Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation Zones
In the last decade, exploration for unconventional hydrocarbon (shale gas) reservoirs has been carried out in Poland. The drilling of wells in prospective shale gas areas supplies numerous physicochemical measurements from rock and reservoir fluid samples. The objective of this paper is to present t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/4/1464 |
| _version_ | 1797480674137997312 |
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| author | Tadeusz Kwilosz Bogdan Filar Mariusz Miziołek |
| author_facet | Tadeusz Kwilosz Bogdan Filar Mariusz Miziołek |
| author_sort | Tadeusz Kwilosz |
| collection | DOAJ |
| description | In the last decade, exploration for unconventional hydrocarbon (shale gas) reservoirs has been carried out in Poland. The drilling of wells in prospective shale gas areas supplies numerous physicochemical measurements from rock and reservoir fluid samples. The objective of this paper is to present the method that has been developed for finding similarities between individual geological structures in terms of their hydrocarbon generation properties and hydrocarbon resources. The measurements and geochemical investigations of six wells located in the Ordovician, Silurian, and Cambrian formations of the Polish part of the East European Platform are used. Cluster analysis is used to compare and classify objects described by multiple attributes. The focus is on the issue of generating clusters that group samples within the gas, condensate, and oil windows. The vitrinite reflectance value (R<sub>o</sub>) is adopted as the criterion for classifying individual samples into the respective windows. An additional issue was determining other characteristic geochemical properties of the samples classified into the selected clusters. Two variants of cluster analysis are applied—the furthest neighbor method and Ward’s method—which resulted in 10 and 11 clusters, respectively. Particular attention was paid to the mean Ro values (within each cluster), allowing the classification of samples from a given cluster into one of the windows (gas, condensate, or oil). Using these methods, the samples were effectively classified into individual windows, and their percentage share within the Silurian, Ordovician, and Cambrian units is determined. |
| first_indexed | 2024-03-09T22:03:27Z |
| format | Article |
| id | doaj.art-5889b8be31fb4205ba5657239ae79e51 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T22:03:27Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-5889b8be31fb4205ba5657239ae79e512023-11-23T19:44:32ZengMDPI AGEnergies1996-10732022-02-01154146410.3390/en15041464Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation ZonesTadeusz Kwilosz0Bogdan Filar1Mariusz Miziołek2Oil and Gas Institute-National Research Institute, 25A Lubicz Str., 31-503 Krakow, PolandOil and Gas Institute-National Research Institute, 25A Lubicz Str., 31-503 Krakow, PolandOil and Gas Institute-National Research Institute, 25A Lubicz Str., 31-503 Krakow, PolandIn the last decade, exploration for unconventional hydrocarbon (shale gas) reservoirs has been carried out in Poland. The drilling of wells in prospective shale gas areas supplies numerous physicochemical measurements from rock and reservoir fluid samples. The objective of this paper is to present the method that has been developed for finding similarities between individual geological structures in terms of their hydrocarbon generation properties and hydrocarbon resources. The measurements and geochemical investigations of six wells located in the Ordovician, Silurian, and Cambrian formations of the Polish part of the East European Platform are used. Cluster analysis is used to compare and classify objects described by multiple attributes. The focus is on the issue of generating clusters that group samples within the gas, condensate, and oil windows. The vitrinite reflectance value (R<sub>o</sub>) is adopted as the criterion for classifying individual samples into the respective windows. An additional issue was determining other characteristic geochemical properties of the samples classified into the selected clusters. Two variants of cluster analysis are applied—the furthest neighbor method and Ward’s method—which resulted in 10 and 11 clusters, respectively. Particular attention was paid to the mean Ro values (within each cluster), allowing the classification of samples from a given cluster into one of the windows (gas, condensate, or oil). Using these methods, the samples were effectively classified into individual windows, and their percentage share within the Silurian, Ordovician, and Cambrian units is determined.https://www.mdpi.com/1996-1073/15/4/1464unconventional resourcesshale gasoil gastotal organic carbon (TOC)cluster analysisgenetic type of kerogen |
| spellingShingle | Tadeusz Kwilosz Bogdan Filar Mariusz Miziołek Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation Zones Energies unconventional resources shale gas oil gas total organic carbon (TOC) cluster analysis genetic type of kerogen |
| title | Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation Zones |
| title_full | Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation Zones |
| title_fullStr | Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation Zones |
| title_full_unstemmed | Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation Zones |
| title_short | Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation Zones |
| title_sort | use of cluster analysis to group organic shale gas rocks by hydrocarbon generation zones |
| topic | unconventional resources shale gas oil gas total organic carbon (TOC) cluster analysis genetic type of kerogen |
| url | https://www.mdpi.com/1996-1073/15/4/1464 |
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