scholar

[13] Wang Shi-cheng, Cheng Qiu-ming, Fan Ji-zhang, et al. Gold Ore Resources Synthesis Information Appraisal Method. Changchun: Jilin Science and Technology Publishing House, (1990), p.10.

Google Scholar

[14] Wei Yuan-tai,Lu Lai-jun,Shao Zhen-guo. The Report Of HeBei Solid Mineral Au Cu Ag Pb. Zn Second Round Mineral Resources Area Planning. Shi Jia-zhuang: HeBei Bureau of Geology and Mineral Resources Exploration, (1994), p.129.

Google Scholar