Predicting Formation Pore-Pressure from Well-Log Data with Hybrid Machine-Learning Optimization Algorithms
Author:
Funder
Tomsk Polytechnic University
Publisher
Springer Science and Business Media LLC
Subject
General Environmental Science
Link
https://link.springer.com/content/pdf/10.1007/s11053-021-09852-2.pdf
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3. Ahmed, S., Mahmoud, A. A., Elkatatny, S., Mahmoud, M., & Abdulraheem, A. (2019). Prediction of pore and fracture pressures using support vector machine. Paper presented at the international petroleum technology conference. https://doi.org/10.2523/IPTC-19523-MS
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5. Anemangely, M., Ramezanzadeh, A., & Tokhmechi, B. (2017). Shear wave travel time estimation from petrophysical logs using ANFIS-PSO algorithm: A case study from Ab-Teymour Oilfield. Journal of Natural Gas Science and Engineering, 38, 373–387.
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