Sealing capacity of clay-cap units above the Cerro Pabellón hidden geothermal system (northern Chile) derived by soil CO2 flux and temperature measurements

Taussi, Marco; Nisi, Bárbara; Pizarro, Marcela; Morata, Diego; Veloso, Eugenio E.; Volpi, Gianni; Vaselli, Orlando; Renzulli, Alberto

doi:10.1016/j.jvolgeores.2019.07.009

Cited by 18 publications

(9 citation statements)

References 59 publications

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“…In the latter, these two elements were detected in only a few spots. These compositional differences, in particular the low Co and Ni concentrations in chalcopyrite studied here, suggest that the hydrothermal system associated with Cerro Pabellón is possibly linked to a relatively more felsic magmatic source [38,39] than at Reykjanes, as proposed by [37] based on the Co/Ni ratios of pyrite. Therefore, and considering that Co/Ni ratios in chalcopyrite may be indicative of source components of hydrothermal fluids, further analytical studies in different ore-forming environments should be undertaken to complement the existing data [19,[42][43][44].…”

Section: Discussionmentioning

confidence: 53%

“…Cerro Pabellón is an active high-enthalpy geothermal system located in the Pampa Apacheta graben and currently hosts the Cerro Pabellón Geothermal Power Plant (48 MWe), the first of its type in South America. A magmatic, high-temperature heat source has been proposed for Cerro Pabellón, based on petrological, geophysical, and geochemical studies [33][34][35][36][37][38][39]. The geology of the area is characterized by the Apacheta-Aguilucho Volcanic Complex (AAVC), dacitic domes and rhyolitic, and dacitic and andesitic lava flows ( Figure 1B).…”

Section: Geological Overviewmentioning

confidence: 99%

“…The geology of the area is characterized by the Apacheta-Aguilucho Volcanic Complex (AAVC), dacitic domes and rhyolitic, and dacitic and andesitic lava flows ( Figure 1B). More detailed descriptions of the geology of the area can be found in [36][37][38][39].…”

Section: Geological Overviewmentioning

confidence: 99%

“…The geothermal system is capped by a 400-m thick low-resistivity layer, which is detected by magnetotelluric methods [33]. For a comprehensive description of Cerro Pabellón, the reader is referred to [36][37][38], and references therein. [37].…”

Section: Geological Overviewmentioning

confidence: 99%

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Silver-Rich Chalcopyrite from the Active Cerro Pabellón Geothermal System, Northern Chile

et al. 2020

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Active subaerial geothermal systems are regarded as modern analogues of low- to intermediate-sulfidation epithermal Au–Ag deposits, where minor amounts of Cu are mostly present as chalcopyrite. Although trace element data concerning sulfides are scarce in active geothermal systems at convergent settings, studies in several other environments have demonstrated that chalcopyrite is a relevant host of Ag and other trace elements. Here, we focus on the active Cerro Pabellón geothermal system in the Altiplano of northern Chile, where chalcopyrite-bearing samples were retrieved from a 561 m drill core that crosscuts the high-enthalpy geothermal reservoir at depth. A combination of EMPA and LA-ICP-MS data shows that chalcopyrite from Cerro Pabellón is silver-rich (Ag > 1000 ppm) and hosts a wide range of trace elements, most notably Se, Te, Zn, Sb, As, and Ni, which can reach 100 s of ppm. Other elements detected include Co, Pb, Cr, Ga, Ge, Sn, Cd, and Hg but are often present in low concentrations (<100 ppm), whereas Au, Bi, Tl, and In are generally below 1 ppm. Chalcopyrite shows a distinct geochemical signature with depth, with significantly higher Ag concentrations in the shallow sample (494 m) and increasing Cd and In contents towards the bottom of the studied drill core (549 m). These differences in the trace element contents of chalcopyrite are interpreted as related to temperature gradients during the waning stages of boiling at Cerro Pabellón, although further studies are still needed to assess the precise partitioning controls. Our data provide evidence that chalcopyrite may play a relevant role as a scavenger of certain metals and a monitor of fluid changes in hydrothermal systems.

