Hydraulic fracture design and optimization of gas storage wells

Journal of Petroleum Science and Engineering

Volumn 23, Issue 3-4, 1999, Pages 161-171

  Mohaghegh, Shahab ^a   Balanb, Bogdan ^b   Platon, Valeriu ^c   Ameri, Sam ^a  

^a WEST VIRGINIA UNIVERSITY   (United States)

^b SCHLUMBERGER   (United States)

^c BAKER ATLAS   (United States)

Author keywords

Gas storage; Hydraulic fracturing; Neural networks

Indexed keywords

VIRTUAL INTELLIGENCE;

GENETIC ALGORITHMS; HYDRAULIC FRACTURING; NEURAL NETWORKS; OPTIMIZATION; PETROLEUM RESERVOIR EVALUATION;

NATURAL GAS WELLS;

HYDRAULIC FRACTURING; NATURAL GAS; NEURAL NETWORK; STORAGE;

EID: 0033215911     PISSN: 09204105     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0920-4105(99)00014-5     Document Type: Article

References (5)

1. Holland, J., 1975. Adaptation in Natural and Artificial Systems. University of Michigan Press.
2. McVey, D.S., Mohaghegh, S., Aminian, K., Ameri, S., 1996. Identification of parameters influencing the response of gas storage wells to hydraulic fracturing with the aid of a neural network. SPE Computer Applications Journal, Apr., 54-57.
3. Michalewicz, Z., 1992. Genetic Algorithms+Data Structure=Evolution Programs. Springer-Verlag, ISBN 3-540-55387-8, 1992.
4. Mohaghegh S., Ameri S., Arefi R. Virtual measurement of heterogeneous formation permeability using geophysical well log responses. The Log Analyst. 37(2):1996;32-39.
5. Mohaghegh, S., Aminian, K., Ameri, S., McVey, D.S., 1996b. Predicting well stimulation results in a gas storage field in the absence of reservoir data, using neural networks. SPE Reservoir Engineering Journal, Nov., 54-57.