Formation water geochemistry for carbonate reservoirs in Ordos basin, China: Implications for hydrocarbon preservation by machine learning
Formation water can in principal be used to identify hydrocarbon reserves. One such potential reserves are the gas reservoirs in the Ordos basin in China. However, there is limited data for this basin; we thus investigated the geochemical properties of a large range of formation water acquired from...
| Main Authors: | , , , , , , , |
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| Format: | Journal Article |
| Language: | English |
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ELSEVIER
2020
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| Online Access: | http://hdl.handle.net/20.500.11937/89580 |
| _version_ | 1848765251191832576 |
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| author | Yu, Hongyan Wang, Z. Rezaee, Reza Zhang, Y. Nwidee, Lezorgia N. Liu, X. Verrall, M. Iglauer, Stefan |
| author_facet | Yu, Hongyan Wang, Z. Rezaee, Reza Zhang, Y. Nwidee, Lezorgia N. Liu, X. Verrall, M. Iglauer, Stefan |
| author_sort | Yu, Hongyan |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Formation water can in principal be used to identify hydrocarbon reserves. One such potential reserves are the gas reservoirs in the Ordos basin in China. However, there is limited data for this basin; we thus investigated the geochemical properties of a large range of formation water acquired from the Ordovician in the Ordos basin (42 brine samples obtained from different wells at M5 member) and analyzed their chemical characteristics. The results showed that this formation water is associated with a sealed reservoir, which is good for hydrocarbon storage. This is also related to the demonstrated strong diagenetic transformations. We also proposed statistical relationships between these geochemical properties and hydrocarbon storage based on a machine learning method (Decision tree). The results suggest that the salinity, Na+/Cl− ratio, (Cl−-Na+)/Mg2+ ratio, (HCO3−-CO32-)/Ca2+ ratio and Mg2+/Ca2+ ratio highly correlate with the gas preservation. The results thus provide drastically more accurate predictions in terms of where to find gas reservoirs in the Ordos basin, and can thus lead to significantly better exploitation of these resources. |
| first_indexed | 2025-11-14T11:32:17Z |
| format | Journal Article |
| id | curtin-20.500.11937-89580 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:32:17Z |
| publishDate | 2020 |
| publisher | ELSEVIER |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-895802022-11-18T07:17:02Z Formation water geochemistry for carbonate reservoirs in Ordos basin, China: Implications for hydrocarbon preservation by machine learning Yu, Hongyan Wang, Z. Rezaee, Reza Zhang, Y. Nwidee, Lezorgia N. Liu, X. Verrall, M. Iglauer, Stefan Science & Technology Technology Energy & Fuels Engineering, Petroleum Engineering Formation water Ion concentration Hydrocarbon preservation Machine learning Decision tree THERMOCHEMICAL SULFATE REDUCTION NATURAL HYDROTHERMAL SYSTEMS CANADA SEDIMENTARY BASIN SALINE FORMATION WATER METEORIC WATER ROCK REACTIONS GERMAN BASIN GAS-FIELD ISOTOPIC COMPOSITION BASALT INTERACTIONS Formation water can in principal be used to identify hydrocarbon reserves. One such potential reserves are the gas reservoirs in the Ordos basin in China. However, there is limited data for this basin; we thus investigated the geochemical properties of a large range of formation water acquired from the Ordovician in the Ordos basin (42 brine samples obtained from different wells at M5 member) and analyzed their chemical characteristics. The results showed that this formation water is associated with a sealed reservoir, which is good for hydrocarbon storage. This is also related to the demonstrated strong diagenetic transformations. We also proposed statistical relationships between these geochemical properties and hydrocarbon storage based on a machine learning method (Decision tree). The results suggest that the salinity, Na+/Cl− ratio, (Cl−-Na+)/Mg2+ ratio, (HCO3−-CO32-)/Ca2+ ratio and Mg2+/Ca2+ ratio highly correlate with the gas preservation. The results thus provide drastically more accurate predictions in terms of where to find gas reservoirs in the Ordos basin, and can thus lead to significantly better exploitation of these resources. 2020 Journal Article http://hdl.handle.net/20.500.11937/89580 10.1016/j.petrol.2019.106673 English ELSEVIER restricted |
| spellingShingle | Science & Technology Technology Energy & Fuels Engineering, Petroleum Engineering Formation water Ion concentration Hydrocarbon preservation Machine learning Decision tree THERMOCHEMICAL SULFATE REDUCTION NATURAL HYDROTHERMAL SYSTEMS CANADA SEDIMENTARY BASIN SALINE FORMATION WATER METEORIC WATER ROCK REACTIONS GERMAN BASIN GAS-FIELD ISOTOPIC COMPOSITION BASALT INTERACTIONS Yu, Hongyan Wang, Z. Rezaee, Reza Zhang, Y. Nwidee, Lezorgia N. Liu, X. Verrall, M. Iglauer, Stefan Formation water geochemistry for carbonate reservoirs in Ordos basin, China: Implications for hydrocarbon preservation by machine learning |
| title | Formation water geochemistry for carbonate reservoirs in Ordos basin, China: Implications for hydrocarbon preservation by machine learning |
| title_full | Formation water geochemistry for carbonate reservoirs in Ordos basin, China: Implications for hydrocarbon preservation by machine learning |
| title_fullStr | Formation water geochemistry for carbonate reservoirs in Ordos basin, China: Implications for hydrocarbon preservation by machine learning |
| title_full_unstemmed | Formation water geochemistry for carbonate reservoirs in Ordos basin, China: Implications for hydrocarbon preservation by machine learning |
| title_short | Formation water geochemistry for carbonate reservoirs in Ordos basin, China: Implications for hydrocarbon preservation by machine learning |
| title_sort | formation water geochemistry for carbonate reservoirs in ordos basin, china: implications for hydrocarbon preservation by machine learning |
| topic | Science & Technology Technology Energy & Fuels Engineering, Petroleum Engineering Formation water Ion concentration Hydrocarbon preservation Machine learning Decision tree THERMOCHEMICAL SULFATE REDUCTION NATURAL HYDROTHERMAL SYSTEMS CANADA SEDIMENTARY BASIN SALINE FORMATION WATER METEORIC WATER ROCK REACTIONS GERMAN BASIN GAS-FIELD ISOTOPIC COMPOSITION BASALT INTERACTIONS |
| url | http://hdl.handle.net/20.500.11937/89580 |