Determination of coal layers using geophysical well-logging methods for correlation of the Gelik-Zonguldak and Kazpınar-Amasra (Bartın) coalfields, Turkey View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02-01

AUTHORS

Ayhan Keskinsezer

ABSTRACT

The most commonly used well-logging methods for determining coal layers are radioactive (gamma ray, neutron and gamma–gamma) and electrical (resistivity, spontaneous potential and inductive polarization). Other methods that can be used are sonic, thermal, density, caliper and dipmeter logs. In the determination of the coal beds, the evaluation of the well-logs and the interactions between the boreholes are very important. The boundaries of the geological strata are determined by the logs, which are also spatially correlated. The decrease in gamma-ray values, low neutron density, high resistivity, characterize coal layers. Due to the presence of large coal reserves in this area, 81 boreholes have been drilled at the determined points in the long term. Radioactive and electrical well-logs have been applied to these boreholes in order to determine lithology and coal beds. In this study, three boreholes from Gelik-Zonguldak region and four boreholes from Kazpınar-Amasra (Bartın) region were selected and evaluated. Geophysical data were used for the determination of coal beds and correlation. Regional assessments were made with the lithological, structural and tectonic data. More... »

PAGES

1-13

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40948-019-00105-4

DOI

http://dx.doi.org/10.1007/s40948-019-00105-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112541269


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/2008/0299", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Other Physical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/02", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Sakarya University", 
          "id": "https://www.grid.ac/institutes/grid.49746.38", 
          "name": [
            "Department of Geophysical Engineering, Engineering Faculty, Sakarya University, 54187, Adapazar\u0131, Sakarya, Turkey"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Keskinsezer", 
        "givenName": "Ayhan", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0166-5162(94)90028-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002468043"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0166-5162(94)90028-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002468043"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0166-5162(00)00021-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004433684"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0166-5162(00)00004-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007046645"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.coal.2010.07.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019187814"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0166-5162(97)00047-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025652293"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.fuel.2009.06.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030346695"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.fuel.2009.05.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036237447"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0306-2619(02)00191-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045242480"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0306-2619(02)00191-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045242480"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2009.04.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049403612"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.coal.2008.10.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051682317"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0146-6380(02)00123-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052504854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0146-6380(02)00123-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052504854"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-02-01", 
    "datePublishedReg": "2019-02-01", 
    "description": "The most commonly used well-logging methods for determining coal layers are radioactive (gamma ray, neutron and gamma\u2013gamma) and electrical (resistivity, spontaneous potential and inductive polarization). Other methods that can be used are sonic, thermal, density, caliper and dipmeter logs. In the determination of the coal beds, the evaluation of the well-logs and the interactions between the boreholes are very important. The boundaries of the geological strata are determined by the logs, which are also spatially correlated. The decrease in gamma-ray values, low neutron density, high resistivity, characterize coal layers. Due to the presence of large coal reserves in this area, 81 boreholes have been drilled at the determined points in the long term. Radioactive and electrical well-logs have been applied to these boreholes in order to determine lithology and coal beds. In this study, three boreholes from Gelik-Zonguldak region and four boreholes from Kazp\u0131nar-Amasra (Bart\u0131n) region were selected and evaluated. Geophysical data were used for the determination of coal beds and correlation. Regional assessments were made with the lithological, structural and tectonic data.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s40948-019-00105-4", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1135968", 
        "issn": [
          "2363-8419", 
          "2363-8427"
        ], 
        "name": "Geomechanics and Geophysics for Geo-Energy and Geo-Resources", 
        "type": "Periodical"
      }
    ], 
    "name": "Determination of coal layers using geophysical well-logging methods for correlation of the Gelik-Zonguldak and Kazp\u0131nar-Amasra (Bart\u0131n) coalfields, Turkey", 
    "pagination": "1-13", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "5c5558bb2f466526299cd5343dccc84e9b442bc6ef53d93558f8106d120d5269"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s40948-019-00105-4"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112541269"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s40948-019-00105-4", 
      "https://app.dimensions.ai/details/publication/pub.1112541269"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T11:02", 
    "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/v90/0000000352_0000000352/records_60351_00000004.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs40948-019-00105-4"
  }
]
 

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/s40948-019-00105-4'

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/s40948-019-00105-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s40948-019-00105-4'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s40948-019-00105-4'


 

