Geostatistical analysis on the spatial variation of radiogenic elements in the crystalline basement of Grenville Province in the southwestern Québec
Accurate assessment of deep geothermal resources remains a challenge from the practical point of view. Parameter uncertainties and partial knowledge of initial conditions limit the prediction of subsurface temperatures using a variety of thermal models strongly unreliable, and the temperature is hig...
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description | Accurate assessment of deep geothermal resources remains a challenge from the practical point of view. Parameter uncertainties and partial knowledge of initial conditions limit the prediction of subsurface temperatures using a variety of thermal models strongly unreliable, and the temperature is highly dependent on the radiogenic heat production in the geological layers mainly affected by a number of factors including the concentrations of uranium, thorium and potassium, and rock density. In this paper, geostatistical methods were applied to investigate the spatial distribution of radiogenic elements (e.g., uranium, thorium, potassium) and their corresponding concentrations and radiogenic heat production. A representative region measuring 35 km × 80 km in the southwestern Québec, and covering the domains of Portneuf-Mauricie, Morin Terrane and Parc des Laurentides in the Grenville Province was selected for this study because of its easy accessibility. Analysis results show that the concentrations of uranium, thorium and potassium for most rocks of the Grenville basement in the research region are in the range of 1–2 ppm, 3–10 ppm and 1–4%, respectively. Furthermore, 90% of the total samples analysed in this study show a uranium concentration of less than 3 ppm, 64% of the samples show a thorium concentration of less than 5 ppm, and 56% of the samples show a potassium concentration of less than 3%. This paper engaged both the ordinary kriging interpolation and sequential Gaussian simulation (SGS) methods to study the spatial distribution of radiogenic elements. Using density data for specific rocks, the distribution of radiogenic heat production in the study area of the southwestern Grenville Province was also simulated using the SGS method. Conclusively, results show that the difference between the minimum and the maximum value of radiogenic heat production is 30%, considering a significant proportion of heterogeneity in rock density. |
doi_str_mv | 10.1007/s12665-018-7917-1 |
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Parameter uncertainties and partial knowledge of initial conditions limit the prediction of subsurface temperatures using a variety of thermal models strongly unreliable, and the temperature is highly dependent on the radiogenic heat production in the geological layers mainly affected by a number of factors including the concentrations of uranium, thorium and potassium, and rock density. In this paper, geostatistical methods were applied to investigate the spatial distribution of radiogenic elements (e.g., uranium, thorium, potassium) and their corresponding concentrations and radiogenic heat production. A representative region measuring 35 km × 80 km in the southwestern Québec, and covering the domains of Portneuf-Mauricie, Morin Terrane and Parc des Laurentides in the Grenville Province was selected for this study because of its easy accessibility. Analysis results show that the concentrations of uranium, thorium and potassium for most rocks of the Grenville basement in the research region are in the range of 1–2 ppm, 3–10 ppm and 1–4%, respectively. Furthermore, 90% of the total samples analysed in this study show a uranium concentration of less than 3 ppm, 64% of the samples show a thorium concentration of less than 5 ppm, and 56% of the samples show a potassium concentration of less than 3%. This paper engaged both the ordinary kriging interpolation and sequential Gaussian simulation (SGS) methods to study the spatial distribution of radiogenic elements. Using density data for specific rocks, the distribution of radiogenic heat production in the study area of the southwestern Grenville Province was also simulated using the SGS method. Conclusively, results show that the difference between the minimum and the maximum value of radiogenic heat production is 30%, considering a significant proportion of heterogeneity in rock density.</description><identifier>ISSN: 1866-6280</identifier><identifier>EISSN: 1866-6299</identifier><identifier>DOI: 10.1007/s12665-018-7917-1</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Biogeosciences ; Computer simulation ; Density ; Distribution ; Domains ; Earth and Environmental Science ; Earth Sciences ; Environmental Science and Engineering ; Geochemistry ; Geology ; Geostatistics ; Geothermal resources ; Heat ; Heterogeneity ; Hydrology/Water Resources ; Initial conditions ; Interpolation ; Kriging interpolation ; Mathematical models ; Normal distribution ; Original Article ; Parameter uncertainty ; Potassium ; Rock ; Rocks ; Spatial analysis ; Spatial distribution ; Spatial variations ; Statistical methods ; Subsurface temperatures ; Temperature dependence ; Terrestrial Pollution ; Thermal analysis ; Thermal models ; Thorium ; Uranium</subject><ispartof>Environmental earth sciences, 2018-11, Vol.77 (21), p.1-12, Article 731</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><rights>Environmental Earth Sciences is a copyright of Springer, (2018). