scholarly journals Remote sensing of surface Hydrothermal Alteration, identification of Minerals and Thermal anomalies at Sveifluháls-Krýsuvík high-temperature Geothermal field, SW Iceland

Author(s):  
Lucía Magali Ramírez-González ◽  
Muhammad Aufaristama ◽  
Ingibjörg Jónsdóttir ◽  
Ármann Höskuldsson ◽  
þorvaldur þórðarson ◽  
...  
2021 ◽  
Vol 14 (16) ◽  
Author(s):  
Mehdi Maleki ◽  
Shojaeddin Niroomand ◽  
Ehsan Farahbakhsh ◽  
Soroush Modabberi ◽  
Hossein Ali Tajeddin

Lithos ◽  
2018 ◽  
Vol 322 ◽  
pp. 347-361
Author(s):  
Surendra P. Verma ◽  
Kailasa Pandarinath ◽  
Rajneesh Bhutani ◽  
Jitendra K. Dash

2019 ◽  
Vol 91 ◽  
pp. 260-271
Author(s):  
Kailasa Pandarinath ◽  
Rajasekhariah Shankar ◽  
E. Santoyo ◽  
Shwetha B. Shetty ◽  
America Yosiris García-Soto ◽  
...  

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1631
Author(s):  
Fan ◽  
Pang ◽  
Liao ◽  
Tian ◽  
Hao ◽  
...  

The Ganzi geothermal field, located in the eastern sector of the Himalayan geothermal belt, is full of high-temperature surface manifestations. However, the geothermal potential has not been assessed so far. The hydrochemical and gas isotopic characteristics have been investigated in this study to determine the geochemical processes involved in the formation of the geothermal water. On the basis of δ18O and δD values, the geothermal waters originate from snow and glacier melt water. The water chemistry type is dominated by HCO3-Na, which is mainly derived from water-CO2-silicate interactions, as also indicated by the 87Sr/86Sr ratios (0.714098–0.716888). Based on Cl-enthalpy mixing model, the chloride concentration of the deep geothermal fluid is 37 mg/L, which is lower than that of the existing magmatic heat source area. The estimated reservoir temperature ranges from 180–210 °C. Carbon isotope data demonstrate that the CO2 mainly originates from marine limestone metamorphism, with a fraction of 74–86%. The helium isotope ratio is 0.17–0.39 Ra, indicating that the He mainly comes from atmospheric and crustal sources, and no more than 5% comes from a mantle source. According to this evidence, we propose that there is no magmatic heat source below the Ganzi geothermal field, making it a distinctive type of high-temperature geothermal system on the Tibetan Plateau.


2019 ◽  
Vol 12 (1) ◽  
pp. 105 ◽  
Author(s):  
Seyed Mohammad Bolouki ◽  
Hamid Reza Ramazi ◽  
Abbas Maghsoudi ◽  
Amin Beiranvand Pour ◽  
Ghahraman Sohrabi

Mapping hydrothermal alteration minerals using multispectral remote sensing satellite imagery provides vital information for the exploration of porphyry and epithermal ore mineralizations. The Ahar-Arasbaran region, NW Iran, contains a variety of porphyry, skarn and epithermal ore deposits. Gold mineralization occurs in the form of epithermal veins and veinlets, which is associated with hydrothermal alteration zones. Thus, the identification of hydrothermal alteration zones is one of the key indicators for targeting new prospective zones of epithermal gold mineralization in the Ahar-Arasbaran region. In this study, Landsat Enhanced Thematic Mapper+ (Landsat-7 ETM+), Landsat-8 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing datasets were processed to detect hydrothermal alteration zones associated with epithermal gold mineralization in the Ahar-Arasbaran region. Band ratio techniques and principal component analysis (PCA) were applied on Landsat-7 ETM+ and Landsat-8 data to map hydrothermal alteration zones. Advanced argillic, argillic-phyllic, propylitic and hydrous silica alteration zones were detected and discriminated by implementing band ratio, relative absorption band depth (RBD) and selective PCA to ASTER data. Subsequently, the Bayesian network classifier was used to synthesize the thematic layers of hydrothermal alteration zones. A mineral potential map was generated by the Bayesian network classifier, which shows several new prospective zones of epithermal gold mineralization in the Ahar-Arasbaran region. Besides, comprehensive field surveying and laboratory analysis were conducted to verify the remote sensing results and mineral potential map produced by the Bayesian network classifier. A good rate of agreement with field and laboratory data is achieved for remote sensing results and consequential mineral potential map. It is recommended that the Bayesian network classifier can be broadly used as a valuable model for fusing multi-sensor remote sensing results to generate mineral potential map for reconnaissance stages of epithermal gold exploration in the Ahar-Arasbaran region and other analogous metallogenic provinces around the world.


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