Identification of low resistivity layers in the “N” geothermal field using 2D magnetotelluric inversion modelling

Journal of Physics and Its Applications, 2(2) 2020, Pages: 85-89 Journal of Physics and Its Applications Journal homepage : https://ejournal2.undip.ac.id/index.php/jpa/index Identification of low resistivity layers in the “N” geothermal field using 2D magnetotelluric inversion modeling Nabil1, Udi Harmoko2, Tony Yulianto2, and Irvan Ramadhan3 1 Physics Undergraduate Study Program, Department of Physics, Diponegoro University, Semarang, Indonesia Department of Physics, Diponegoro University, Semarang, Indonesia, 3 Supreme Energy, Jakarta, Indonesia, Semarang, Indonesia 2 ARTICLE INFO Article history: Received : 9 April 2020 Accepted : 11 May 2020 Available online : 10 June 2020 Keywords: Geothermal Cap rock Magnetotelluric 2D inversion Time-series Low resistivity ABSTRACT Magnetotelluric survey in the “N” geothermal field was carried out to map the distribution of resistivity value around the “N” geothermal field. The low resistivity value (2 – 10 ohm.m) which overlying the higher resistivity area beneath, usually represents geothermal system cap rocks. This study began with time-series data robust process processingto generate apparent resistivity and phase data from each MT station. 2D inversion model was constructed by using processed MT EDI Files. The final result of this study is a 2D MT model representing the lateral and vertical distribution of geothermal clay cap. Based on this study, cap rock layer was identified by low resistivity distribution (2 Ω.m - 10 Ω.m), the medium resistivity layer (11 Ω.m - 70 Ω.m) was identified as the transition zone, while high resistivity value (more than 70 Ω.m) represented geothermal reservoir. The existence of a geothermal reservoir around “N” geothermal field was also supported by the occurrence of several manifestations across the area. 1. Introduction The development of technology throughout the world causes the demand for energy continues to increase. Currently, fossil energy reserves as the main energy resources in the world keep depleting. Therefore, alternative energy sources are needed to replace the role of fossil energy sources, one of them is geothermal energy. To extract the geothermal resource, a comprehensive geoscience study consisting of geology, geophysics, and geochemistry was carried out to find potential geothermal fields and to determine the location of exploration drilling wells. The existence of geothermal fluid which has high temperature and high salinity cause resistivity of the rocks as the best geophysical parameter for geothermal exploration [1]. Magnetotelluric (MT) is one of the passive geophysical methods which measures the resistivity of the rocks [2]. Magnetotelluric methods measurements involved electric field fluctuations and natural magnetic fields which were perpendicular to the surface of the earth from a depth of several meters to hundreds of kilometers [3]. Parameters measured in the MT method were natural electromagnetic signals included the earth’s magnetic field (Hx, Hy, and Hz) and the earth’s electric field (Ex and Ey) resulting in resistivity and phase as the parameters that needed to be analyzed [4]. The target of geothermal exploration for convective hydrothermal resources is usually a region composed of faults and fractures filled with thermal fluids and hydrothermal alteration products. The low-resistivity zone produced by the brines and clays capping a geothermal system provided a feature that should be easily detectable by electromagnetic (EM) methods [5]. An important stage of MT interpretation was the elevation map of the base of the conductive (BOC) smectite clay zone corresponding to the top of reservoir (TOR) to determine the drilling point. Areas with low resistivity valuesidentified as cap rock are usually located above the reservoir zone [6]. the base of conductive (BOC) layer (low resistivity value) was collated to construct a BOC map. The trend and thickness of the conductive layer were useful to predict reservoir doming feature, and together with the resistive core, could be used to “draw” the reservoir geometry. These features of low resistivity layer and resistive core could delineate the potential productive area [7]. The cap rock acted as a reservoir cover to prevent the geothermal fluid leak from the reservoir. Cap rock was impermeable or resistant to fluid pressure and it had a low resistivity value or referred to as a conductive layer [8]. Identification of the low resistivity layer at the “N” geothermal field was the main topic of this study because it was one of the important parts of geothermal exploration. 85 2. Methodology The data used in this study were secondary data on magnetotelluric acquisition in the “N” geothermal field in the form of time-domain data equipped with remote reference data and transverse function data. Time-series data were obtained with the Metronix ADU-07e which calculated two orthogonal components of the electric field (Ex and Ey) and three magnetic field components (Hx, Hy, Hz). At each station, bandwidth range starting from 64 Hz up to 64 KHz, data with a bandwidth smaller than 64 Hz was obtained by filtering on a 64 Hz bandwidth to get deeper depth. This research used some software used for data processing, data analysis, and 2D inversion modeling. The software used in this research were Mapros and Geotools. Mapros was used to perform several timeseries data processing where the format *.ats were needed, including eliminating noise by adjusting the value of FFT Length, eliminating data spikes manually, and changing magnetotelluric data in the time domain to a frequency domain with fourier transforms to produce smoother transverse function curves [9]. From this software, a transverse function curve was obtained. Geotools software was used to create profiles, cross power selection processes, and to do 2D inversion modeling. The total measurement station on the “N” geothermal field was 163 stations stretching from north to south and passing through manifestations in the form of fumaroles shown in Fig.1. curves usually had a static shift effect, To eliminate the effect of the static effect on the curve, a static shift correction process was needed which could be carried out by several methods. The static shift correction methods used in this study were the spatial filtering method and TDEM. According to [11] TDEM, data was applied because it was not affected by local conductivity anomalies near the surface, and spatial filteringwas applied by assuming regional effects that presented the actual subsurface conditions that would emerge after averaging. TDEM data only covered some data and the rest was done by spatial filtering methods. In Fig 2. and Fig 3. Show the MT curve that had been done static shift correction with TDEM and spatial filtering method. (a) Fig.1: Survey design and geological map[10] To reduce the static effect on data, the static shift correction process in this study was carried out by spatia (...truncated)