Soft computing: Tools for intelligent reservoir characterization (IRESC)

1999 SEG Annual Meeting

Volumn , Issue , 1999, Pages

  Nikravesh, Masoud ^a   Levey, Raymond A ^a   Adams, Roy D ^a   Ekart, D D ^a  

^a UNIVERSITY OF UTAH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BOREHOLES; FUZZY INFERENCE; GEOPHYSICAL PROSPECTING; MAPPING; OIL FIELD EQUIPMENT; PATTERN RECOGNITION; SEISMIC RESPONSE; SEISMIC WAVES; SOFT COMPUTING;

CLUSTERING TECHNIQUES; CONVENTIONAL TECHNIQUES; INTEGRATED METHODOLOGY; NEURAL NETWORK CLUSTERING; NON-LINEAR RELATIONSHIPS; PROBABILISTIC REASONING; RESERVOIR CHARACTERIZATION; RESERVOIR CONNECTIVITIES;

FUZZY LOGIC;

EID: 84978501556     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. Aminzadeh, F. and S. Chatterjee, Applications of clustering in exploration seismology, Geoexploration, 23 (1984/85) 147-159.
2. Nikravesh, M., B. Novak, and F. Aminzadeh, Data mining and fusion with integrated neuro-fuzzy agents: Rock properties and seismic attenuation, JCIS'98, The Fourth Joint Conference on Information Sciences, North Carolina, USA, October 23-28, 1998.
3. Nikravesh, M., and Aminzadeh, F., Knowledge discovery from data bases: Intelligent data mining, FACT Inc. and LBNL Proposal, submitted to SBIR-NASA, 1997.
4. Nikravesh, M. "Mining and fusion of petroleum data with fuzzy logic and neural network agents", CopyRight© Report, LBNL-DOE, ORNL-DOE, and DeepLook Industry Consortium, 1998.
5. Boadu, F. K., Rock properties and seismic attenuation; Neural network analysis, Pure Applied Geophysics, 149(1997), pp. 507-524.
6. Nikravesh, M., Neural network knowledge-based modeling of rock properties based on well log databases, SPE 46206, 1998 SPE Western Regional Meeting, Bakersfield, California, 10-13 May, 1998.
7. Chawathe, A., A. Quenes, and W. W. Weiss, Interwell property mapping using crosswell seismic attributes, SPE 38747, SPE Annual Technical Conference and Exhibition, San Antonio, TX, 5-8 Oct. 1997
8. Yoshioka, K, N. Shimada, and Y. Ishii, Application of neural networks and cokriging for predicting reservoir porosity-thickness, GeoArabia, Vol 1, No 3, 1996.
9. Schuelke, J. S., J. A. Quirein, J. F. Sarg,, D. A. Altany, and P. E. Hunt, Reservoir architecture and porosity distribution, Pegasus field, West Texas-An integrated sequence stratigraphic-seismic attribute study using neural networks, SEG'97 meeting, Dallas, TX 1997.
10. Monson G. D., and J. A. Pita, Neural network prediction of pseudo-logs for net pay and reservoir property interpretation: Greater Zafiro field area, Equatorial Guinea, SEG'97 meeting, Dallas, TX 1997.
11. Hecht-Nielsen, R., Theory of backpropagation neural networks, presented at IEEE Proc., Int. Conf. Neural Network, Washington DC, 1989.
12. Zadeh, L. A., Fuzzy sets, Information and Control, 8, 1965, 338-353.
13. Kohonen, T. Self-Organizing Maps, Second Edition, Springer, 1997.
14. Lin, C. T., C. S. G. Lee, Neural fuzzy systems, Prentice Hall, 1996.
15. The Math Works, Natick, 1995.
16. Adams, R. D., J. W. Collister, D. D. Ekart, R. A. Levey, and M. Nikravesh, Evaluation of gas reservoirs in collapsed paleocave systems, Ellenburger group, Perminan basin, Texas, AAPPG Annual Meeting, San Antonio, Tx, 11-14 April, 1999.
17. Levey, R., M. Nikravesh, R. Adam, s, D. Ekart, Y. Livant, S. Snelgrove, J. Cllister, Evaluation of fractured and paleocave carbonate reservoirs, AAPPG Annual Meeting, San Antonio, Tx, 11-14 April, 1999.