PSEUDO PROXIMATE ANALYSIS USING CONVENTIONAL WIRELINE LOG DATA IN MUARAENIM COAL-BEARING FORMATION, OGAN KOMERING AREA, SOUTH PALEMBANG SUB-BASIN, SOUTH SUMATRA BASIN

• Main Author: PROBO ANANTO NIM: 22013027, WAHYU
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/31541
• Institution: Institut Teknologi Bandung

<p align="justify">Indonesia has great potential of unconventional hydrocarbon resources such as coal bed methane with total resources number around 453 TCF. The largest portion of that number are in South Sumatra Basin (183 TCF). South Sumatra Basin has two coal-bearing formations, Talangakar Formation and Muaraenim Formation, the latter is one of the largest coal producer in Indonesia. The quantity of coal bed methane in coal seams is influenced by the quality of coal which became its reservoir. One method to determining the quality of coal is proximate analysis. It is a fundamental analysis on coal in order to determine fixed carbon value, volatile matter content, ash content and moisture content. Unfortunately not all of the coal seam has proximate analysis and sometimes the analysis is performed one time only in one thick coal seam. Limitations of vertical resolution and limited well data which has proximate value became one of the purposes of this study. Proximate value estimation generally performed by using density log data only. However, there are recent developments with the inclusion of the gamma ray log and neutron log on proximate value estimation process known as Pseudo Proximate Analysis method. This study attempted to examine the reliability of that method in low rank coal of Muaraenim Formation. <br /> Methodology of data processing and analysis in this study include the identification of coal seams, coal type and quality (rank) analysis, depositional environment analysis, relationship analysis between proximate value and wireline logs data, proximate analysis estimation in coal seams and wells without availability of proximate analysis, and the final mathematical model of pseudo proximate analysis, as well as the characterization of each layer of coal seam based on estimated proximate and its relation to the depositional environment and coal rank. Procedures in this study consist of several stages of common and exceptional methods in coal study. The procedure which exceptionally performed is the use of graphic clustering method with principle of multivariate analysis using gamma ray log, density log, and neutron log in the determination of lithology and the top-bottom picking of coal seam, also the use of gamma ray log, density log, and neutron log simultaneously in estimating the value of proximate. The use of graphic clustering method with the principles of multivariate analysis <br /> combined with conventional top-bottom picking of coal seam using cutting data is expected to produce more precise coal seam position. Meanwhile, the use of gamma ray log, density log, and neutron log simultaneously in proximate value estimation is expected to be more represent coal matrix concept, dual porosity concept on coal, and the presence of coal bed methane in coal seams. <br /> Data availability and analyzes that have been performed in this study shows that the Muaraenim coal-bearing formation in the study area has coal ranking ranging from lignite to sub-bituminous. Muaraenim coal-bearing formation is deposited on littoral (lower part of Muaraenim Formation) until supralitoral (upper part of Muaraenim Formation). Therefore, coal seam that is deposited on littoral zone will be associated with lower delta plain (interdistributary swamp-marsh) deposits and/or coastal marshes (tidal flat), while coal seam that is deposited on supralitoral zone will be associated with upper delta plain - alluvial plain (backswamp - overbank) deposits. <br /> Qualitative observations on gamma ray log data indicates that this log can distinguish coal population, sandstone population, and claystone population according to gamma ray range value. Meanwhile, density and neutron log only able to distinguish coal and non-coal population. According to principle of gamma ray log, this log is used in ash content determination, while the density log is used in determining fixed carbon content and ash content, while the neutron log is used in determining the fixed carbon content, volatile matter content, and moisture content. To estimate the proximate value, the composition of the coal matrix can be simplified into fixed carbon, clay, quartz, and pore volume which filled by volatile matter and water. <br /> Proximate estimation equations require modification in determination of neutron hydrogen index with direct neutron use as indicator. Estimation result of fixed carbon and volatile matter needs to be corrected because there is a difference with proximate laboratory result. Correction of the estimated value of volatile matter conducted by a factor of 0.6. This factor obtained from discrepancy between equation of the line before correction with equation of the theoretical line. Discrepancy between estimated value of corrected volatile matter with the estimated value of volatile matter before the correction was used as a deduction to get the estimation of fixed carbon content. Coal characterization result indicate that the middle - upper part of M2 coal seam group (Suban - Mangus Seam) and lower part of M3 coal seam group (Burung) has better quality than other coal seams in the area of research. <br /> <p align="justify">