Assessing the geothermal potential of the Shahin Dezh Region, based on the geological, geochemical and geophysical evidence

Ebrahimi, Davar; Nouraliee, Javad; Dashti, Ali

doi:10.1016/j.jafrearsci.2019.02.005

Cited by 11 publications

(6 citation statements)

References 31 publications

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“…The classification results are evaluated by means of the overall accuracy, Cohen's Kappa index, and the receiving operating characteristic (ROC) curve area. The area under the ROC curve (AUC) provides a comparison between the predicted and actual instance values in a classification by measuring the precision and the recall [56]. The RF classification for the cross-validation achieved a Kappa index of 88.4%, an overall accuracy of 94.0% and an AUC equal to 98.7%.…”

Section: Resultsmentioning

confidence: 99%

Detection of Geothermal Potential Zones Using Remote Sensing Techniques

González¹,

Rodríguez‐Gonzálvez²

2019

Remote Sensing

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The transition towards a new sustainable energy model-replacing fossil fuels with renewable sources-presents a multidisciplinary challenge. One of the major decarbonization issues is the question of to optimize energy transport networks for renewable energy sources. Within the range of renewable energies, the location and evaluation of geothermal energy is associated with costly processes, such as drilling, which limit its use. Therefore, the present research is aimed at applying different geomatic techniques for the detection of geothermal resources. The workflow is based on free/open access geospatial data. More specifically, remote sensing information (Sentinel-2A and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)), geological information, distribution of gravimetric anomalies, and geographic information systems have been used to detect areas of shallow geothermal potential in the northwest of the province of Orense, Spain. Due to the variety of parameters involved, and the complexity of the classification, a random forest classifier was employed, since this algorithm works well with large sets of data and can be used with categorical and numerical data. The results obtained allowed identifying a susceptible area to be operated on with a geothermal potential of 80 W·m −1 or higher.2 of 20 drilling operations. For this reason, different researchers have tried to develop methodologies to reduce costs in the search for these areas, taking into great consideration the use of remote sensing as a means to prioritize zones of potential geothermal energy [8,9], due to the availability of free satellite imagery and its cost-effective ratio for the geothermal exploration of large areas. One approach that involves remote sensing is the search for areas of rocks altered by hydrological action using images from one or more sensors, since they are indicative of thermal fluids being discharged along faults [10]. Surface thermal properties are an indicator of geothermal resources, which can be measured by the use of images from thermal sensors [11,12]. Additionally, temperatures can also be obtained using multispectral imagery [13] acquiring land surface temperature (LST) values.Among the geomatic techniques, geographic information systems (GIS) offer a whole new dimensionality by combining the remote sensing data with other geographic information sources as in [14], in which gravimetric anomalies, thermal images, and the location of geological faults were employed. Among the available GIS techniques, the use of random forest classifiers stands out, since they allow the ability to extract information from categorical and numerical variables. As a result, they support the decision-taking process without significant computational requirements. These algorithms are popular among the scientific community due to its ease of use and being able to be applied in multiple fields as in the case of [15], in which they were used to obtain a model of the demand of electricity. Another transversal example is the app...

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Section: Resultsmentioning

confidence: 99%

Detection of Geothermal Potential Zones Using Remote Sensing Techniques

González¹,

Rodríguez‐Gonzálvez²

2019

Remote Sensing

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“…Mahallat is also another possible geothermal site located in the Markazi Province of Iran. Three negative gravity anomaly zones and faults (acting as preferential pathways for hydrothermal fluids circulation) are confirmed in this area [21][22][23][24][25][26][27][28][29] . Published documents mainly presented all interpretations on the Mahalat geothermal region merely based on the geophysical data.…”

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confidence: 88%

“…Installation of the first Iranian geothermal power plant at the Sabalan Field (northwest of Iran) is the result of some country-wide exploration projects. In addition, further detailed geothermal exploration studies have been carried out in different parts of Iran [17][18][19][20][21][22][23][24][25]26 .Mahallat is also another possible geothermal site located in the Markazi Province of Iran. Three negative gravity anomaly zones and faults (acting as preferential pathways for hydrothermal fluids circulation) are confirmed in this area [21][22][23][24][25][26][27][28][29] .…”

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confidence: 99%

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Appraising Mahallat Geothermal Region using thermal surveying data accompanied by the geological, geochemical and gravity analyses

Nouraliee

Ebrahimi

Dashti

et al. 2021

Sci Rep

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Mahallat Geothermal Region, located in the central part of Iran, is known as one of the largest low-temperature geothermal fields. In this study, Mahallat geothermal resource has been evaluated based on integrated geological, geochemical and geophysical analyses. Gravity data revealed three major negative anomaly zones. Based on the geochemical analyses, quartz geothermometers are more reliable than others and confirmed that the reservoir is about 90 °C. Lithological properties of Jurassic layers and high sulphate content observed in geochemical data showed traces of the coal-rich layers on the hot fluids. Measured temperatures in 7 boreholes with the depths ranging from 50 to 100 m, have proposed that expected geothermal gradient will be about 81.5 °C/km. Among all drilled boreholes, the data coming from only one resulted in this almost reliable gradient. Other boreholes are clearly too shallow or affected by upflow or downflow of water along existing faults. Geological, geochemical, gravity and measurements of drilled boreholes suggested the existence of a shallow reservoir with an approximate temperature of 90 °C. Regarding gravity and observed faults, geothermal reservoir is elongated parallel to one of the main faults of the region with NE-SW strike.

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“…190 In geological survey, features like faults, rock units, alteration zones, geothermal springs, travertine outcrops, mud volcanoes, fumaroles, steam-heated lakes, geysers, and mud pots are the main studied phenomena. 191 In ref. [197], the results of 3D geologic analyses of two geothermal systems in the Basin and Range, USA were presented.…”

Section: Geothermal Energymentioning

confidence: 99%

Renewable Energy for Robots and Robots for Renewable Energy – A Review

Hassan¹,

Habrouk²,

Deghedie³

2019

Robotica

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SUMMARY Fossil fuel sources are well suited to fulfill the energy needs of human beings. Unfortunately, there are some limitations and disadvantages pertaining to fossil fuels, some of which are drastic. The main issues are: firstly, there is a finite supply of these fuels, eventually this supply will be exhausted; secondly, burning fossil fuels contributes to global warming, leading to disastrous consequences for the environment and the health of humans. Switching to renewable energy sources is the viable solution to the aforementioned issues. Robots bring numerous benefits in a wide variety of applications. Introducing robots to production environments and other applications results in a remarkable improvement in terms of productivity and efficiency. In this paper, the integration between robots and renewable energy sources is discussed. In other words, two main points are investigated: (1) how can renewable energy be a viable source of energy for robots and (2) how can the renewable energy industry benefit from utilizing robots in the execution of renewable energy-related tasks. Some of the recent developments concerning the integration between robots and renewable energy are reviewed. In addition, more opportunities and expected advancements are also discussed.

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Assessing the geothermal potential of the Shahin Dezh Region, based on the geological, geochemical and geophysical evidence

Cited by 11 publications

References 31 publications

Detection of Geothermal Potential Zones Using Remote Sensing Techniques

Detection of Geothermal Potential Zones Using Remote Sensing Techniques

Appraising Mahallat Geothermal Region using thermal surveying data accompanied by the geological, geochemical and gravity analyses

Renewable Energy for Robots and Robots for Renewable Energy – A Review

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