Abstract

Indonesian coal production nowadays has reached 63% of total production, which means this high demand will also produce a lot of data. This high demand needs to be innovated as a new alternative energy based on coal production, Underground Coal Gasification (UCG). The coal in this alternative energy source is used to turn the solid coal into gas. Coal mining data has a lot of variables that might be difficult to process manually. Our automatic system will help the users, especially the geologists, identify which coal seams have the potential to be developed as the UCG. We developed the system using a python-based coding system and required data standardization to ease the built-in code reading and process all the required steps to identify the UCG. We implemented the calculation and characterization regarding the calorific value (ADB), proximate, and ultimate analysis from the provided data to find the needed variables for the UCG analytics system. The automatic system will allow the user to choose the interesting borehole that they want to identify. Our system then shows the initial UCG recommendation layer for the next analysis. From our experiment, our system finally found that at the depth of 260 meters, Borehole MJ02 has the potential as the initial guest of the recommendation layer of the UCG development. Doi: 10.28991/CEJ-SP2021-07-012 Full Text: PDF

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