Construction of Deep Thermal Models Based on Integrated Thermal Properties Used for Geothermal Risk Management View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Hejuan Liu, Mather Nasr

ABSTRACT

The development of deep geothermal energy may be at risk from the economic point of view if the estimated deep thermal field is far from its real state. The strong heterogeneity of geological units makes it challenging to perform a reliable estimation on the construction of the deep thermal field over a large region. Additionally, the thermal properties of rocks, such as thermal conductivity and the radiogenic element concentration, whether they are from laboratory measurements or inversed from well logs, may strongly control the deep thermal field at a local scale. In this paper, the thermal conductivities of rocks from the Trois-Rivières region in the Saint Lawrence Lowlands sedimentary basin in eastern Canada are obtained from two methods: (i) direct experimental measurement and (ii) indirect inversion method using well logs, including gamma ray, neutron porosity, density, and photoelectric absorption factor. The spatial distribution of subsurface temperature in the study area in the Trois-Rivières region is numerically investigated by considering four case studies that include different values (minimum, average, and maximum) of the thermal properties by applying the Underworld simulator. The results show that thermal properties play a large role in controlling the subsurface temperature distribution and heat flux. The temperature difference can reach 15 °C in the basement, caused by the difference in thermal properties in the Trois-Rivières region. The highest heat flux is found in the Trenton–Black River–Chazy groups, and the lowest heat flux is in the Potsdam group, which also has the highest thermal conductivity. Vertical heat flux does not change linearly with depth but is highly related to the thermal properties of specific geological formations. Furthermore, it does not have a positive correlation with the vertical temperature changes. This demonstrates that the assessment of the potential of deep geothermal energy depending merely on the surface heat flux may greatly overestimate or underestimate the geothermal capacity. Construction of the thermal models based on the integrated thermal properties from both the experimental measurement and well logs in this paper is useful in reducing the exploration risk associated with the utilization of deep geothermal energy. More... »

PAGES

295-317

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11004-019-09790-z

DOI

http://dx.doi.org/10.1007/s11004-019-09790-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112685254


