Well Parameters' Estimation using Traditional and Non-traditional Methods

Knowledge of accurate values of well parameters like well loss coefficient (C) and aquifer loss coefficient (B) are important for successful modeling and proper management of ground water resources. In the present paper, B and C were determined using various traditional and nontraditional methods. These methods include traditional gradient-based nonlinear optimization technique like Gauss-Newton (GN) and non-traditional optimization techniques like Particle swarm optimization (PSO) and Genetic-Algorithm (GA). The study found that PSO and GA depend on search space but are non-sensitive to initial guesses, whereas, GN is sensitive to the initial guesses of well parameters. It is also concluded that PSO, which is motivated by social behaviour of organisms such as bird flocking and fish schooling, gives better forecasts of B and C when the data is discreet and full of noise.