Effective Residual and Regional Gravity Anomaly Separation - Using 1-D & 2-D Stationary Wavelet Transform

Abstract

Numerous studies on capabilities of de-noising and separation by wavelet were performed, and their all aims more and less was elimination of possible largest nongeological factors, noise, and to achieve pure regional effects free from residuals. De-noising could be used for removal of non-desired effects like latitude, terrain, tides, drift etc., from our desired portion of data as target. Separations of anomalies that are not of interest conclude shallow structure is suitable to be optimal. Hence detection and removal of ever larger surface anomalies to obtain optimal separation is of interest. At up to now studies, large deviation of primarily original signal has been prevented. In this paper controlling factors which limit the overall deviation of transformed signal from the original one have been replaced with two new parameters that simultaneously cause extracting the maximum surplus signals, residuals, and also preserving the original form ever possible. Results of artificial models along with application of separation to real data indicate the usefulness of discrete stationary wavelet transform in order to optimal separation of anomalies with various wavelengths.

The shallow and deep crustal structure in Zagros from inversion and forward modeling: insights from the application of Moho-free Bouguer anomaly

“…Traditionally, researchers apply separation techniques to divide shallow and deep effects (Gupta and Ramani, 1980;Pawlowski and Hansen,1990;Mousavi et al, 2013). For having only one set of wavelengths, either short or long, filtering is also applied which is somewhat geological-wise erroneous.…”