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0403", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Geology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Earth Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Chinese Academy of Sciences", 
          "id": "https://www.grid.ac/institutes/grid.410726.6", 
          "name": [
            "State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, 430071, Wuhan, Hubei, China", 
            "University of Chinese Academy of Sciences, 100049, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Hejuan", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institut National de la Recherche Scientifique", 
          "id": "https://www.grid.ac/institutes/grid.418084.1", 
          "name": [
            "Centre Eau Terre Environnement, Institut National de la Recherche Scientifique, G1K 9A9, Qu\u00e9bec, QC, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nasr", 
        "givenName": "Mather", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/b978-0-08-023832-6.50015-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003203278"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0040-1951(03)00227-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006363021"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0040-1951(03)00227-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006363021"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.geothermics.2013.02.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010668898"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0012-821x(95)00187-h", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011154189"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-90-481-8702-7_63", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011779243", 
          "https://doi.org/10.1007/978-90-481-8702-7_63"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-246x.2007.03403.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016096348"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/97jb03104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016590196"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/e02-077", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017091006"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/96gl03929", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019248152"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0040-1951(84)90075-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020740559"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0040-1951(84)90075-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020740559"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/92tc01710", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020906224"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.epsl.2004.04.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022517733"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jog.2005.01.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022565446"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/e94-113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022788142"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.coal.2013.10.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023641173"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.geothermics.2016.04.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024378927"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.chemer.2010.05.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026896061"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1364-0321(02)00002-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026951391"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.epsl.2014.01.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027654430"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.epsl.2014.01.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027654430"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00878955", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030275332", 
          "https://doi.org/10.1007/bf00878955"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2005.05.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032525334"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.rser.2014.04.075", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033089862"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/e95-109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034830581"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.egypro.2013.06.422", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036117237"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1038267869", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-34023-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038267869", 
          "https://doi.org/10.1007/978-3-642-34023-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-34023-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038267869", 
          "https://doi.org/10.1007/978-3-642-34023-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12665-013-2941-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038329571", 
          "https://doi.org/10.1007/s12665-013-2941-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/e09-059", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039501700"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jb076i017p03842", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043753834"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.geothermics.2012.03.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044036310"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.pepi.2007.06.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044818577"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0016-7037(01)00704-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046374950"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1130/0016-7606(1994)106<0461:assotd>2.3.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047272094"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/0471743984.vse3592", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048804497"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/0471743984.vse3592", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048804497"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0040-1951(93)90194-o", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049907419"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0040-1951(93)90194-o", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049907419"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0012-821x(77)90002-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052854059"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0012-821x(77)90002-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052854059"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/1742-2132/13/3/366", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059162427"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/1742-2132/7/3/002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059162724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/gji/ggt382", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059636983"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ipdps.2007.370400", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094191310"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511781773", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098701298"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511606021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098701482"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2973/odp.proc.sr.150.1996", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099137804"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.geothermics.2018.04.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103657403"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s40517-018-0115-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110911761", 
          "https://doi.org/10.1186/s40517-018-0115-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s40517-018-0115-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110911761", 
          "https://doi.org/10.1186/s40517-018-0115-2"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-04", 
    "datePublishedReg": "2019-04-01", 
    "description": "The development of deep geothermal energy may be at risk from the economic point of view if the estimated deep thermal field is far from its real state. The strong heterogeneity of geological units makes it challenging to perform a reliable estimation on the construction of the deep thermal field over a large region. Additionally, the thermal properties of rocks, such as thermal conductivity and the radiogenic element concentration, whether they are from laboratory measurements or inversed from well logs, may strongly control the deep thermal field at a local scale. In this paper, the thermal conductivities of rocks from the Trois-Rivi\u00e8res region in the Saint Lawrence Lowlands sedimentary basin in eastern Canada are obtained from two methods: (i) direct experimental measurement and (ii) indirect inversion method using well logs, including gamma ray, neutron porosity, density, and photoelectric absorption factor. The spatial distribution of subsurface temperature in the study area in the Trois-Rivi\u00e8res region is numerically investigated by considering four case studies that include different values (minimum, average, and maximum) of the thermal properties by applying the Underworld simulator. The results show that thermal properties play a large role in controlling the subsurface temperature distribution and heat flux. The temperature difference can reach 15 \u00b0C in the basement, caused by the difference in thermal properties in the Trois-Rivi\u00e8res region. The highest heat flux is found in the Trenton\u2013Black River\u2013Chazy groups, and the lowest heat flux is in the Potsdam group, which also has the highest thermal conductivity. Vertical heat flux does not change linearly with depth but is highly related to the thermal properties of specific geological formations. Furthermore, it does not have a positive correlation with the vertical temperature changes. This demonstrates that the assessment of the potential of deep geothermal energy depending merely on the surface heat flux may greatly overestimate or underestimate the geothermal capacity. Construction of the thermal models based on the integrated thermal properties from both the experimental measurement and well logs in this paper is useful in reducing the exploration risk associated with the utilization of deep geothermal energy.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11004-019-09790-z", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1039818", 
        "issn": [
          "1874-8961", 
          "1874-8953"
        ], 
        "name": "Mathematical Geosciences", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "51"
      }
    ], 
    "name": "Construction of Deep Thermal Models Based on Integrated Thermal Properties Used for Geothermal Risk Management", 
    "pagination": "295-317", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11004-019-09790-z"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ef718ff00c30ab8e481597fc4640eb12b67c99e1f84036ec56c44efc3481cb9f"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112685254"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11004-019-09790-z", 
      "https://app.dimensions.ai/details/publication/pub.1112685254"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-15T09:10", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000376_0000000376/records_56155_00000006.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs11004-019-09790-z"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11004-019-09790-z'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11004-019-09790-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11004-019-09790-z'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11004-019-09790-z'


 

This table displays all metadata directly associated to this object as RDF triples.

