Reservoir porosity prediction from 3-D seismic data using neural networks

1997 SEG Annual Meeting

Volumn , Issue , 1997, Pages 842-845

  Himmer, Phillip ^a   Link, Curtis ^a  

^a UNIVERSITY OF MONTANA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GEOLOGIC MODELS; GEOPHYSICAL PROSPECTING; NEURAL NETWORKS; PETROLEUM RESERVOIRS; SEISMIC RESPONSE; SEISMIC WAVES; WELL LOGGING;

3D SEISMIC DATA; AMPLITUDE INFORMATION; BACK PROPAGATION NEURAL NETWORKS; HETEROGENEOUS REGION; HISTORY MATCHING; INTERPOLATION TECHNIQUES; RESERVOIR POROSITY; RESERVOIR SIMULATION;

POROSITY;

EID: 1842503535     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1190/1.1886145     Document Type: Conference Paper

References (6)

1. Campen Consultants Inc., 1996. personal communication.
2. Link, CA., 1995, Artificial neural networks for lithology prediction and reservoir characterization: Proceedings of the SPIE: Mathematical Methods in Geophysical Imaging III, 2571, 163-174.
3. Porter. K. W. (in press), Geologic data in a reservoir characterization, Sawtooth Formation, NE Rabbit Hills field, Blaine County, Montana: Montana Bureau of Mines and Geology Open-File Report 354.
4. Rogers S., J., Chen H., C.; Kopaska-Merkel D., C.; and Fang J. H., 1995, Predicting permeability from pomsity urine artificial neural networks: AAPG Bulletin, 79 12, 1786-1797.
5. Schlumberger, 1972, Log Interpretation Volume I: Principles: Schlumberger Limited.
6. Sheriff R., 1992, Reservoir characterization investigations in Geophysics No. 7, SEG.