Amalia, Kharisma (2023) Pemodelan Bawah Permukaan Berdasarkan Analisis Koherensi pada Proses Advance Data Magnetotelurik (MT) Prospek Geotermal Way Selabung. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Hasil akuisisi data MT di lapangan tidak lepas dari noise sehingga perlunya pembobotan data. Pada penelitiaan ini, pembobotan data MT dilakukan pada saat proses robust. Pemrosesan robust menggunakan 3 variasi pembobotan, yaitu, No Weight, Rho Variance dan Ordinary Coherency. Proses tersebut menghasilkan nilai koherensi yang merupakan salah satu parameter untuk meninjau kualitas data MT. Kualitas data MT yang baik menunjukkan nilai koherensi ≥75%. Data dengan nilai koherensi <75% akan diproses dengan menggunakan seleksi crosspower (XPR). Tujuan dari penelitian ini adalah menentukan nilai koherensi yang didapatkan dari pemrosesan robust dan seleksi crosspower (XPR), menganalisis pengaruh nilai koherensi terhadap hasil pemodelan inversi 2D dan interpretasi sistem geothermal Way Selabung berdasarkan hasil pemrosesan terbaik. Hasil pemrosesan robust dan XPR jenis pembobotan Ordinary Coherency memberikan efek peningkatan nilai koherensi rata-rata lebih besar dibandingkan jenis pembobotan Rho Variance. Penampang hasil inversi robust Ordinary Coherency menunjukkan batas-batas kedalaman dugaan caprock, reservoirs, dan heat source yang representatif. Hasil pemrosesan robust terbaik menunjukkan perkiraan heat source ditandai dengan sebaran resistivitas tinggi di sebelah barat daya lokasi penelitian yang tersusun oleh lava basalt kuarter. Perkiraan reservoir ditandai dengan sebaran resistivitas menengah diduga tersusun atas sedimen batu pasir. Perkiraan caprock yang ditandai dengan sebaran resistivitas rendah diduga sebagai satuan batuan Jatuhan Piroklastik Ranau yang tersusun oleh breksi dengan komponen batuapung serta debu vulkanik dan satuan batuan Lava Akarjangkang tersier yang tersusun oleh lava basalt teralterasi.
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MT data acquisition results in the field cannot be separated from noise, so data weighting is needed. In this research, MT data weighting was carried out during the robust process. Robust processing uses 3 weighting variations, namely, No Weight, Rho Variance and Ordinary Coherency. This process produces a coherence value which is one of the parameters for reviewing the quality of MT data. Good MT data quality shows a coherence value of ≥75%. Data with coherence values <75% will be processed using crosspower selection (XPR). The purpose of this study is to determine the coherence value obtained from robust processing and crosspower selection (XPR), to analyze the effect of coherence value on the results of 2D inversion modeling and interpretation of the Way Selabung geothermal system based on the best processing results. The processing results of robust and XPR with the Ordinary Coherency weighting type give the effect of increasing the average coherence value greater than the Rho Variance weighting type. The cross section of the robust Ordinary Coherency inversion results shows the depth limits of the representative predicted caprock, reservoirs, and heat sources. The best robust processing results show presumptiom of heat source characterized by a high resistivity distribution in the southwest of the study site which is composed of quaternary basalt lava. The presumption of reservoir is characterized by an intermediate resistivity distribution thought to be composed of sandstone sediments. Presumption of caprock which is characterized by a low resistivity distribution is suspected as a rock unit of the Ranau Pyroclastic Fall composed of breccia with pumice components and volcanic ash and a tertiary Akarjangkang Lava rock unit composed of altered basalt lava.
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | Koherensi, Pemodelan Inversi 2D, Proses Robust, Coherence, 2D Inversion Modelling, Robust Process |
Subjects: | Q Science Q Science > QE Geology |
Divisions: | Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geophysics Engineering > 33201-(S1) Undergraduate Thesis |
Depositing User: | Kharisma Amalia |
Date Deposited: | 26 Sep 2023 02:02 |
Last Modified: | 26 Sep 2023 02:02 |
URI: | http://repository.its.ac.id/id/eprint/103384 |
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