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a291t-22c49c262f709130db98890594aebe9c37e9ea52016b6a067eb0f7086c2298173</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12665-018-7917-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12665-018-7917-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Liu, Hejuan</creatorcontrib><creatorcontrib>Were, Patrick</creatorcontrib><title>Geostatistical analysis on the spatial variation of radiogenic elements in the crystalline basement of Grenville Province in the southwestern Québec</title><title>Environmental earth sciences</title><addtitle>Environ Earth Sci</addtitle><description>Accurate assessment of deep geothermal resources remains a challenge from the practical point of view. Parameter uncertainties and partial knowledge of initial conditions limit the prediction of subsurface temperatures using a variety of thermal models strongly unreliable, and the temperature is highly dependent on the radiogenic heat production in the geological layers mainly affected by a number of factors including the concentrations of uranium, thorium and potassium, and rock density. In this paper, geostatistical methods were applied to investigate the spatial distribution of radiogenic elements (e.g., uranium, thorium, potassium) and their corresponding concentrations and radiogenic heat production. A representative region measuring 35 km × 80 km in the southwestern Québec, and covering the domains of Portneuf-Mauricie, Morin Terrane and Parc des Laurentides in the Grenville Province was selected for this study because of its easy accessibility. Analysis results show that the concentrations of uranium, thorium and potassium for most rocks of the Grenville basement in the research region are in the range of 1–2 ppm, 3–10 ppm and 1–4%, respectively. Furthermore, 90% of the total samples analysed in this study show a uranium concentration of less than 3 ppm, 64% of the samples show a thorium concentration of less than 5 ppm, and 56% of the samples show a potassium concentration of less than 3%. This paper engaged both the ordinary kriging interpolation and sequential Gaussian simulation (SGS) methods to study the spatial distribution of radiogenic elements. Using density data for specific rocks, the distribution of radiogenic heat production in the study area of the southwestern Grenville Province was also simulated using the SGS method. Conclusively, results show that the difference between the minimum and the maximum value of radiogenic heat production is 30%, considering a significant proportion of heterogeneity in rock density.</description><subject>Biogeosciences</subject><subject>Computer simulation</subject><subject>Density</subject><subject>Distribution</subject><subject>Domains</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environmental Science and Engineering</subject><subject>Geochemistry</subject><subject>Geology</subject><subject>Geostatistics</subject><subject>Geothermal resources</subject><subject>Heat</subject><subject>Heterogeneity</subject><subject>Hydrology/Water Resources</subject><subject>Initial conditions</subject><subject>Interpolation</subject><subject>Kriging interpolation</subject><subject>Mathematical models</subject><subject>Normal distribution</subject><subject>Original Article</subject><subject>Parameter uncertainty</subject><subject>Potassium</subject><subject>Rock</subject><subject>Rocks</subject><subject>Spatial analysis</subject><subject>Spatial distribution</subject><subject>Spatial variations</subject><subject>Statistical methods</subject><subject>Subsurface temperatures</subject><subject>Temperature dependence</subject><subject>Terrestrial Pollution</subject><subject>Thermal analysis</subject><subject>Thermal models</subject><subject>Thorium</subject><subject>Uranium</subject><issn>1866-6280</issn><issn>1866-6299</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kc9KAzEQxoMoWGofwFvA82qSbbObo4hWoaCCnkM2nW1TtknNbCt9EB_C5_DFzLr-OZlLhpnv9zHMR8gpZ-ecseICuZBykjFeZoXiRcYPyICXUmZSKHX4W5fsmIwQVyy9nOeKyQF5m0LA1rQOW2dNQ403zR4d0uBpuwSKmzRL_Z2JLlWpG2oazdyFBXhnKTSwBt8idb3exn2yaxrngVYGv4YdMo3gd65pgD7EsHPewg-BYdsuXwFbiJ4-bj_eK7An5Kg2DcLo-x-S55vrp6vbbHY_vbu6nGVGKN5mQtixskKKumCK52xeqbJUbKLGBipQNi9AgZkIxmUlDZMFVCxJS2mFUCUv8iE56303Mbxs0w56FbYxnQC14KLgZa7SoYaE9yobA2KEWm-iW5u415zpLgDdB6BTALoLQHeM6BlMWr-A-Of8P_QJTEeLow</recordid><startdate>20181101</startdate><enddate>20181101</enddate><creator>Liu, Hejuan</creator><creator>Were, Patrick</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>M2P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope></search><sort><creationdate>20181101</creationdate><title>Geostatistical analysis on the spatial variation of radiogenic elements in the