The Use of Sparse Direct Solver in Vector Finite Element Modeling for Calculating Two Dimensional (2-D) Magnetotelluric Responses in Transverse Electric (TE) Mode

The Lembang fault located 15 Km north of Bandung City is one of the active faults situated on Java Island, Indonesia. The Lembang fault is an extension of the Cimandiri fault that can be one of the potential sources of earthquakes in Indonesia. In this study, the Magnetotelluric method was used to model the subsurface resistivity at the Lembang Fault area. The data acquisition was conducted in 8 points of measurement forming a line perpendicular to the Lembang Fault. The analysis was performed using 1D inversion of apparent resistivity and phase with the frequency range of 1 Hz to 320 Hz. The contrast apparent resistivity has observed in two sites around the fault. The inversion results show resistivity contrasts around the LMB02 point that is suspected to be the Lembang Fault. These results are consistent with geological data in the Lembang Fault area. Aside from the LMB02 point, there are also resistivity contrasts around the LMB05 point. However, from a geological perspective, it is not yet known whether the area around the LMB05 point represents a fault.

Section: Magnetotelluric Methodsmentioning

confidence: 99%

Resistivity Distribution of Lembang Fault Based on Magnetotelluric Data

Nurhasan,

Naufal,

Srigutomo

et al. 2024

“…Magnetotelluric is a passive electromagnetic (EM) method that maps subsurface electrical conductivity or resistivity structure by measuring natural variations in electric and magnetic vector fields at the earth's surface [17]- [18]. The magnetotelluric approach's formulation is based on the electrodynamic phenomena described by Maxwell's equations.…”

Section: Magnetotelluric Methods (Mt)mentioning

confidence: 99%

Analysis of Subsurface Resistivity Distribution of the Kelud Volcano Using Magnetotelluric Method

Nurhasan,

Pratama,

Naufal

et al. 2024

Indonesia has the world’s most active volcanoes, with more than 30% of them lying within its borders. The Kelud volcano erupted in 2007, resulting in the development of a Lava Dome in the crater lake. This phenomena is known as effusive. The magnetotelluric approach is used in this study to predict the subsurface resistivity distribution in the Kelud volcano area. Data was obtained at 10 different locations around the Kelud volcano area. The subsurface structure of the Kelud Volcano can be identified based on resistivity values that show significant differences, according to the modelling results. According to the findings, the surface resistivity surrounding the Kelud volcano ranges from 1 to 100 ohm. The main structure of the hydrothermal system’s clay cap was discovered at a depth of 1000 m from the surface in the western part of the summit, with resistivity values ranging from 1-10.m. With a resistivity of more than 100 ohm.m., a high resistivity forming a conduit appears in the centre of the summit area. The subsurface structure values obtained indicate that these structures are volcanic.

“…As a result, iterative solvers were frequently employed to derive an approximate solution. Yet, with the increasing computational capabilities now available, the utilization of direct solvers has become viable (e.g., [19] [20]). Direct solvers assure solution accuracy and are more dependable when dealing with ill-conditioned systems.…”

Section: Implementation In Juliamentioning

confidence: 99%

Two-dimensional magnetotelluric inversion using unstructured triangular mesh implemented in Julia

Diba,

Nurhasan,

Uyeshima

et al. 2024

This study presents a 2-D magnetotelluric inversion code tailored for unstructured triangular meshes, developed using Julia, a high-level, high-performance programming language designed for scientific and numerical computation. The forward modeling engine utilizes a node-based finite element method to solve electromagnetic fields throughout the modeling domain. The inversion process employs the Gauss-Newton optimization algorithm, iteratively updating the model via the minimization of a regularized least-squares objective function. We verified the accuracy of the forward modeling using two reference models and performed a synthetic inversion experiment to validate our inversion method and stress the necessity of accurately handling topography-influenced data. Through its application to constructing an electrical resistivity model beneath the northwestern end of Sumatra Island, Indonesia, we demonstrate the practicality of our code for inverting field datasets.