209 TRIPLES      21 PREDICATES      72 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11004-019-09790-z schema:about anzsrc-for:04
2 anzsrc-for:0403
3 schema:author N3b33cfbeec9744e0ac61ca4d1932e2aa
4 schema:citation sg:pub.10.1007/978-3-642-34023-9
5 sg:pub.10.1007/978-90-481-8702-7_63
6 sg:pub.10.1007/bf00878955
7 sg:pub.10.1007/s12665-013-2941-7
8 sg:pub.10.1186/s40517-018-0115-2
9 https://app.dimensions.ai/details/publication/pub.1038267869
10 https://doi.org/10.1002/0471743984.vse3592
11 https://doi.org/10.1016/0012-821x(77)90002-4
12 https://doi.org/10.1016/0012-821x(95)00187-h
13 https://doi.org/10.1016/0040-1951(84)90075-1
14 https://doi.org/10.1016/0040-1951(93)90194-o
15 https://doi.org/10.1016/b978-0-08-023832-6.50015-2
16 https://doi.org/10.1016/j.chemer.2010.05.017
17 https://doi.org/10.1016/j.coal.2013.10.011
18 https://doi.org/10.1016/j.egypro.2013.06.422
19 https://doi.org/10.1016/j.epsl.2004.04.002
20 https://doi.org/10.1016/j.epsl.2014.01.009
21 https://doi.org/10.1016/j.geothermics.2012.03.002
22 https://doi.org/10.1016/j.geothermics.2013.02.002
23 https://doi.org/10.1016/j.geothermics.2016.04.010
24 https://doi.org/10.1016/j.geothermics.2018.04.004
25 https://doi.org/10.1016/j.ijrmms.2005.05.015
26 https://doi.org/10.1016/j.jog.2005.01.003
27 https://doi.org/10.1016/j.pepi.2007.06.009
28 https://doi.org/10.1016/j.rser.2014.04.075
29 https://doi.org/10.1016/s0016-7037(01)00704-9
30 https://doi.org/10.1016/s0040-1951(03)00227-0
31 https://doi.org/10.1016/s1364-0321(02)00002-3
32 https://doi.org/10.1017/cbo9780511606021
33 https://doi.org/10.1017/cbo9780511781773
34 https://doi.org/10.1029/92tc01710
35 https://doi.org/10.1029/96gl03929
36 https://doi.org/10.1029/97jb03104
37 https://doi.org/10.1029/jb076i017p03842
38 https://doi.org/10.1088/1742-2132/13/3/366
39 https://doi.org/10.1088/1742-2132/7/3/002
40 https://doi.org/10.1093/gji/ggt382
41 https://doi.org/10.1109/ipdps.2007.370400
42 https://doi.org/10.1111/j.1365-246x.2007.03403.x
43 https://doi.org/10.1130/0016-7606(1994)106<0461:assotd>2.3.co;2
44 https://doi.org/10.1139/e02-077
45 https://doi.org/10.1139/e09-059
46 https://doi.org/10.1139/e94-113
47 https://doi.org/10.1139/e95-109
48 https://doi.org/10.2973/odp.proc.sr.150.1996
49 schema:datePublished 2019-04
50 schema:datePublishedReg 2019-04-01
51 schema:description The development of deep geothermal energy may be at risk from the economic point of view if the estimated deep thermal field is far from its real state. The strong heterogeneity of geological units makes it challenging to perform a reliable estimation on the construction of the deep thermal field over a large region. Additionally, the thermal properties of rocks, such as thermal conductivity and the radiogenic element concentration, whether they are from laboratory measurements or inversed from well logs, may strongly control the deep thermal field at a local scale. In this paper, the thermal conductivities of rocks from the Trois-Rivières region in the Saint Lawrence Lowlands sedimentary basin in eastern Canada are obtained from two methods: (i) direct experimental measurement and (ii) indirect inversion method using well logs, including gamma ray, neutron porosity, density, and photoelectric absorption factor. The spatial distribution of subsurface temperature in the study area in the Trois-Rivières region is numerically investigated by considering four case studies that include different values (minimum, average, and maximum) of the thermal properties by applying the Underworld simulator. The results show that thermal properties play a large role in controlling the subsurface temperature distribution and heat flux. The temperature difference can reach 15 °C in the basement, caused by the difference in thermal properties in the Trois-Rivières region. The highest heat flux is found in the Trenton–Black River–Chazy groups, and the lowest heat flux is in the Potsdam group, which also has the highest thermal conductivity. Vertical heat flux does not change linearly with depth but is highly related to the thermal properties of specific geological formations. Furthermore, it does not have a positive correlation with the vertical temperature changes. This demonstrates that the assessment of the potential of deep geothermal energy depending merely on the surface heat flux may greatly overestimate or underestimate the geothermal capacity. Construction of the thermal models based on the integrated thermal properties from both the experimental measurement and well logs in this paper is useful in reducing the exploration risk associated with the utilization of deep geothermal energy.
52 schema:genre research_article
53 schema:inLanguage en
54 schema:isAccessibleForFree false
