scholarly journals Supplemental material: Guides to understanding the aeromagnetic expression of faults in sedimentary basins: Lessons learned from the central Rio Grande rift, New Mexico

Author(s):  
V.J.S. Grauch ◽  
Mark R. Hudson

Geosphere, December 2007, v. 3, p. 596-623, doi: 10.1130/GES00128.1. Plate 1 - Color shaded-relief image of reduced-to-pole (RTP) aeromagnetic data for the central Rio Grande rift, compiled from Sweeney et al. (2002) and Bankey et al. (2006). The colors primarily reflect the broad variations in the data, whereas the illumination (from the west) emphasizes detailed variations, especially linear features associated with faults. Selected geographic, geologic, and interpretative features are labeled. Map projection is NAD27, UTM zone 13, in units of meters. Inset shows locations and names of aeromagnetic survey areas. Map scale 1:250,000. File size is 9.2 MB.

1999 ◽  
Vol 39 (1) ◽  
pp. 494
Author(s):  
I. Kivior ◽  
D. Boyd

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.


Geophysics ◽  
1990 ◽  
Vol 55 (12) ◽  
pp. 1567-1576 ◽  
Author(s):  
J. F. Hermance ◽  
G. A. Neumann

The magnetic variation (MV) technique employs magnetic transients from natural sources in the magnetosphere to delineate geologic structures in the earth’s interior based on their electrical properties. By measuring only the magnetic field at each site, and not the electric field as required for magnetotelluric (MT) studies, a site can be set up quickly, and often in places which might be quite unsuitable for MT measurements. This generally allows one to execute MV surveys in culturally developed areas or in rugged and logistically difficult terrain at much closer site spacings than those used for conventional MT surveys. Procedures for acquiring and processing MV field data are straightforward, as are methods for inverting data to obtain plausible geophysical models. Using a new 2-D generalized inverse algorithm which employs singular value damping of the Lanczos (or SVD) inverse, we apply the MV technique to determine the basement topography beneath a sequence of 11 remote referenced MV sites from an east‐west profile transecting one of the sedimentary basins of the Rio Grande rift—the San Antonio graben in the southern portion of the Socorro Basin in central New Mexico. Band‐limited data at 50 and 63 s were adequate to delineate the major features of the basin: its lateral margins, its asymmetrical cross‐section with basement dipping sharply to the west, and a large vertical displacement along the western boundary fault of the graben. Our results suggest, therefore, that reconnaissance surveys can be optimized to capture only those data needed to resolve such features. This strategy significantly affects the cost‐effectiveness of the method as a complement to other geophysical techniques.


2013 ◽  
Vol 2013 ◽  
pp. 1-26 ◽  
Author(s):  
V. J. S. Grauch ◽  
C. A. Ruleman

Combined interpretation of aeromagnetic and LiDAR data builds on the strength of the aeromagnetic method to locate normal faults with significant offset under cover and the strength of LiDAR interpretation to identify the age and sense of motion of faults. Each data set helps resolve ambiguities in interpreting the other. In addition, gravity data can be used to infer the sense of motion for totally buried faults inferred solely from aeromagnetic data. Combined interpretation to identify active faults at the northern end of the San Luis Basin of the northern Rio Grande rift has confirmed general aspects of previous geologic mapping but has also provided significant improvements. The interpretation revises and extends mapped fault traces, confirms tectonic versus fluvial origins of steep stream banks, and gains additional information on the nature of active and potentially active partially and totally buried faults. Detailed morphology of surfaces mapped from the LiDAR data helps constrain ages of the faults that displace the deposits. The aeromagnetic data provide additional information about their extents in between discontinuous scarps and suggest that several totally buried, potentially active faults are present on both sides of the valley.


2016 ◽  
Author(s):  
Cody L. MacCabe ◽  
◽  
Greg L. Melton ◽  
Richard Wendlandt

2017 ◽  
Author(s):  
Lon D. Abbott ◽  
◽  
Rebecca M. Flowers ◽  
James R. Metcalf ◽  
Sarah Falkowski

2019 ◽  
Author(s):  
Benjamin J. Drenth ◽  
◽  
V.J.S. Grauch ◽  
Kenzie J. Turner ◽  
Brian D. Rodriguez ◽  
...  

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