『Abstract
Traditional geometric and geostatistic methods for reserve estimation
in a single deposit are difficult to use with skewed distribution
mineralization variables including grade, orebody thickness and
grade-thickness, a common characteristic of most deposits, and
require complex data processing. It has been shown that the skewed
mineralization variables can be described by the number-size model
in a fractal domain. Based on the number-size model, assuming
that orebody thickness and grade-thickness are continuous variables,
the fractal model for reserve estimation (FMRE) in a single deposit
can be established. In the FMRE, ore tonnage can be estimated
given the orebody area and the fractal parameters of orebody thickness
distribution and metal tonnage can be estimated based on the orebody
area and the fractal parameters of grade-thickness distribution.
The reserve estimated by the FMRE can denote actual ore tonnage
and metal tonnage that can be mined out of the deposit. The FRME
was applied to the Dayingezhuang gold deposit in the Jiaodong
gold province in China. The gold reserves via the FMRE and the
traditional geometric block method are similar, with relative
errors of 3.11％ in ore tonnage and 0.29％ in metal tonnage. Compared
to traditional reserve estimation the FMRE is much easier in calculation
process and is more reasonable in dealing with the skewed distribution.
However, this new method fails to calculate local reserve, which
can be derived via any of the traditional estimation methods.
Keywords: Ore reserves; Jiaodong gold province; Fractal modeling』
1. Introduction
1.1. Traditional reserve estimation methods
1.2. Fractal models in geology
1.3. Research objective
2. Mathematical modeling
2.1. Preliminary processing of raw data
2.2. Block modeling
2.3. Fractal algorithms
2.3.1. Number-size model
2.3.2. Fractal model for ore tonnage estimation
2.3.3. Fractal model for metal tonnage estimation
2.3.4. Grade estimation
2.4. Limitations of the FMRE
2.4.1. Exploration grid density
2.4.2. Ore density
2.4.3. Variable limit
2.5. Steps in the FMRE
3. Case study
3.1. Regional geology and deposit geology
3.1.1. Regional geology
3.1.2. Deposit geology
3.2. Deposit explorations and raw data
3.3. FMRE application
3.3.1. Consistence test of the fractal model
3.3.2. Reserve estimation
4. Discussion
4.1. Estimation result
4.2. Comparison between FMRE and traditional methods
4.3. FMRE application scope
5. Conclusions
Acknowledgements
References