55 schema:isPartOf N4cfd2c7e65e444d1940bf645c8539c73
56 Ne2e2fff42b41426b802100707c201293
57 sg:journal.1039818
58 schema:name Construction of Deep Thermal Models Based on Integrated Thermal Properties Used for Geothermal Risk Management
59 schema:pagination 295-317
60 schema:productId N808c834d45c449fd87c4eba59067606c
61 Nc9ed17612f114b5f93dc0440b36322b1
62 Ne56972ee0a754d94bdfd996c2b38625b
63 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112685254
64 https://doi.org/10.1007/s11004-019-09790-z
65 schema:sdDatePublished 2019-04-15T09:10
66 schema:sdLicense https://scigraph.springernature.com/explorer/license/
67 schema:sdPublisher N65df311260484a5a871d7b5c6697546b
68 schema:url https://link.springer.com/10.1007%2Fs11004-019-09790-z
69 sgo:license sg:explorer/license/
70 sgo:sdDataset articles
71 rdf:type schema:ScholarlyArticle
72 N3b33cfbeec9744e0ac61ca4d1932e2aa rdf:first Nbda3f95634c94a4d9c755c594c92653b
73 rdf:rest Na2af2a3839ad4d98a25aeaa56acc544e
74 N4cfd2c7e65e444d1940bf645c8539c73 schema:volumeNumber 51
75 rdf:type schema:PublicationVolume
76 N65df311260484a5a871d7b5c6697546b schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 N808c834d45c449fd87c4eba59067606c schema:name doi
79 schema:value 10.1007/s11004-019-09790-z
80 rdf:type schema:PropertyValue
81 Na2af2a3839ad4d98a25aeaa56acc544e rdf:first Ne4d9bc4039e1465caaaf7a5415525e70
82 rdf:rest rdf:nil
83 Nbda3f95634c94a4d9c755c594c92653b schema:affiliation https://www.grid.ac/institutes/grid.410726.6
84 schema:familyName Liu
85 schema:givenName Hejuan
86 rdf:type schema:Person
87 Nc9ed17612f114b5f93dc0440b36322b1 schema:name readcube_id
88 schema:value ef718ff00c30ab8e481597fc4640eb12b67c99e1f84036ec56c44efc3481cb9f
89 rdf:type schema:PropertyValue
90 Ne2e2fff42b41426b802100707c201293 schema:issueNumber 3
91 rdf:type schema:PublicationIssue
92 Ne4d9bc4039e1465caaaf7a5415525e70 schema:affiliation https://www.grid.ac/institutes/grid.418084.1
93 schema:familyName Nasr
94 schema:givenName Mather
95 rdf:type schema:Person
96 Ne56972ee0a754d94bdfd996c2b38625b schema:name dimensions_id
97 schema:value pub.1112685254
98 rdf:type schema:PropertyValue
99 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
100 schema:name Earth Sciences
101 rdf:type schema:DefinedTerm
102 anzsrc-for:0403 schema:inDefinedTermSet anzsrc-for:
103 schema:name Geology
104 rdf:type schema:DefinedTerm
105 sg:journal.1039818 schema:issn 1874-8953
106 1874-8961
107 schema:name Mathematical Geosciences
108 rdf:type schema:Periodical
109 sg:pub.10.1007/978-3-642-34023-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038267869
110 https://doi.org/10.1007/978-3-642-34023-9
111 rdf:type schema:CreativeWork
112 sg:pub.10.1007/978-90-481-8702-7_63 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011779243
113 https://doi.org/10.1007/978-90-481-8702-7_63
114 rdf:type schema:CreativeWork
115 sg:pub.10.1007/bf00878955 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030275332
116 https://doi.org/10.1007/bf00878955
117 rdf:type schema:CreativeWork
118 sg:pub.10.1007/s12665-013-2941-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038329571
119 https://doi.org/10.1007/s12665-013-2941-7
120 rdf:type schema:CreativeWork
121 sg:pub.10.1186/s40517-018-0115-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110911761
122 https://doi.org/10.1186/s40517-018-0115-2
123 rdf:type schema:CreativeWork
124 https://app.dimensions.ai/details/publication/pub.1038267869 schema:CreativeWork
125 https://doi.org/10.1002/0471743984.vse3592 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048804497
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/0012-821x(77)90002-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052854059
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/0012-821x(95)00187-h schema:sameAs https://app.dimensions.ai/details/publication/pub.1011154189
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/0040-1951(84)90075-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020740559
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/0040-1951(93)90194-o schema:sameAs https://app.dimensions.ai/details/publication/pub.1049907419
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/b978-0-08-023832-6.50015-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003203278
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.chemer.2010.05.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026896061
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/j.coal.2013.10.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023641173
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.egypro.2013.06.422 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036117237
