非线性矿床模型与非常规矿产资源评价

成秋明

Volume 28 Issue 4

Jul. 2003

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CHENG Qiu-ming, 2003. Non-Linear Mineralization Model and Information Processing Methods for Prediction of Unconventional Mineral Resources. Earth Science, 28(4): 445-454.

Citation:

CHENG Qiu-ming, 2003. Non-Linear Mineralization Model and Information Processing Methods for Prediction of Unconventional Mineral Resources. Earth Science, 28(4): 445-454.

CHENG Qiu-ming, 2003. Non-Linear Mineralization Model and Information Processing Methods for Prediction of Unconventional Mineral Resources. Earth Science, 28(4): 445-454.

Citation:

CHENG Qiu-ming, 2003. Non-Linear Mineralization Model and Information Processing Methods for Prediction of Unconventional Mineral Resources. Earth Science, 28(4): 445-454.

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Non-Linear Mineralization Model and Information Processing Methods for Prediction of Unconventional Mineral Resources

CHENG Qiu-ming^{1, 2
,}

1.
L aboratory of Earth Systems and Mineral Resources Engineering, China University of Geosciences, Wuhan 430074, China
2.
Department of Earth and Atmospheric Science, York University, Toronto, Canada M3J1P3

Received Date: 2003-04-21
Publish Date: 2003-07-25

Abstract

Abstract

A non-linear mineralization model was proposed on the basis of a classical igneous differentiation mineralization model which can describe the generation of multi-fractal distribution of element concentration as well as grade-tonnage fractal/multi-fractal model. The work has also led to a model to explain the common properties of mineralization and mineralization-associated geochemical anomaly diversity and generalized self-similarity of the anomalies. Generalized self-similarity is related to the generalized scaling invariance which can characterize the external diversity and internal similarity of natural phenomena including mineralization and occurrence of mineral deposits. The models based on core principal of generalized self-similarity and singularity analysis have been applied to a case study of Co-Ni-Ag-As-Pb mineral resources assessment in the Gowganda area of Abitibi district, northern Ontario, Canada. The results have demonstrated that the non-linear models proposed in the current research are effective for delineating week lake sediment and water geochemical anomalies caused by deeply buried sources or week anomalies superimposed to low background values.
- non-linear mineralization model,
- generalized self-similarity,
- singularity analysis method,
- mineralization index,
- GIS data integration

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References(28)

References

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