Coal exploratory pattern estimation by geological uncertainty and analysis of fault presence effect (Parvadeh III region)

Geostatistical simulation methods have known as a powerful tool for estimating spatial distribution of geological uncertainty and risk in the mining exploration. This method is used in metal mining industry very much but was less in coal mining industry. Parvadeh III is located in east of central Iran. This deposit has 5 layers as: C1, C2, B1, B2, and D, that layer C1 was chosen as a layer which can reflect alone the specification of Parvadeh III because of low ash, lack of continuity of the coefficient of zero and first place in terms of having quality. In this research, at first Sequential Gaussian Simulation (SGS) has applied in order to carbon accumulation and fault estimation. Then accumulation geological uncertainty for coal resource classification has obtained using error maps. More optimal number of boreholes in the area, according to the 95% confidence level has determined. Since the uncertainty and risk have significant role in geological fault coal resource estimation and previous studies estimated mineral resources and reserves of coal has also been ignored, according to these criteria the presence of fault probability maps were determined. The places that have probability of fault presence about 100% are the riskiest regions for coal resource estimation. Finally, this method can be used for subsequent analysis to design exploratory pattern because of the high performance.