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Optimized feature selection assists lithofacies machine learning with sparse …
Machine learning (ML) to predict lithofacies from sparse suites of well-log data is difficult in laterally and vertically heterogeneous reservoir formations in oil and gas fields. Meandering, braided fluviatile depositional environments tend to form clastic sequences with laterally discontinuous layers due to the continuous shifting of relatively narrow sandstone channels. Three cored wellbores…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 16 hlm PDF, 10.025 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Enhancing lithofacies machine learning predictions with gamma-ray attributes …
Derivative and volatility attributes can be usefully calculated from recorded gamma ray (GR) data to enhance lithofacies classification in wellbores penetrating multiple lithologies. Such attributes extract information about the log curve shape that cannot be readily discerned from the recorded well log data. A logged wellbore section for which 8911 data records are available for the three reco…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 17 hlm PDF, 5.728 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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