Please use this identifier to cite or link to this item: http://paper.sci.ui.ac.id/jspui/handle/2808.28/424
Title: Coal bed methane properties modeling using improved seismic resolution for estimating gas reserves: A case study of East Kalimantan field, Indonesia
Authors: Haris, Abdul
Imam, Choirul
Berger, Ng Bei
Riyanto, Agus
Keywords: CBM potential
deterministic approach
probabilistic approach
Issue Date: Dec-2017
Publisher: GEOMATE International Society
Series/Report no.: Volume 13;ssue 40
Abstract: Coal bed methane (CBM) potential resources are distributed in many areas of East Kalimantan and are estimated to total about 50 trillion cubic feet (TCF). To estimate more accurately the potential reserves of CBM, sub-surface modeling of CBM properties is required. The objective of this study is to estimate the gas methane reserves by using deterministic and probabilistic approaches, which are based on the identified coal seam distribution. This work is carried out by estimating the gas content parameters (moisture, ash, volatile matter, and fixed carbon), which are derived by empirical approximation from geological and geophysical information. The property modeling of CBM parameters is then distributed, based on the three-dimensional (3D) framework of the identified coal seam distribution. In the well log data, several coal seams can be recognized using the electric log characters, especially the gamma ray, resistivity, and density logs. Coal seams are indicated by a low-density value and high resistivity. In this field, coal seams can be identified at depths ranging from 400 to 1100 m. The gas-in-place (GIP) was estimated in reference to the identified coal seam along the 3D geometrical framework. The results show that based on the probabilistic approach, the GIP ranges between a minimum of 8.9 billion cubic feet (BCF) and a maximum of 493.7 BCF, with a mean of 47.7 BCF, while based on the deterministic approach the GIP is 107.7 BCF.
URI: http://paper.sci.ui.ac.id/jspui/handle/2808.28/424
ISSN: 2186-2982 (Print) 2186-2990 (Online)
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