Praditiyo Riyadi
Syarif Hidayatullah State Islamic University of Jakarta, Indonesia

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2D Joint Inversion of Gravity and Magnetic Data to Evaluate a Geological Structure in Tanimbar Island Arkanu Andaru; Praditiyo Riyadi; Muhammad Nafian
Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics AL-FIZIYA JOURNAL OF MATERIALS SCIENCE, GEOPHYSICS, INSTRUMENTATION AND THEORETICAL PHYSICS VOL.6, N
Publisher : Physics Study Programme, Faculty of Science and Technology UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/fiziya.v6iI.34293

Abstract

The need for hydrocarbon energy, especially oil and gas, requires continuous exploration of hydrocarbon reserves, especially in eastern Indonesia. Tanimbar Islands, Maluku was chosen to be the research area because of its complex subsurface geology and is located on the fold thrust belt resulting from tectonic evolution. In this research, an innovation is carried out using joint inversion modeling by correlating physical parameters from two different geophysical data, which are gravity and geomagnetic. The purpose of this research is to determine the subsurface mapping of the research area, determine the density and susceptibility values of rocks, and determine the structural patterns that exist in the subsurface. The results of subsurface mapping of the Tanimbar Islands based on the results of Joint Inversion modelling have found a geological structure pattern in the form of a fold thrust belt due to the Banda Arc subduction zone. In section A-A', there is a sequence of fold thrust belt with 10 structural patterns, including 6 structures in the northwest-southeast direction and 4 structures in the northeast-southwest direction. In section B-B' there are 9 structural patterns in the northeast-southwest direction. High anomalies obtained density values ranging from 2.77 - 2.81 gr/cm3 and susceptibility ranging from 0.00125 - 0.0013 SI are thought to be caused by high basement in the form of volcanic rocks, while low anomalies obtained density values ranging from 2.45 - 2.49 gr/cm3 and susceptibility ranging from 0.0008 - 0.00085 SI are thought to be caused by thick sedimentary layers of the Batimafudi Formation.
EVALUATION OF COAL DISTRIBUTION FOR ALTERNATIVE ENERGY USING SEISMIC SPECTRAL DECOMPOSITION Praditiyo Riyadi
Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics AL-FIZIYA JOURNAL OF MATERIALS SCIENCE, GEOPHYSICS, INSTRUMENTATION AND THEORETICAL PHYSICS VOL.5, N
Publisher : Physics Study Programme, Faculty of Science and Technology UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/fiziya.v5i1.26670

Abstract

Indonesia is the largest coal producer in the world, and Sumatera is one of the contributors to Indonesia's coal production. Coal is generally widely used for industrial fuel or power plants with production directly on the surface. The technology to develop coal into alternative energy sources (Coal Bed Methane (CBM) & Underground Coal Gasification (UCG)) began to develop with various production methods in the earth without having to be exploited directly. To apply this production method, it is necessary to analyze the distribution of coal below the earth's surface. The research area is located in the South Sumatera Basin with coal targets in the Muara Enim Formation. The data consists of 3D seismic data and well data as validation. From the well data, it was identified that there was coal in two zones, with an average thickness in Zone A reaching 6 meters while in Zone B the average thickness reaching 11 meters. The results of the amplitude spectrum analysis from the seismic data, obtained three dominant frequency trends from seismic data, 26 Hz, 42 Hz, and 58 Hz. By using the calculation of ΒΌ wavelength, the frequency that matches the thickness of the coal is 58 Hz for Zone A and 42 Hz for Zone B coal layer. Seismic amplitudes are then separated based on their frequency using the Spectral Decomposition method, and the distribution of coal is validated with existing well data.