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Section: Discussionmentioning

confidence: 53%

Section: Geological Overviewmentioning

confidence: 99%

Section: Geological Overviewmentioning

confidence: 99%

Section: Geological Overviewmentioning

confidence: 99%

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Silver-Rich Chalcopyrite from the Active Cerro Pabellón Geothermal System, Northern Chile

et al. 2020

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“…Dang [9] reported that an increase in ST will reduce the growth cycle of crops and significantly increase the yield. The ST is also an essential important parameter in a geothermal exploration [10], ground heat exchanger applications [11], thermal energy storage [12], ground source heat pump (GSHP) systems [13], and other geothermal development and utilization applications.…”

Section: Introductionmentioning

confidence: 99%

Modeling Hourly Soil Temperature Using Deep BiLSTM Neural Network

2020

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Soil temperature (ST) plays a key role in the processes and functions of almost all ecosystems, and is also an essential parameter for various applications such as agricultural production, geothermal development, and their utilization. Although numerous machine learning models have been used in the prediction of ST, and good results have been obtained, most of the current studies have focused on daily or monthly ST predictions, while hourly ST predictions are scarce. This paper presents a novel scheme for forecasting the hourly ST using weather forecast data. The method considers the hourly ST prediction to be the superposition of two parts, namely, the daily average ST prediction and the ST amplitude (the difference between the hourly ST and the daily average ST) prediction. According to the results of correlation analysis, we selected nine meteorological parameters and combined two temporal parameters as the input vectors for predicting the daily average ST. For the task of predicting the ST amplitude, seven meteorological parameters and one temporal parameter were selected as the inputs. Two submodels were constructed using a deep bidirectional long short-term memory network (BiLSTM). For the task of hourly ST prediction at five different soil depths at 30 sites, which are located in 5 common climates in the United States, the results showed the method proposed in this paper performs best at all depths for 30 stations (100% of all) for the root mean square error (RMSE), 27 stations (90% of all) for the mean absolute error (MAE), and 30 stations (100% of all) for the coefficient of determination (R2), respectively. Moreover, the method adopted in this study displays a stronger ST prediction ability than the traditional methods under all climate types involved in the experiment, the hourly ST produced by it can be used as a driving parameter for high-resolution biogeochemical models, land surface models and hydrological models and can provide ideas for an analysis of other time series data.

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Phreatic and Hydrothermal Eruptions: From Overlooked to Looking Over

et al. 2022

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Over the last decade, field investigations, laboratory experiments, geophysical exploration and petrological, geochemical and numerical modelling have provided insight into the mechanisms of phreatic and hydrothermal eruptions. These eruptions are driven by sudden flashing of ground- or hydrothermal water to steam and are strongly influenced by the interaction of host rock and hydrothermal system. Aquifers hosted in volcanic edifices, calderas and rift environments can be primed for instability by alteration processes affecting rock permeability and/or strength, while magmatic fluid injection(s), earthquakes or other subtle triggers can promote explosive failure. Gas emission, ground deformation and seismicity may provide short- to medium-term forerunner signals of these eruptions, yet a definition of universal precursors remains a key challenge. Looking forward in the next 10 years, improved warning and hazard assessment will require integration of field and experimental data with models combining case studies, as well as development of new monitoring methods integrated by machine learning approaches.

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Sealing capacity of clay-cap units above the Cerro Pabellón hidden geothermal system (northern Chile) derived by soil CO2 flux and temperature measurements

Cited by 18 publications

References 59 publications

Silver-Rich Chalcopyrite from the Active Cerro Pabellón Geothermal System, Northern Chile

Silver-Rich Chalcopyrite from the Active Cerro Pabellón Geothermal System, Northern Chile

Modeling Hourly Soil Temperature Using Deep BiLSTM Neural Network

Phreatic and Hydrothermal Eruptions: From Overlooked to Looking Over

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