Application of regional aeromagnetic data in targeting detailed fracture zones

Airo, Meri-Liisa; Wennerström, Marit

doi:10.1016/j.jappgeo.2010.03.003

Cited by 19 publications

(5 citation statements)

References 7 publications

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“…We cannot as yet confirm these as dykes due to a lack of appropriate geologic information. Best (1988) and Airo and Wennerström (2010) see similar features in the region immediately to the northeast of this study that they interpret to be faults in the sediments and within the metamorphic basement.…”

Section: Integration Of the Data Sets And Interpretationsupporting

confidence: 64%

Detailed topography of the Devonian Grosmont Formation surface from legacy high-resolution seismic profiles, northeast Alberta

2014

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The Devonian Grosmont Formation in northeastern Alberta, Canada, is the world’s largest accumulation of heavy oil in carbonate rock with estimated bitumen in place of [Formula: see text]. Much of the reservoir unconformably subcrops beneath Cretaceous sediments. This is an eroded surface modified by kartstification known as the Sub-Mannville Unconformity (SMU). We studied the reanalysis and integration of legacy seismic data sets obtained in the mid-1980s to investigate the structure of this surface. Standard data processing was carried out supplemented by some more modern approaches to noise reduction. The interpretation of these reprocessed data resulted in some key structural maps above and below the SMU. These seismic maps revealed substantially more detail than those constructed solely on the basis of well-log data; in fact, the use of only well-log information would likely result in erroneous interpretations. Although features smaller than about 40 m in radius cannot be easily discerned at the SMU due to wavefield and data sampling limits, the data did reveal the existence of a roughly east–west-trending ridge-valley system. A more minor northeast–southwest-trending linear valley also was apparent. These observations are all consistent with the model of a karsted/eroded carbonate surface. Comparison of the maps for the differing horizons further suggested that deeper horizons may influence the structure of the SMU and even the overlying Mesozoic formations. This suggested that some displacements due to karst cavity collapse or minor faulting within the Grosmont occurred during or after deposition of the younger Mesozoic sediments on top of the Grosmont surface.

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Section: Integration Of the Data Sets And Interpretationsupporting

confidence: 64%

Detailed topography of the Devonian Grosmont Formation surface from legacy high-resolution seismic profiles, northeast Alberta

2014

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“…In this study, the directional gradient, Sobel and Laplacian filters as well as the hillshade and TDR transforms have been selected to demonstrate various feature extraction methods. These operators have been selected as they are commonly applied in lineament detection studies, be it manual or semi-automated, to enhance features prior to detection on a variety of datasets (Smithurst, 1990;Morris, 1991;Maini and Aggarwal, 2009;Airo and Wennerström, 2010;Mallast et al, 2011;Grebby et al, 2012;Hashim et al, 2013;Rahnama and Gloaguen, 2014;Sukumar et al, 2014;Middleton et al, 2015;Mwaniki et al, 2015;Scheiber et al, 2015;Sedrette and Rebaï, 2016;ilhav˝et al, 2016;Thiele et al, 2017;Yeomans et al, 2019). It is worth noting that other methods are available such as the Prewitt and Canny filter, Principal Component Analysis and Hough transforms, among others, which fall out of scope of this study.…”

Section: Filters and Transformsmentioning

confidence: 99%

Application of the tilt derivative transform to bathymetric data for structural lineament mapping

Yeomans

Head

Lindsay

2021

Journal of Structural Geology

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High-resolution bathymetry surveys provide an opportunity to analyse local geological structure where onshore areas a ord limited exposure. Semi-automated lineament detection methods are necessary for areas of large coverage where a manual analysis would be subjective and timeconsuming. However, semi-automated approaches are dependent on e ective feature extraction methods to identify genuine lineaments. This study o ers solutions to common problems that can impede processing methods where sharp steps in the seafloor (e.g. palaeocoastlines) are present. Directional gradient, Sobel and Laplacian filters are explored as well as the hillshade and tilt derivative transform for feature extraction prior to applying an object-based image analysis lineament detection approach. The filtered datasets generally perform poorly with a marked improvement when using the hillshade transform. However, we find the azimuth-invariant tilt derivative, which incorporates a convolved vertical derivative, to be the most successful, identifying lineaments in a range of orientations and across a sharp step in the seafloor.

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“…In a wide-area analysis (thousands to tens of thousands of square meters), surface data can provide useful information for an aeromagnetic map, such as information on large joints or faults (Airo et al 2010;Bruna et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Enhanced and multi-purpose analysis of aeromagnetic anomalies by combining topographic data

Park,

2024

Preprint

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Tie-lines are used in aeromagnetic surveys to detect measurement errors and compensate for insufficient measurement data in the north-south direction. However, increasing the number of tie-lines to improve the accuracy of interpretation can be very challenging. The aim of this study was to overcome this issue by combining aeromagnetic and related multi-parametric data. Therefore, we generated an aeromagnetic map using simple kriging with local varying means (SK-lvm) based on topographic data correlated with the distribution patterns of the aeromagnetic data. The generated aeromagnetic map achieved reduced uncertainties and increased resolution compared with the conventional aeromagnetic map as a result of the interpolation of the magnetic data, which leveraged the dense distribution of the topographic data points and enabled a clearer analysis of geological structures. Generally, topographic and aeromagnetic data were positively correlated with deviating patterns displayed in some regions; however, all the regions shown were classified into Types 1–4 based on the correlation regression equation. Types 1 and 4 showed positive correlations, while Types 2 and 3 exhibited negative correlations with the following characteristics: Type 2 regions are characterized by high altitude and low magnetic anomalies, while Type 3 regions are characterized by low altitude and high magnetic anomalies. The analysis revealed that Type 2 regions are distributed around high-altitude mountainous areas covered with igneous and sedimentary rocks with low magnetic anomalies, whereas Type 3 regions abound with igneous rocks with high magnetic anomalies and mining sites in low-altitude alluvium or coastal areas. Thus, the proposed aeromagnetic map improved resolution and enhanced the reliability of the interpretation (compared with those of a conventional aeromagnetic map) by combining topographic datasets using SK-lvm to process and interpret the comprehensive aeromagnetic survey data. Moreover, the correlation analysis results for the two datasets are expected to serve as useful reference data for determining the characteristic type of rocks distributed in the study area.

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Application of regional aeromagnetic data in targeting detailed fracture zones

Cited by 19 publications

References 7 publications

Detailed topography of the Devonian Grosmont Formation surface from legacy high-resolution seismic profiles, northeast Alberta

Detailed topography of the Devonian Grosmont Formation surface from legacy high-resolution seismic profiles, northeast Alberta

Application of the tilt derivative transform to bathymetric data for structural lineament mapping

Enhanced and multi-purpose analysis of aeromagnetic anomalies by combining topographic data

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