Falah, Hanif Fajrul (2019) Desain Filter 1D Metode Spectral Decomposition pada Pemodelan 3D Data Gravitasi Bawah Permukaan. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pemodelan struktur bawah permukaan menggunakan data gravitasi memiliki hasil yang tidak unik. Terdapat ambiguitas tinggi yang disebabkan oleh subjektivitas penafsir pada penentuan faktor bentuk. Metode Spectral Decomposition digunakan untuk mendapatkan model yang lebih objektif berdasarkan bentukan spektrum pada suatu kedalaman dengan parameter tertentu. Dengan objektivitas yang tinggi, ambiguitas model dapat diatasi. Penelitian ini bertujuan untuk melakukan desain filter 1D pada metode Spectral Decomposition dalam pemodelan 3D struktur bawah permukaan dari data gravitasi. Penelitian dilakukan dengan memisahkan kandungan bilangan gelombang profil anomali dari sayatan digitasi peta kontur Anomali Gravitasi Bouguer dengan algoritma Fast Fourier Transform (FFT). Kemudian nilai bilangan gelombang dipakai sebagai nilai cutoff frequency untuk membuat desain filter metode Interpolated Finite Impulse Response. Dilakukan konvolusi filter 1D terhadap profil gravitasi, sehingga didapatkan spektrum pada suatu kedalaman yang ditentukan berdasarkan nilai bilangan gelombang. Spektrum divalidasi dengan lokasi hiposenter gempa sebagai indikator struktur bawah permukaan, kemudian dinormalisasi dengan skala λ=1/k. Kemudian spektrum diinterpolasi secara pemodelan geostatistik untuk membuat model peta kontur 2D geometri bawah permukaan, dan dilakukan gridding untuk mendapat model 3D. Pemodelan Anomali Gravitasi Bouguer menggunakan filter ini mampu memberikan petunjuk struktur geologi di antara spektrum pada kedalaman tertentu. Pengaruh filter adalah mengatenuasi komponen frekuensi tinggi, memberikan kompleksitas rendah pada model dalam akibat konten komponen frekuensi yang lebih sedikit.
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Subsurface modelling using gravity data has non unique model result. High ambiguity is resulted by interpreter subjectivity on shape factor parameter determination. Spectral decomposition is a method proposed to reduce subjectivity by achieving objective model based on its frequency components at a certain depth with given parameters. With higher objectivity, model ambiguity can also be mitigated. The purpose of this thesis is to design a suitable 1D filter for Spectral Decomposition on subsurface structure 3D modelling from gravity data. One-dimension profiles -digitized from Bouguer Gravity Anomaly contour map- are decomposed into different wavenumber components using Fast Fourier Transform (FFT). The obtained wavenumber values are used as cutoff frequency value as a parameter for filter designing. Filter design method used in this thesis is Interpolated Finite Impulse Response Method, as it has desired narrowband and linear phase characteristic. Filtering is done by convolution of 1D filter with gravity profiles. The results are profiles at a certain depth given by its corresponding wavenumber. The spectra are validated with earthquake hypocenter locations as indicator for subsurface structure and normalized by a scale of λ=1/k. One-dimension spectra are then interpolated using geostatistical modelling to create 2D subsurface contour map, and then gridded to achieve 3D model. Modelling for Bouguer anomaly using one-dimension filter can give some geological structure insight between spectra at certain depth. One-dimension filter attenuates high frequency components, giving less complex characteristic at lower depth models due to less adequate value of frequency components.
| Item Type: | Thesis (Other) |
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| Uncontrolled Keywords: | Filter, Gravitasi, Spectral Decomposition |
| Subjects: | Q Science Q Science > QC Physics Q Science > QC Physics > QC20.7.F67 Fourier transformations |
| Divisions: | Faculty of Civil, Environmental, and Geo Engineering > Geophysics Engineering > 33201-(S1) Undergraduate Theses |
| Depositing User: | Hanif Fajrul Falah |
| Date Deposited: | 23 Jul 2026 01:07 |
| Last Modified: | 23 Jul 2026 01:07 |
| URI: | http://repository.its.ac.id/id/eprint/64836 |
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