Gravity anomaly separation by Wiener filtering

Abstract

We introduce a gravity anomaly separation method based on frequency‐domain Wiener filtering. Gravity anomaly separation can be effected by such wavelength filtering when the gravity response from the geologic feature of interest (the signal) dominates one region (or spectral band) of the observed gravity field’s power spectrum. The Wiener filter is preferable to a conventional band‐pass filter because geologic information from the study area can be incorporated to a greater extent in specifying the filter’s transfer function. Our method differs from previous Wiener filtering schemes in that it provides, through direct modeling of known geology (e.g., outcrop and borehole data), a more objective estimate of the signal power spectrum required for defining the transfer function of the filter. We illustrate the technique first with synthetic data, and then with a field example from the southern Paradox basin. The Paradox basin example reveals the limitation inherent to all wavelength filtering which results from spectral overlap between the gravity signal and the spectral contributions of other geologic sources. In the study area, significant spectral overlap occurs between the gravity effects of sources in the Precambrian basement and the gravity signal arising from the density contrast across the Mississippian‐Pennsylvanian interface.

Density variations within the south polar layered deposits of Mars

“…Here we use the gravity residuals outside the SPLD to construct a Wiener filter to characterize the spectral nature of the residual gravity anomalies outside the SPLD that likely have a source in the crust or mantle. We adapted the approach of Pawlowski and Hansen [1990], and briefly describe our procedures as follows.…”

Gravity method for investigating the geological structures associated with W–Sn polymetallic deposits in the Nanling Range, China

“…Field-separation are commonly implemented in the Fourier domain by using various frequency filtering functions, such as the upward continuation (Nettleton, 1954), matched filtering (Spector and Grant, 1970), and Wiener filtering (Pawlowski and Hansen, 1990), etc. In the last decades, multi-resolution analysis based on wavelet transform (MAWT) (Mallat, 1989), acting as a breakthrough for Fourier transformation, has been introduced to decompose potential fields ( , ) f x y into a set of details (D j , j=1, 2, .., n) and a low-resolution approximation (A n ) (Fedi and Quarta, 1998;Hou and Yang, 1997).…”

Application of magnetic amplitude inversion in exploration for volcanic units in a basin environment

“…With the clear identification of different source depths, we can proceed to carry out an anomaly separation by using a Wiener filter (Pawlowski and Hansen, 1990) to extract the anomaly corresponding to the second ensemble, which is interpreted as the volcanic units. We use the ratio of the power spectrum of the second ensemble over the total power of the data as the transfer function of the Wiener filter…”