Thinned coal distribution modeling based on integrated geological and geophysical data: Case study CBM resources in Central Palembang Sub-Basin

Abstract

The main workable coal measures are concentrated at two horizons sediments within the Miocene Muara Enim Formations (MEF). MEF coals are has a proper coal thickness and favorable depth for Coal Bed Methane (CBM) production, and become the main CBM target. Generally, coals are recognized of thin toward the east as they pinch out against the Sunda landmass. Coal presence and lateral coal distribution are the CBM essential elements. The research aim is to identify thin coal reservoir distribution using well and seismic data integration. Reprocessing seismic data before acoustic impedance (AI) inversion produces better results than non-reprocessing. In situations where the wells are located far away from seismic lines, calibration with logs is problematic, and inversion produces less than maximum results. The multi-attribute approach can optimize the results. Integration of the filtering, AI inversion, and then multi-attribute and neural network methods produce the best output to identify coal seams, their distribution, and continuity. The thickest coal, 6 m of thickness, was identified form 11 wells well data at depth 768 m with a total of 5 layers of coal (seam A, B, C, D, and E) in R5. Based on seismic modeling, the seam target was only seamed A with a total volume respectively 518 million m3.