Tiaraningtias Bagus Pertiwi, Yunus Daud, Fikri Fahmi
{"title":"Investigation of Geological Structure Using Magnetotelluric and Gravity Data Optimization on Non Volcanic Geothermal, Bora, Centre of Sulawesi","authors":"Tiaraningtias Bagus Pertiwi, Yunus Daud, Fikri Fahmi","doi":"10.25299/jgeet.2023.8.02-2.13876","DOIUrl":null,"url":null,"abstract":"The existence of geological structures is one of the important parameters in determining the permeability zone in a geothermal system. This research was conducted in a non-volcanic geothermal field, Bora, located in the province of Central Sulawesi, aiming to identify the subsurface features, especially geological structures related to permeability zones by optimizing geophysical data. Magnetotelluric (MT) 3D inversion modelling is some of the latest methods to identify geological structural patterns in geothermal systems. The results of the MT model and analysis its parameters can find variations in the distribution of subsurface resistivity, orientation of the direction of the prospect area, and indications of geological structure zones. The type and geometry of the geological structure associated with the high permeability zone can be complemented by determining the contrast of gravity values and analysis of the maximum First Horizontal Derivative (FHD) and zero of the Second Vertical Derivative (SVD). Based on the analysis of geophysical data, it is possible to identify the permeability zone associated with the main structure, namely the Palu-Koro fault, delineate the geothermal reservoir at a depth of 1500-2000 meters and determine the location of well drilling. To visualize the geothermal system comprehensively, a conceptual model is developed by integrating the geophysical model with geological and geochemical data that are correlated with each other, therefore it can assist in determining the location of production well development.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JGEET Journal of Geoscience Engineering Environment and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25299/jgeet.2023.8.02-2.13876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The existence of geological structures is one of the important parameters in determining the permeability zone in a geothermal system. This research was conducted in a non-volcanic geothermal field, Bora, located in the province of Central Sulawesi, aiming to identify the subsurface features, especially geological structures related to permeability zones by optimizing geophysical data. Magnetotelluric (MT) 3D inversion modelling is some of the latest methods to identify geological structural patterns in geothermal systems. The results of the MT model and analysis its parameters can find variations in the distribution of subsurface resistivity, orientation of the direction of the prospect area, and indications of geological structure zones. The type and geometry of the geological structure associated with the high permeability zone can be complemented by determining the contrast of gravity values and analysis of the maximum First Horizontal Derivative (FHD) and zero of the Second Vertical Derivative (SVD). Based on the analysis of geophysical data, it is possible to identify the permeability zone associated with the main structure, namely the Palu-Koro fault, delineate the geothermal reservoir at a depth of 1500-2000 meters and determine the location of well drilling. To visualize the geothermal system comprehensively, a conceptual model is developed by integrating the geophysical model with geological and geochemical data that are correlated with each other, therefore it can assist in determining the location of production well development.