GIS integration model for geothermal exploration and well siting

Noorollahi, Younes; Itoi, Ryuichi; Fujii, Hikari; Tanaka, Toshiaki

doi:10.1016/j.geothermics.2007.12.001

Cited by 96 publications

(50 citation statements)

References 3 publications

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“…Geothermal energy exploration requires the combination of several survey and investigation results (such as geological, geophysical, and geochemical) to determine the most prospect area for further development. The GIS overlay Boolean and overlay weighted techniques were used to map the best prospect areas for geothermal energy and well sitting in many countries such as Iran [3], Japan [4], [5], Turkey [6] and Mexico [7].…”

Section: Introductionmentioning

confidence: 99%

Prospect Area Mapping for Geothermal Energy Exploration in Afghanistan

Anwarzai¹,

Nagasa²

2017

JOCET

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Abstract-One of the cleanest energy sources is geothermal. To generate electricity or to directly use as heat this sustainable resource proper investigation of reservoir characteristics is required. The purpose of this research is to determine the best prospect location of geothermal reservoirs for further investigation in Afghanistan. To achieve this goal, the geological, geophysical, and geochemical evidence maps (such as volcanic dome and rock, fault, high temperature, intrusive rock, geopressured, hot spring, and hydrothermal mineral areas) were created in GIS (Geographical Information System) ArcMap 10.1. The GIS geoprocessing tools (such as buffer, union, and intersection) were used to define the best prospect areas of geothermal energy resources. The result of this study is the first digital map of prospect areas for geothermal resources in Afghanistan. Besides known hot springs, it has determined the wide potential areas around the load centers and big cities of the country.

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Section: Introductionmentioning

confidence: 99%

Prospect Area Mapping for Geothermal Energy Exploration in Afghanistan

Anwarzai¹,

Nagasa²

2017

JOCET

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“…Fry analysis [41] has appeared in scholars' studies like those by Noorollahi, Moghaddam, and Wibowo [2][3][4], but it was used only to show the distribution trend of objects or as an auxiliary tool for spatial analysis. Since the distribution of hot springs can be determined by the Fry angle rose diagram, the distribution trend of hot springs can also be expressed by the Fry method.…”

Section: Hot Spring Data Processing By the Fry Methodsmentioning

confidence: 99%

“…Scientists from all over the world have done a lot of research in this field. Noorollahi et al [2] used the geological and geomorphological data of northwest Sabalan, drawing a rose diagram of the fault strikes. The multiple-criteria decision-making method is used to calculate favorable positions for geothermal resources exploitation and drilling.…”

Section: Introductionmentioning

confidence: 99%

A Novel Workflow for Geothermal Prospectively Mapping Weights-of-Evidence in Liaoning Province, Northeast China

Sang

Liu

et al. 2017

Energies

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Geological faults are highly developed in the eastern Liaoning Province in China, where Mesozoic granitic intrusions and Archean and Paleoproterozoic metamorphic rocks are widely distributed. Although the heat flow value in eastern Liaoning Province is generally low, the hot springs are very developed. It is obvious that the faults have significant control over the distribution of hot springs, and traditional methods of spatial data analysis such as WofE (weight of evidence) usually do not take into account the direction of the distribution of geothermal resources in the geothermal forecast process, which seriously affects the accuracy of the prediction results. To overcome the deficiency of the traditional evidence weight method, wherein it does not take the direction of evidence factor into account, this study put forward a combination of the Fry and WofE methods, Fry-WofE, based on geological observation, gravity, remote sensing, and DEM (digital elevation model) multivariate data. This study takes eastern Liaoning Province in China as an example, and the geothermal prospect was predicted respectively by the Fry-WofE and WofE methods from the statistical data on the spatial distribution of the exposed space of geothermal anomalies the surface. The result shows that the Fry-WofE method can achieve better prediction results when comparing the accuracy of these two methods. Based on the results of Fry-WofE prediction and water system extraction, 13 favorable geothermal prospect areas are delineated in eastern Liaoning Province. The Fry-WofE method is effective in study areas where the geothermal distribution area is obviously controlled by the fault. We provide not only a new method for solving the similar issue of geothermal exploration, but also a new insight into the distribution of geothermal resources in Liaoning Province.

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“…The decision making process involved in locating prospective areas, recommended for further study or exploratory drilling, demands to combine, integrate and interpret the results of geological, geochemical, geophysical and other surveys (Noorollahi, et al, 2008). GIS models have been successfully used in performing these tasks.…”

Section: Data Integration For Targeting Promising Areas and Well Sitesmentioning

confidence: 99%

“…The Boolean method proved to be more restrictive and therefore more dependable for exploration well siting. Noorollahi et al (2008) introduce the results of an environmental suitability analysis (e.g. land cover, residential areas,…) to select the most promising well sites.…”

Section: Data Integration For Targeting Promising Areas and Well Sitesmentioning

confidence: 99%

Methods and tools to evaluate the availability of renewable energy sources

Angelis-Dimakis

Biberacher

Bravo

et al. 2011

Renewable and Sustainable Energy Reviews

349

132

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The recent statements of both the European Union and the US Presidency pushed in the direction of using renewable forms of energy, in order to act against climate changes induced by the growing concentration of carbon dioxide in the atmosphere. In this paper, a survey regarding methods and tools presently available to determine potential and exploitable energy in the most important renewable sectors (i.e., solar, wind, wave, biomass and geothermal energy) is presented. Moreover, challenges for each renewable resource are highlighted as well as the available tools that can help in evaluating the use of a mix of different sources.

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GIS integration model for geothermal exploration and well siting

Cited by 96 publications

References 3 publications

Prospect Area Mapping for Geothermal Energy Exploration in Afghanistan

Prospect Area Mapping for Geothermal Energy Exploration in Afghanistan

A Novel Workflow for Geothermal Prospectively Mapping Weights-of-Evidence in Liaoning Province, Northeast China

Methods and tools to evaluate the availability of renewable energy sources

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