Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems: Prediction Models Exploiting Well-Log Information
Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems: Prediction Models Exploiting Well-Log Information explores machine and deep learning models for subsurface geological prediction problems commonly encountered in applied resource evaluation and...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Amsterdam
Elsevier
[2025]
|
| Links: | https://www.sciencedirect.com/science/book/9780443265105 https://doi.org/10.1016/C2023-0-51304-7 |
| Zusammenfassung: | Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems: Prediction Models Exploiting Well-Log Information explores machine and deep learning models for subsurface geological prediction problems commonly encountered in applied resource evaluation and reservoir characterization tasks. The book provides insights into how the performance of ML/DL models can be optimized—and sparse datasets of input variables enhanced and/or rescaled—to improve prediction performances. A variety of topics are covered, including regression models to estimate total organic carbon from well-log data, predicting brittleness indexes in tight formation sequences, trapping mechanisms in potential sub-surface carbon storage reservoirs, and more. Each chapter includes its own introduction, summary, and nomenclature sections, along with one or more case studies focused on prediction model implementation related to its topic. |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9780443265112 |
| DOI: | 10.1016/C2023-0-51304-7 |
Internformat
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| spelling | Wood, David A. Verfasser (DE-588)1251889549 aut Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems Prediction Models Exploiting Well-Log Information David A. Wood (DWA Energy Limited, Lincoln, United Kingdom) Amsterdam Elsevier [2025] 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems: Prediction Models Exploiting Well-Log Information explores machine and deep learning models for subsurface geological prediction problems commonly encountered in applied resource evaluation and reservoir characterization tasks. The book provides insights into how the performance of ML/DL models can be optimized—and sparse datasets of input variables enhanced and/or rescaled—to improve prediction performances. A variety of topics are covered, including regression models to estimate total organic carbon from well-log data, predicting brittleness indexes in tight formation sequences, trapping mechanisms in potential sub-surface carbon storage reservoirs, and more. Each chapter includes its own introduction, summary, and nomenclature sections, along with one or more case studies focused on prediction model implementation related to its topic. Erscheint auch als Druck-Ausgabe 978-0-443-26510-5 https://doi.org/10.1016/C2023-0-51304-7 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Wood, David A. Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems Prediction Models Exploiting Well-Log Information |
| title | Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems Prediction Models Exploiting Well-Log Information |
| title_auth | Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems Prediction Models Exploiting Well-Log Information |
| title_exact_search | Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems Prediction Models Exploiting Well-Log Information |
| title_full | Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems Prediction Models Exploiting Well-Log Information David A. Wood (DWA Energy Limited, Lincoln, United Kingdom) |
| title_fullStr | Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems Prediction Models Exploiting Well-Log Information David A. Wood (DWA Energy Limited, Lincoln, United Kingdom) |
| title_full_unstemmed | Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems Prediction Models Exploiting Well-Log Information David A. Wood (DWA Energy Limited, Lincoln, United Kingdom) |
| title_short | Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems |
| title_sort | implementation and interpretation of machine and deep learning to applied subsurface geological problems prediction models exploiting well log information |
| title_sub | Prediction Models Exploiting Well-Log Information |
| url | https://doi.org/10.1016/C2023-0-51304-7 |
| work_keys_str_mv | AT wooddavida implementationandinterpretationofmachineanddeeplearningtoappliedsubsurfacegeologicalproblemspredictionmodelsexploitingwellloginformation |