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.epsl.2004.04.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022517733
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/j.epsl.2014.01.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027654430
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/j.geothermics.2012.03.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044036310
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/j.geothermics.2013.02.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010668898
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1016/j.geothermics.2016.04.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024378927
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1016/j.geothermics.2018.04.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103657403
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1016/j.ijrmms.2005.05.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032525334
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1016/j.jog.2005.01.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022565446
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1016/j.pepi.2007.06.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044818577
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1016/j.rser.2014.04.075 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033089862
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/s0016-7037(01)00704-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046374950
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/s0040-1951(03)00227-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006363021
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/s1364-0321(02)00002-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026951391
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1017/cbo9780511606021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098701482
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1017/cbo9780511781773 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098701298
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1029/92tc01710 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020906224
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1029/96gl03929 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019248152
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1029/97jb03104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016590196
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1029/jb076i017p03842 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043753834
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1088/1742-2132/13/3/366 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059162427
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1088/1742-2132/7/3/002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059162724
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1093/gji/ggt382 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059636983
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1109/ipdps.2007.370400 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094191310
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1111/j.1365-246x.2007.03403.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1016096348
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1130/0016-7606(1994)106<0461:assotd>2.3.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047272094
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1139/e02-077 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017091006
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1139/e09-059 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039501700
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1139/e94-113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022788142
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1139/e95-109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034830581
200 rdf:type schema:CreativeWork
201 https://doi.org/10.2973/odp.proc.sr.150.1996 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099137804
202 rdf:type schema:CreativeWork
203 https://www.grid.ac/institutes/grid.410726.6 schema:alternateName University of Chinese Academy of Sciences
204 schema:name State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, 430071, Wuhan, Hubei, China
205 University of Chinese Academy of Sciences, 100049, Beijing, China
206 rdf:type schema:Organization
207 https://www.grid.ac/institutes/grid.418084.1 schema:alternateName Institut National de la Recherche Scientifique
208 schema:name Centre Eau Terre Environnement, Institut National de la Recherche Scientifique, G1K 9A9, Québec, QC, Canada
209 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...