Geophysical Compilation/QC/Processing/Enhancement

Potential field data (principally gravity and magnetic data) provide a window to the basement that can cover a wide area with uninterrupted data at constant resolution. Such “map view” interpretation contrasts with the “cross section view” interpretation conventionally used in the petroleum industry. But the combination is very significant for extracting more geological information more quickly than is possible with either dataset on its own. This is the basis of the FrOG Tech approach that has been developed over many years.

FrOG Tech specialises in compiling, evaluating, correcting, stitching and enhancing multi-vintage DEM, gravity and magnetic data of various data types (eg, line data, digitised contours, marine and onshore).

Compilation

For most of the world there are a series of publically available geophysical datasets at a fairly coarse scale. In addition, many areas also include proprietry surverys ranging from paper copies to GIS ready information. One of FrOG Tech's first steps in any of our projects is to compile all of the available geophyscial datasets in a single GIS project and within a  common datum and projection.

QC

An important component of FrOG Tech's services to our clients is the ability to provide quality control (QC) evaluating and correcting field data to provide immediate feedback to our clients on where reacquisition/recalibration is required.

Stitching

However, individual geophysical surveys are only so useful, so once the various datasets are compiled and have passed through FrOG Tech's QC process they are stitched together to form a seamless dataset covering the entire study area. In a typical FroG Tech project, we will stitch together 20-30 (or more depending on the size of the project area) different datasets. Where datasets overlap, FrOG Tech selects the best quality dataset to produce the final stitched gravity or magnetic grid.

Enhancement

A summary of image enhancement techniques used to achieve various outcomes includes:

  • Enhancement of near surface features (i.e. intrabasinal features) – 1VD (first vertical derivative).
  • Reduction of noise in data – upward continuation (using a cell size distance).
  • Enhancement of deep features (i.e. basement) – Low pass filter  (using 20-100km depending on depth of interest), or large distance upward continuation filter.

For more information and examples see