Structural Geology Identification based on Derivative Analysis Gravity Data in Tangkuban Perahu Mountain

Authors

  • Syamsurijal Rasimeng Geophysics Engineering, Engineering Faculty Universitas Lampung
  • Tectona Putra Epriyan Pratama Geophysics Engineering, Engineering Faculty, Universitas Lampung
  • Rahmat Catur Wibowo Geology Engineering Department, Engineering Faculty Universitas Lampung

DOI:

https://doi.org/10.23960/jesr.v6i1.163

Keywords:

Gravity, structure geology, modeling, tangkuban perahu, geothermal

Abstract

The earth is composed of structures with different rock types, properties, and characteristics and can be known by applying the laws of physics in the form of geophysical methods such as the gravity method. The gravity method is a passive geophysical method that is widely used for geodynamic and exploration studies in estimating fault structures. The aim of this research is to model the subsurface geological structure based on the results of derivative analysis of gravity data related to geothermal prospects. The data used are GGMplus gravity acceleration data and topography (elevation) from each measurement point, totaling 6889. The data was then subjected to several corrections to produce a complete Bouguer anomaly. Then, the next stage is derivative analysis, which is used to obtain a subsurface geological structure model and geothermal prospects for the Tangkuban Perahu area. Based on the correlation between derivative analysis and two-dimensional modeling results, it can be seen that the Tangkuban Perahu geothermal system is controlled by structures in the form of horsts and grabens formed due to Tangkuban Perahu volcanic activity. The Tangkuban Perahu geothermal reservoir prospect is estimated to be at a depth of around 0.6 km – 2.8 km with a density ranging from 2.15 g/cc to 2.45 g/cc, which is estimated to be basalt breccia.

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Published

2024-06-07

How to Cite

[1]
S. Rasimeng, T. P. E. . Pratama, and R. C. Wibowo, “Structural Geology Identification based on Derivative Analysis Gravity Data in Tangkuban Perahu Mountain”, JESRsf, vol. 6, no. 1, Jun. 2024.

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