Abstract. The geophysical exploration method is the superior over the project area due to the dense of vegetation and thick soil so very limited geological outcrops. Contrast of physical properties of every different rock type should be able to be distinguished by the geophysical data. Fuzzy logic approach and weight of evidence were used for geophysical data modeling. Posterior probability was used to calculate the weight of evidence (WofE) of every fuzzy map memberships. By combining each rock type model, the model provides better result compared from the model from mixed rock type on the data training. This method is able to eliminate the potential interference of different geophysical signature. So that, the understanding the geological feature of the area is key success for the mineral prosperity modeling. We verified the model by site visiting and drilling and it is estimated about 90% confident.
Mud rushes, or wet muck spills, are hydro-geotechnical challenges in block cave mines where wet muck spills out of drawpoints formed by the accumulation of fine materials and water in drawbells. The purpose of this paper is to share the results of the developement of an improved predictive tool that can be used to manage wet muck spills. The tool was developed based on the hybrid modeling of wet muck distribution using fuzzy logic and fuzzy number operations. The fuzzy logic operations were applied to model the spatial distribution of wet muck classes, providing the spatial model of drawpoint status based on five contributing factors, i.e. the height of draw, the water content, the grain size of the fine material, rainfall, and no-mucking days. The fuzzy number operations were used in accordance with the mass balance principle to estimate the temporal distribution of wet muck that forms a mud deposit consisting of fine materials and water in a drawbell. The mass balance principle was expressed using the fuzzy ordinary differential equation, including the uncertainty of joining variables. A wet muck spill event at the Deep Ore Zone (DOZ) block cave mine of PT Freeport Indonesia was utilized as a case study as well as to validate the proposed method. The fuzzy-based approach shows promising results in predicting wet muck spill events.
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