• Gravity data interpretation using the particle swarm optimisation method with application to mineral exploration

    • Fulltext


        Click here to view fulltext PDF

      Permanent link:

    • Keywords


      Particle swarm optimisation; second moving average; discrepancy; depth; mineral exploration.

    • Abstract


      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.

    • Author Affiliations


      Khalid S Essa1 Marc Munschy2

      1. Department of Geophysics, Cairo University, Giza, Egypt.
      2. Institut de Physique du Globe de Strasbourg, EOST, CNRS, University of Strasbourg, Strasbourg, France.
    • Dates

  • Journal of Earth System Science | News

    • Editorial Note on Continuous Article Publication

      Posted on July 25, 2019

      Click here for Editorial Note on CAP Mode

© 2017-2019 Indian Academy of Sciences, Bengaluru.