The montaj Geophysics™ extension provides a range of filters and statistical tools for working with large volume geophysical data.
Spatial 1D Filters enable field geophysicists to process data by applying a variety of space domain filters (linear and non-linear).
The 1D FFT Filter enables you to apply a variety of Fourier domain filters to onedimensional (line) potential field and other data.
A variety of geostatistical tools provide the ability for summary and advanced statistics, including histogram, scatter and triplot analysis, and the ability to subset data based on code or map group classification.
Spatial 1D Filters
Smooth data, with or without nonlinear filtering, using spatial one dimensional filters. The montaj Geophysics extension includes these 1D filters:
- High-pass filter applies a high-pass (sharpening) filter to a channel
- Low-pass filter applies a low-pass (smoothing) filter to a channel
- Bandpass filter applies a filter that removes features longer than the long wavelength cutoff and shorter than the short-wavelength cutoff
- Convolution filter applies space-domain averaging filter to a channel. The filter can be defined in a filter file or in a comma delimited string
- Difference filter calculates differences between values in a channel. The common fourth difference can be calculated by specifying four differences, which is useful for identifying noise,
- Polynomial filter calculates n’th (maximum nine) order trend of a data channel by (least square) best-fit polynomial. The trend is then evaluated and placed in a new channel. An optional residual channel (input trend) may also be created
- B-Spline filter calculates a B-Spline interpolation of data in a channel. A B-Spline allows you to control the smoothness of the spline and the tension applied to the ends of the spline
- Linear Regression filter fits a least-square linear regression to a set of marked data in a channel and reports the slope and intercept.
1D Non-Linear Filters
Use 1D Non-Linear Filters to remove very short wavelength, but high amplitude features from data. It is often thought of as a noise spike-rejection filter, but it can also be effective for removing short wavelength geological features, such as signal from surficial features.
The 1D Non-Linear Filter is used to locate and remove data that is recognized as noise. The algorithm is ‘nonlinear’ because it looks at each data point and decides if that data is noise or a valid signal. If the point is noise, it is simply removed and replaced by an estimate based on surrounding data points. Parts of the data that are not considered noise are not modified at all.
Fourier Filters can be used to:
- Perform profile-based processing for interpretation and modeling purposes
- Rapidly apply filters to one or more lines of data
- Interactively select filtering parameters, display power spectra and identify optimal filters for processing and interpretation
- Automatically sample to distance or optionally to fiducials.