Permeability Determination Using Neural Networks in the Ravva Field, Offshore India

SPE Reservoir Engineering (Society of Petroleum Engineers)

Volumn 1, Issue 2, 1998, Pages 99-104

  Wong, P M ^a   Henderson, D J ^a   Brooks, L J ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORK; OIL RESERVOIR; PERMEABILITY; WELL LOGGING;

HYDROCARBON RESERVOIR; NEURAL NETWORK; NEURAL NETWORKS; OIL AND GAS FIELDS; PERMEABILITY;

EID: 0031670319     PISSN: 08859248     EISSN: None     Source Type: Journal    
DOI: 10.2118/38034-pa     Document Type: Article

References (18)

1. Kozeny, J : "Uber Kapillare Leitung des Wassers im Boden Sitzungsberichte," Royal Academy of Science, Vienna, Pro Class I (1927) 136, 271.
2. Carmen, P.C.: "Fluid Flow Through Granular Beds," Trans. of the American Inst. of Chemical Engineers (1937) 15, 150.
3. Bateman, R.M.: Open-Hole Log Analysis and Formation Evaluation, IHRDC, Boston (1985).
4. Wendt, W.A., Sakurai, S. and Nelson, P.H.: "Permeability Prediction from Well Logs using Multiple Regression," Reservoir Characterization, L.W. Lake and H.B. Carroll, Jr. (eds.), Academic Press Inc., Orlando, FL, (1986) 181-222.
5. Jian, F.X., et al.: "A Genetic Approach to the Prediction of Petrophysical Properties," J. of Petroleum Geology (1994) 17, No. 1, 71.
6. Size, W.B.: Use and Abuse of Statistical Methods in the Earth Sciences, Oxford U. Press, New York City (1987).
7. Malki, H.A., Baldwin, J.L., and Kwari, M.A.: "Estimating Permeability by the Use of Neural Networks in Thinly Bedded Shaly Gas Sands," SPECA (April 1996), 58.
8. Balan, B., Mohaghegh, S., and Ameri, S.: "State-of-the-Art in Permeability Determination from Well Log Data: Part 1 - A Comparative Study, Model Development," paper SPE 30978 presented at the 1995 SPE Eastern Regional Conference and Exhibition, Morgantown, West Virginia, 17-21 September.
9. Huang, Z., et al.: "Permeability Prediction with Artificial Neural Network Modelling in the Venture Gas Field, Offshore Eastern Canada," Geophysics (1996) 61, No. 2, 422.
10. Rogers, S.J., et al.: "Predicting Permeability from Porosity Using Artificial Neural Networks," American Assn. of Petroleum Geologists Bull. (1995) 79, No. 12, 1786.
11. Wong, P.M., Taggart, I.J., and Gedeon, T.D.: "Use of Neural Network Methods to Predict Porosity and Permeability of a Petroleum Reservoir," AI Applications (1995) 9, No. 2, 27.
12. Wong, P.M., Taggart, I.J., and Jian, F.X: "A Critical Comparison of Neural Networks and Discriminant Analysis in Lithofacies, Porosity and Permeability Predictions," J. of Petroleum Geology (1995) 18, No. 2, 191.
13. Dayoff, J.E.: Neural Network Architectures: An Introduction, Van Nostrand Reinhold, New York City (1990).
14. Lippmann, R.P.: "Pattern Classification Using Neural Networks," IEEE Communication Magazine (1989) 27, No. 11, 47.
15. Widrow, B. and Lehr, M. A.: "30 Years of Adaptive Neural Networks: Perceptron, Madaline and Backpropagation," Proc. of IEEE (1990) 78, No. 9, 1415.
16. Wong, P.M., Gedeon, T.D., and Taggart, I.J.: "An Improved Technique in Porosity Predictions: A Neural Network Approach," IEEE Trans. on Geoscience and Remote Sensing (1995) 33, No. 4, 971.
17. Gedeon, T.D., Wong, P.M., and Harris, D: "Balancing Bias and Variance: Network Topology and Pattern Set Reduction Techniques," From Natural to Artificial Neural Computation: Lecture Notes in Computer Science, J. Mira and F. Sandoval (eds.), 930, Springer-Verlag, New York City (1995) 551-558.
18. Wong, P.M. and Gedeon, T.D.: "A New Method to Detect and Remove the Outliers in Noisy Data using Neural Networks: Error Sign Testing," International J. of Systems Research and Information Science (1995) 7, No. 1, 55.