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—We have developed a least-squares minimization approach to depth determination from magnetic data. By defining the anomaly value T(0) at the origin and the anomaly value T(N) at any other distance (N) on the profile, the problem of depth determination from magnetic data has been transformed into finding a solution to a nonlinear equation of the form f(z)=0. Formulas have been derived for a sphere, horizontal cylinder, dike, and for a geologic contact. Procedures are also formulated to estimate the effective magnetization intensity and the effective magnetization inclination. A scheme for analyzing the magnetic data has been formulated for determining the model parameters of the causative sources. The method is applied to synthetic data with and without random errors. Finally, the method is applied to two field examples from Canada and Arizona. In all cases examined, the estimated depths are found to be in good agreement with actual values. [ABSTRACT FROM AUTHOR]

This paper describes a new method based on the particle swarm optimisation (PSO) technique for interpreting the second moving average (SMA) residual gravity anomalies. The SMA anomalies are deduced from the measured gravity data to eradicate the regional anomaly by utilising filters of consecutive window lengths (s-value). The buried structural parameters are the amplitude factor (A), depth (z), location (d) and shape (q) that are estimated from the PSO method. The discrepancy between the measured and the predictable gravity anomaly is estimated by the root mean square error. The PSO method is applied to two different theoretical and three real data sets from Cuba, Canada and India. The model parameters inferred from the method developed here are compared with the available geological and geophysical information. [ABSTRACT FROM AUTHOR]