Pore Pressure Prediction by Empirical and Machine Learning Methods Using Conventional and Drilling Logs in Carbonate Rocks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geology,Geotechnical Engineering and Engineering Geology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00603-022-03089-y.pdf
Reference68 articles.
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2. Abdulmalek AS, Elkatatny S, Abdulraheem A, Mahmoud M, Abdulwahab ZA, Mohamed IM (2018) Pore pressure prediction while drilling using fuzzy logic. SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition, Dammam, Saudi Arabia, April 2018. https://doi.org/10.2118/192318-MS
3. Ahmed A, Elkatatny S, Ali A, Abdulraheem A (2019) Comparative analysis of artificial intelligence techniques for formation pressure prediction while drilling. Arab J Geosci 12(18):1–13
4. Ahmed A, Elkatatny S, Abdulraheem A (2021a) Real-time static Poisson’s ratio prediction of vertical complex lithology from drilling parameters using artificial intelligence models. Arab J Geosci 14(6):1–13
5. Ahmed A, Elkatatny S, Gamal H, Abdulraheem A (2021b) Artificial intelligence models for real-time bulk density prediction of vertical complex lithology using the drilling parameters. Arab J Sci Eng (47):1–14, 10993–11006 (2022). https://doi.org/10.1007/s13369-021-05537-3
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