S-wave velocity inversion and prediction using a deep hybrid neural network
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
https://link.springer.com/content/pdf/10.1007/s11430-021-9870-8.pdf
Reference85 articles.
1. Akhundi H, Ghafoori M, Lashkaripour G R. 2014. Prediction of shear wave velocity using artificial neural network technique, multiple regression and petrophysical data: A case study in Asmari Reservoir (SW Iran). Open J Geo, 04: 303–313
2. 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. J Nat Gas Sci Eng, 38: 373–387
3. Araya-Polo M, Jennings J, Adler A, Dahlke T. 2018. Deep-learning tomography. Leading Edge, 37: 58–66
4. Asoodeh M, Bagheripour P. 2012. Prediction of compressional, shear, and stoneley wave velocities from conventional well log data using a committee machine with intelligent systems. Rock Mech Rock Eng, 45: 45–63
5. Azadpour M, Saberi M R, Javaherian A, Shabani M. 2020. Rock physics model-based prediction of shear wave velocity utilizing machine learning technique for a carbonate reservoir, southwest Iran. J Pet Sci Eng, 195: 107864
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