Self‐potential data interpretation using standard deviations of depths computed from moving‐average residual anomalies

ABSTRACT We have developed a least‐squares minimization approach to determine simultaneously the shape (shape factor) and the depth of a buried structure from self‐potential (SP) data. The method is based on computing the standard deviation of the depths determined from all moving‐average residual anomalies obtained from SP data, using filters of successive window lengths for each shape factor. The standard deviation may generally be considered a criterion for determining the correct depth and shape factor of the buried structure. When the correct shape factor is used, the standard deviation of the depths is less than the standard deviations computed using incorrect shape factors. This method is applied to synthetic data with and without random errors, complicated regionals and interference from neighbouring sources, and is tested on a known field example from Turkey. In all cases, the shape and depth solutions obtained are in a good agreement with the actual values.