1887
Volume 28, Issue 1-2
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

A wide variety of numerical procedures in potential field geophysics require data modelled on a regular grid. However, airborne data tend to be highly sampled along the flight line and sparsely sampled in the perpendicular direction.

A gridding method commonly called ‘bi-cubic spline’ is widely used in potential field geophysics. Standard bi-cubic spline methods used on aeromagnetic data produce artefacts when a geological feature’s ‘line of strike’ is not perpen-dicular to the direction of the acquisition line. This method has a tendency to break up thin elongated magnetic anomalies, at an oblique angle, into a series of bulls eye artefacts. A method of finding local anomalies and their strike along lines based upon minimum variance principles reduces these effects. This technique has significant impact on the quality of output grids.

In association with the Magnetic Image Project (MAGMAGE) developed by Gunn and collaborators, that involved work on complex attributes of aeromagnetic anomalies, the gridding of phase posed some unique problems. Raw phase is a spiralling function which is periodic and cyclic. Unwrapping of the phase, therefore, is necessary to give a spatially coherent grid for interpretation.

By focussing on two developments in gridding — trending in a bi-cubic spline method and unwrapping of cyclic data — these methods are shown to increase the accuracy of representation of actual data being interpolated. Case studies of these solutions are presented using the INTREPID geophysical processing and visualisation system.

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1997-03-01
2026-01-17
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References

  1. Briggs, I.C., 1974, Machine contouring using minimum curvature: Geophysics 39, 39-48.
  2. Brindt, L. and Hauska, H., 1985, Direction dependent interpolation of aeromagnetic data: Eleventh International Symposium on Machine Processing of Remotely Sensed Data, Purdue University, Indiana USA.
  3. Cambois, G. and Stoffa, P., 1993, Surface-consistent phase decomposition in the log/Fourier domain: Geophysics 58, 1099-1 111.
  4. Crain, I. K., 1970, Computer interpolation and contouring of two dimensional data: a review: Geoexploration 8, 71-86.
  5. De Boor, C, 1962, Bi-cubic spline interpolation: Journal of Mathematics and Physics 41, 212-218.
  6. Dreyer, H. and Naudy, H., 1967, Non-linear filtering applied to aeromagnetic profiles: Paper presented at the EAEG meeting, Stockholm.
  7. Fraser, D.C., Fuller, B.D. and Ward, S.H., 1966, Some numerical techniques for appli-cation in mining exploration: Geophysics 31, 1066-1077.
  8. Gunn, P., FitzGerald, D., Yassi, N. and Dart, P., 1997, New algorithms for visually enhancing aeromagnetic geophysical data: Exploration Geophysics, this volume.
  9. Hansen, R.O., 1993, Interpretive gridding by anisotropic kriging: Geophysics 58, 1491-1497.
  10. Rasmussen, K.L. and Sharma, P.V., 1979, Bicubic spline interpolation: a quantitative test of accuracy and efficiency: Geophysical Prospecting 27, 394-408.
  11. Smith, W.H.F. and Wessel, P., 1990, Gridding with continuous curvature spline in tension: Geophysics 55, 293-303.
  12. Taner, M.T., Koehler, F. and Sheriff, R.E., 1979, Complex seismic trace analysis: Geophysics 44, 1041-1063.
  13. Watson, D., 1994, nngridr: an implementation of natural neighbour interpolation. Volume 1, David Watson Publishers, Claremont W.A., Australia.
/content/journals/10.1071/EG997204
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  • Article Type: Research Article
Keyword(s): gridding; interpolation; INTREPID; phase unwrapping; spline; trend-spline

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