Wavelet transforms and hybrid neural nets for improved pore fluid prediction and reservoir properties estimation
Author:
Affiliation:
1. Shell International E&P Company, Houston, TX
2. Shell EP Americas, New Orleans, LA
Publisher
Society of Exploration Geophysicists
Link
https://library.seg.org/doi/pdf/10.1190/1.1851131
Reference9 articles.
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2. Lashgari, B., 1991, Expert Systems in Exploration (SEG Geophysics Development No. 3), p 161,SEG, Tulsa
3. Singularity Detection and processing with wavelets, 1992, Mallat, S. and Hwang, W. L., IEEE transactions on Information theory, vol. 38, No.2
4. Dessing, F., J., Phd Thesis, (1997), Laboratory Of Seismic & Acoustics, Delft University.
5. Interpretation of incised valleys using new 3-D seismic techniques: A case history using spectral decomposition and coherency
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2. Inverse Theory, Artificial Neural Networks;Encyclopedia of Solid Earth Geophysics;2021
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4. High-resolution seismic signals from band-limited data using scaling laws of wavelet transforms;GEOPHYSICS;2009-03
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