| 000 | 01992cam a2200289zu 4500 | ||
|---|---|---|---|
| 001 | 88965431 | ||
| 003 | FRCYB88965431 | ||
| 005 | 20250429183730.0 | ||
| 006 | m o d | ||
| 007 | cr un | ||
| 008 | 250429s2021 fr | o|||||0|0|||eng d | ||
| 020 | _a9780323854658 | ||
| 035 | _aFRCYB88965431 | ||
| 040 |
_aFR-PaCSA _ben _c _erda |
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| 100 | 1 | _aWood, David A. | |
| 245 | 0 | 1 |
_aSustainable Geoscience for Natural Gas SubSurface Systems _c['Wood, David A.', 'Cai, Jianchao'] |
| 264 | 1 |
_bGulf Professional Publishing _c2021 |
|
| 300 | _a p. | ||
| 336 |
_btxt _2rdacontent |
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| 337 |
_bc _2rdamdedia |
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| 338 |
_bc _2rdacarrier |
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| 650 | 0 | _a | |
| 700 | 0 | _aWood, David A. | |
| 700 | 0 | _aCai, Jianchao | |
| 856 | 4 | 0 |
_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88965431 _qtext/html _a |
| 520 | _aSustainable Geoscience for Natural Gas SubSurface Systems delivers many of the scientific fundamentals needed in the natural gas industry, including coal-seam gas reservoir characterization and fracture analysis modeling for shale and tight gas reservoirs. Advanced research includes machine learning applications for well log and facies analysis, 3D gas property geological modeling, and X-ray CT scanning to reduce environmental hazards. Supported by corporate and academic contributors, along with two well-distinguished editors, the book gives today's natural gas engineers both fundamentals and advances in a convenient resource, with a zero-carbon future in mind. - Includes structured case studies to illustrate how new principles can be applied in practical situations - Helps readers understand advanced topics, including machine learning applications to optimize predictions, controls and improve knowledge-based applications - Provides tactics to accelerate emission reductions - Teaches gas fracturing mechanics aimed at reducing environmental impacts, along with enhanced oil recovery technologies that capture carbon dioxide | ||
| 999 |
_c1330064 _d1330064 |
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