The use of soft computing techniques as data preprocessing and postprocessing in permeability determination from well log data
Wong, K.W., Gedeon, T. and Fung, C.C. (2002) The use of soft computing techniques as data preprocessing and postprocessing in permeability determination from well log data. In: Wong, P.M., Aminzadeh, F. and Nikravesh, M., (eds.) Soft Computing for Reservoir Characterization and Modeling. Physica-Verlag, Heidelberg, pp. 243-271.
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The uses of soft computing techniques comprising artificial neural networks, fuzzy logic and genetic algorithms are emerging for the building of permeability interpretation models in well log data analysis. Regardless of which soft computing techniques are used, they rely on a set of core permeability data to give a better understanding of the formation. However uncertainties and errors with the core permeability data may undetermined the accuracy of permeability determination. This paper examines the problems that could possibly appear in the core permeability data. In most cases, data preprocessing and postprocessing are required to ensure that the permeability determination is successful. In this paper, soft computing techniques that are mainly based on fuzzy and neural networks approaches are used to assist the preprocessing and post processing stages thereby improving the overall accuracy.
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|Murdoch Affiliation:||School of Information Technology|
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