Evaluation of Traditional and Nontraditional Optimization Techniques for Determining Well Parameters from Step-Drawdown Test Data
Publication: Journal of Hydrologic Engineering
Volume 11, Issue 6
Abstract
Adequate knowledge of the hydraulic characteristics of production wells is indispensable for the proper development and management of wells and for the selection of suitable pumps. In this study, the characteristic hydraulic parameters of production wells were determined by the widely used graphical analysis of step-drawdown pumping test data as well as the two traditional gradient-based nonlinear optimization techniques (viz., Levenberg–Marquardt and Gauss–Newton) and the nontraditional optimization technique, genetic algorithm. Three stand-alone and interactive computer programs were developed to optimize the hydraulic parameters of production wells by these numerical techniques. The efficacy and robustness of the developed computer codes were examined using eleven sets of step-drawdown data from diverse hydrogeologic conditions. The results of this study revealed that all the three numerical techniques yielded superior well parameters with lower values of root-mean-square errors (RMSE) for all the eleven data sets compared to the parameters obtained by the graphical method. The values of the exponent ranged from 1.2 to 6.0, which gave minimum RMSE values. Furthermore, it was found that both the Gauss–Newton and Levenberg–Marquardt techniques are sensitive to the initial guess values of well parameters. It is concluded that both the traditional and nontraditional numerical techniques offer an efficient and reliable tool for the determination of well parameters with a greater accuracy and better insight.
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Acknowledgments
The writers are very grateful to the two anonymous referees for providing constructive comments that improved the article.
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Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 11 • Issue 6 • November 2006
Pages: 617 - 630
Copyright
© 2006 ASCE.
History
Received: May 10, 2004
Accepted: Feb 8, 2005
Published online: Nov 1, 2006
Published in print: Nov 2006
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