crystalline basement of Grenville Province in the southwestern Québec</title><author>Liu, Hejuan ; Were, Patrick</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a291t-22c49c262f709130db98890594aebe9c37e9ea52016b6a067eb0f7086c2298173</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Biogeosciences</topic><topic>Computer simulation</topic><topic>Density</topic><topic>Distribution</topic><topic>Domains</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Environmental Science and Engineering</topic><topic>Geochemistry</topic><topic>Geology</topic><topic>Geostatistics</topic><topic>Geothermal resources</topic><topic>Heat</topic><topic>Heterogeneity</topic><topic>Hydrology/Water Resources</topic><topic>Initial conditions</topic><topic>Interpolation</topic><topic>Kriging interpolation</topic><topic>Mathematical models</topic><topic>Normal distribution</topic><topic>Original Article</topic><topic>Parameter uncertainty</topic><topic>Potassium</topic><topic>Rock</topic><topic>Rocks</topic><topic>Spatial analysis</topic><topic>Spatial distribution</topic><topic>Spatial variations</topic><topic>Statistical methods</topic><topic>Subsurface temperatures</topic><topic>Temperature dependence</topic><topic>Terrestrial Pollution</topic><topic>Thermal analysis</topic><topic>Thermal models</topic><topic>Thorium</topic><topic>Uranium</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Hejuan</creatorcontrib><creatorcontrib>Were, Patrick</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Science Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><jtitle>Environmental earth sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Hejuan</au><au>Were, Patrick</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geostatistical analysis on the spatial variation of radiogenic elements in the crystalline basement of Grenville Province in the southwestern Québec</atitle><jtitle>Environmental earth sciences</jtitle><stitle>Environ Earth Sci</stitle><date>2018-11-01</date><risdate>2018</risdate><volume>77</volume><issue>21</issue><spage>1</spage><epage>12</epage><pages>1-12</pages><artnum>731</artnum><issn>1866-6280</issn><eissn>1866-6299</eissn><abstract>Accurate assessment of deep geothermal resources remains a challenge from the practical point of view. Parameter uncertainties and partial knowledge of initial conditions limit the prediction of subsurface temperatures using a variety of thermal models strongly unreliable, and the temperature is highly dependent on the radiogenic heat production in the geological layers mainly affected by a number of factors including the concentrations of uranium, thorium and potassium, and rock density. In this paper, geostatistical methods were applied to investigate the spatial distribution of radiogenic elements (e.g., uranium, thorium, potassium) and their corresponding concentrations and radiogenic heat production. A representative region measuring 35 km × 80 km in the southwestern Québec, and covering the domains of Portneuf-Mauricie, Morin Terrane and Parc des Laurentides in the Grenville Province was selected for this study because of its easy accessibility. Analysis results show that the concentrations of uranium, thorium and potassium for most rocks of the Grenville basement in the research region are in the range of 1–2 ppm, 3–10 ppm and 1–4%, respectively. Furthermore, 90% of the total samples analysed in this study show a uranium concentration of less than 3 ppm, 64% of the samples show a thorium concentration of less than 5 ppm, and 56% of the samples show a potassium concentration of less than 3%. This paper engaged both the ordinary kriging interpolation and sequential Gaussian simulation (SGS) methods to study the spatial distribution of radiogenic elements. Using density data for specific rocks, the distribution of radiogenic heat production in the study area of the southwestern Grenville Province was also simulated using the SGS method. Conclusively, results show that the difference between the minimum and the maximum value of radiogenic heat production is 30%, considering a significant proportion of heterogeneity in rock density.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s12665-018-7917-1</doi><tpages>12</tpages></addata></record> |
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subjects | Biogeosciences Computer simulation Density Distribution Domains Earth and Environmental Science Earth Sciences Environmental Science and Engineering Geochemistry Geology Geostatistics Geothermal resources Heat Heterogeneity Hydrology/Water Resources Initial conditions Interpolation Kriging interpolation Mathematical models Normal distribution Original Article Parameter uncertainty Potassium Rock Rocks Spatial analysis Spatial distribution Spatial variations Statistical methods Subsurface temperatures Temperature dependence Terrestrial Pollution Thermal analysis Thermal models Thorium Uranium |
title | Geostatistical analysis on the spatial variation of radiogenic elements in the crystalline basement of Grenville Province in the southwestern Québec |
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