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The effect of geological uncertainty on the development and mining of underground coal deposits is a key issue for longwall mining, as the presence of faults generates substantial monetary losses. This paper develops a method for the conditional simulation of fault systems and uses the method to quantify and assess fault uncertainty. The method is based on the statistical modelling of fault attributes and the simulation of the locations of the centres of the fault traces. Fault locations are generated from the thinning of a Poisson process using a spatially correlated probability field. The proposed algorithm for simulating fault traces takes into account soft data such as geological interpretations and geomechanical data. The simulations generate realisations of fault populations that reproduce observed faults, honour the statistics of the fault attributes, and respect the constraints of soft data, providing the means to thereby model and assess the related fault uncertainty.
The effect of geological uncertainty on the development and mining of underground coal deposits is a key issue for longwall mining, as the presence of faults which produce substantially monetary losses. This paper develops a method for the conditional simulation of fault systems and uses the method to quantify The assessors are based on the statistical modeling of fault attributes and the simulation of the locations of the centers of the fault traces. Fault locations are generated from the thinning of a Poisson process using a spatially correlated probability field. algorithm for simulating fault traces takes into account soft data such as geological interpretations and geomechanical data. The simulations generate realizations of fault populations that reproduce observed faults, honoring the statistics of the fault attributes, and respect the constraints of soft data, providing the means to so model and assess the related fault uncertainty.