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

87 TRIPLES      21 PREDICATES      35 URIs      16 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s40948-019-00105-4 schema:about anzsrc-for:02
2 anzsrc-for:0299
3 schema:author N211ec55b043d41149d86b761527e9f8f
4 schema:citation https://doi.org/10.1016/0166-5162(94)90028-0
5 https://doi.org/10.1016/j.coal.2008.10.005
6 https://doi.org/10.1016/j.coal.2010.07.002
7 https://doi.org/10.1016/j.fuel.2009.05.018
8 https://doi.org/10.1016/j.fuel.2009.06.003
9 https://doi.org/10.1016/j.ijrmms.2009.04.002
10 https://doi.org/10.1016/s0146-6380(02)00123-7
11 https://doi.org/10.1016/s0166-5162(00)00004-5
12 https://doi.org/10.1016/s0166-5162(00)00021-5
13 https://doi.org/10.1016/s0166-5162(97)00047-5
14 https://doi.org/10.1016/s0306-2619(02)00191-5
15 schema:datePublished 2019-02-01
16 schema:datePublishedReg 2019-02-01
17 schema:description The most commonly used well-logging methods for determining coal layers are radioactive (gamma ray, neutron and gamma–gamma) and electrical (resistivity, spontaneous potential and inductive polarization). Other methods that can be used are sonic, thermal, density, caliper and dipmeter logs. In the determination of the coal beds, the evaluation of the well-logs and the interactions between the boreholes are very important. The boundaries of the geological strata are determined by the logs, which are also spatially correlated. The decrease in gamma-ray values, low neutron density, high resistivity, characterize coal layers. Due to the presence of large coal reserves in this area, 81 boreholes have been drilled at the determined points in the long term. Radioactive and electrical well-logs have been applied to these boreholes in order to determine lithology and coal beds. In this study, three boreholes from Gelik-Zonguldak region and four boreholes from Kazpınar-Amasra (Bartın) region were selected and evaluated. Geophysical data were used for the determination of coal beds and correlation. Regional assessments were made with the lithological, structural and tectonic data.
18 schema:genre research_article
19 schema:inLanguage en
20 schema:isAccessibleForFree false
21 schema:isPartOf sg:journal.1135968
22 schema:name Determination of coal layers using geophysical well-logging methods for correlation of the Gelik-Zonguldak and Kazpınar-Amasra (Bartın) coalfields, Turkey
23 schema:pagination 1-13
24 schema:productId N85a9f69c94964e8aaf86ff815fde5832
25 Nd95296f506fe4c2791c2e63964964b9b
26 Nf95605aafdc84b7e9c073ff0cbd2b5e3
27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112541269
28 https://doi.org/10.1007/s40948-019-00105-4
29 schema:sdDatePublished 2019-04-11T11:02
30 schema:sdLicense https://scigraph.springernature.com/explorer/license/
31 schema:sdPublisher Neb6cc125991949f79b1bc263ef820730
32 schema:url https://link.springer.com/10.1007%2Fs40948-019-00105-4
33 sgo:license sg:explorer/license/
34 sgo:sdDataset articles
35 rdf:type schema:ScholarlyArticle
36 N211ec55b043d41149d86b761527e9f8f rdf:first Na06d1598daa940a491483687e3369c45
37 rdf:rest rdf:nil
38 N85a9f69c94964e8aaf86ff815fde5832 schema:name dimensions_id
39 schema:value pub.1112541269
40 rdf:type schema:PropertyValue
41 Na06d1598daa940a491483687e3369c45 schema:affiliation https://www.grid.ac/institutes/grid.49746.38
42 schema:familyName Keskinsezer
43 schema:givenName Ayhan
44 rdf:type schema:Person
45 Nd95296f506fe4c2791c2e63964964b9b schema:name readcube_id
46 schema:value 5c5558bb2f466526299cd5343dccc84e9b442bc6ef53d93558f8106d120d5269
47 rdf:type schema:PropertyValue
48 Neb6cc125991949f79b1bc263ef820730 schema:name Springer Nature - SN SciGraph project
49 rdf:type schema:Organization
50 Nf95605aafdc84b7e9c073ff0cbd2b5e3 schema:name doi
51 schema:value 10.1007/s40948-019-00105-4
52 rdf:type schema:PropertyValue
53 anzsrc-for:02 schema:inDefinedTermSet anzsrc-for:
54 schema:name Physical Sciences
55 rdf:type schema:DefinedTerm
56 anzsrc-for:0299 schema:inDefinedTermSet anzsrc-for:
57 schema:name Other Physical Sciences
58 rdf:type schema:DefinedTerm
59 sg:journal.1135968 schema:issn 2363-8419
60 2363-8427
61 schema:name Geomechanics and Geophysics for Geo-Energy and Geo-Resources
62 rdf:type schema:Periodical
63 https://doi.org/10.1016/0166-5162(94)90028-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002468043
64 rdf:type schema:CreativeWork
65 https://doi.org/10.1016/j.coal.2008.10.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051682317
66 rdf:type schema:CreativeWork
67 https://doi.org/10.1016/j.coal.2010.07.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019187814
68 rdf:type schema:CreativeWork
69 https://doi.org/10.1016/j.fuel.2009.05.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036237447
70 rdf:type schema:CreativeWork
71 https://doi.org/10.1016/j.fuel.2009.06.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030346695
72 rdf:type schema:CreativeWork
73 https://doi.org/10.1016/j.ijrmms.2009.04.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049403612
74 rdf:type schema:CreativeWork
75 https://doi.org/10.1016/s0146-6380(02)00123-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052504854
76 rdf:type schema:CreativeWork
77 https://doi.org/10.1016/s0166-5162(00)00004-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007046645
78 rdf:type schema:CreativeWork
79 https://doi.org/10.1016/s0166-5162(00)00021-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004433684
80 rdf:type schema:CreativeWork
81 https://doi.org/10.1016/s0166-5162(97)00047-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025652293
82 rdf:type schema:CreativeWork
83 https://doi.org/10.1016/s0306-2619(02)00191-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045242480
84 rdf:type schema:CreativeWork
85 https://www.grid.ac/institutes/grid.49746.38 schema:alternateName Sakarya University
86 schema:name Department of Geophysical Engineering, Engineering Faculty, Sakarya University, 54187, Adapazarı, Sakarya, Turkey
87 rdf:type schema:Organization
 




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


...