Werner deconvolution for variable altitude aeromagnetic data

Geophysics ◽  
1993 ◽  
Vol 58 (10) ◽  
pp. 1481-1490 ◽  
Author(s):  
Julius S. Ostrowski ◽  
Mark Pilkington ◽  
Dennis J. Teskey
Keyword(s):  
British Columbia ◽  
Linear Function ◽  
Survey Data ◽  
Horizontal Position ◽  
Numerical Instability ◽  
Aeromagnetic Data ◽  
Deconvolution Method ◽  
Aeromagnetic Survey ◽  
Flight Height ◽  
Subsequent Selection

The standard Werner deconvolution method is extended to include the effects of variable sensor altitude but this leads to a deconvolution algorithm that is unstable for slowly changing flight height. By expressing the sensor altitude as a linear function of horizontal position (within a specified window), we show that the numerical instability can be avoided. The subsequent selection and averaging of the raw solutions is controlled by three parameters that can be adjusted to specific survey data characteristics. Results for an aeromagnetic survey over Vancouver Island, British Columbia show that, in comparison with the variable altitude approach, the standard Werner method produces unacceptable errors when applied to variable altitude data.

THE INTERPRETATION OF AEROMAGNETIC SURVEYS FOR HYDROCARBON EXPLORATION

1999 ◽  
Vol 39 (1) ◽  
pp. 494
Author(s):  
I. Kivior ◽  
D. Boyd
Keyword(s):  
Spectral Analysis ◽  
Sedimentary Basins ◽  
Hydrocarbon Exploration ◽  
Petroleum Exploration ◽  
Magnetic Data ◽  
Curve Matching ◽  
Aeromagnetic Data ◽  
Profile Data ◽  
Aeromagnetic Survey ◽  
New Approach

Aeromagnetic surveys have been generally regarded in petroleum exploration as a reconnaissance tool for major structures. They were used commonly in the early stages of exploration to delineate the shape and depth of the sedimentary basin by detecting the strong magnetic contrast between the sediments and the underlying metamorphic basement. Recent developments in the application of computer technology to the study of the earth's magnetic field have significantly extended the scope of aeromagnetic surveys as a tool in the exploration for hydrocarbons. In this paper the two principal methods used in the analysis and interpretation of aeromagnetic data over sedimentary basins are: 1) energy spectral analysis applied to gridded data; and, 2) automatic curve matching applied to profile data. It is important to establish the magnetic character of sedimentary and basement rocks, and to determine the regional magnetic character of the area by applying energy spectral analysis. Application of automatic curve matching to profile data can provide results from the sedimentary section and deeper parts of a basin. High quality magnetic data from an experimental aeromagnetic survey flown over part of the Eromanga/Cooper Basin has recently been interpreted using this new approach. From this survey it is possible to detect major structures such as highs and troughs in the weakly magnetic basement, as well as pick out faults, and magnetic layers in the sedimentary section. The results are consistent with interpretation from seismic and demonstrate that aeromagnetic data can be used to assist seismic interpretation, for example to interpolate between widely spaced seismic lines and sometimes to locate structures which can not be detected from seismic surveys. This new approach to the interpretation of aeromagnetic data can provide a complementary tool for hydrocarbon exploration, which is ideal for logistically difficult terrain and environmentally sensitive areas.

AN AUTOMATIC METHOD OF COMPILATION AND MAPPING OF HIGH‐RESOLUTION AEROMAGNETIC DATA

Geophysics ◽  
1971 ◽  
Vol 36 (4) ◽  
pp. 695-716 ◽  
Author(s):  
B. K. Bhattacharyya
Keyword(s):  
High Resolution ◽  
Magnetic Measurements ◽  
High Sensitivity ◽  
Positional Error ◽  
Automatic Method ◽  
Aeromagnetic Data ◽  
Aeromagnetic Survey ◽  
Machine Method ◽  
Flux Gate ◽  
Definition Of

An automatic method has been developed for compilation of digital aeromagnetic data. This method has been applied to the data obtained during a high‐sensitivity aeromagnetic survey over an area in the Precambrian shield of northeastern Ontario in Canada. With this method, all points of intersection between traverse and base lines are determined automatically and adjusted within the limits of positional error for minimizing differences in magnetic values at the intersections. Then the data are corrected for diurnal variation and leveled to tie the magnetic measurements together. Next, the resulting total field values are contoured with a machine method at a scale of 1:25,000. For such a scale, the minimum contour interval that can be used in the present area is two gammas. However, because of the accuracy of the method of compilation, with a larger scale, it is possible to trace one‐gamma contours. The maps thus compiled have been compared with published aeromagnetic maps of data obtained with conventional flux‐gate and proton‐precession magnetometers. The new maps are vastly superior to the old ones for delineating trends, patterns, and fine features of available detailed geological maps. This superiority is mainly due to the excellent definition of small amplitude anomalies, some of only a few gammas in magnitude, on the high‐resolution magnetic maps.

GROUPING OF LOWER FRASER VALLEY SOILS OF BRITISH COLUMBIA BY NUMERICAL METHODS

1973 ◽  
Vol 53 (4) ◽  
pp. 435-443
Author(s):  
B. KLOOSTERMAN ◽  
L. M. LAVKULICH
Keyword(s):  
British Columbia ◽  
Cluster Analysis ◽  
Survey Data ◽  
Soil Classification ◽  
Data File ◽  
Soil Survey ◽  
Data Sets ◽  
Lower Fraser Valley ◽  
Average Profile ◽  
Fraser Valley

The British Columbia Soil Survey Data File was used to numerically classify soils of the Lower Fraser Valley of British Columbia. The data employed in the numerical-classification procedure were routine soil survey data and this classification was compared with the Canadian Soil Classification System. Three types of soil-profile data sets were used: average surface slice, selected average profile, and average profile. Methods of statistical analysis were cluster analysis and hierarchial grouping analysis. No marked differences in grouping resulted by the two methods of analyses. The average profile method seemed to give better correspondence with the Canadian System of Soil Classification. Consideration of surface layers alone did not correspond with the Canadian Soil Classification. The hierarchical grouping scheme resulted in better defined groups than the cluster analysis approach.

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