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Enhancement of Potential Field Source Boundaries Using the Hyperbolic Domain (Gudermannian Function)
by
Alvandi, Ahmad
, Ardestani, Vahid E.
, Su, Kejia
, Ai, Hanbing
, Lyu, Chuan
in
Comparative analysis
/ Comparative studies
/ Data interpretation
/ Datasets
/ Detectors
/ Edge detection
/ Geological structures
/ Geomagnetism
/ Gravity anomalies
/ Gravity data
/ High resolution
/ Hyperbolic functions
/ Information retrieval
/ Potential fields
/ Sensors
2023
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Enhancement of Potential Field Source Boundaries Using the Hyperbolic Domain (Gudermannian Function)
by
Alvandi, Ahmad
, Ardestani, Vahid E.
, Su, Kejia
, Ai, Hanbing
, Lyu, Chuan
in
Comparative analysis
/ Comparative studies
/ Data interpretation
/ Datasets
/ Detectors
/ Edge detection
/ Geological structures
/ Geomagnetism
/ Gravity anomalies
/ Gravity data
/ High resolution
/ Hyperbolic functions
/ Information retrieval
/ Potential fields
/ Sensors
2023
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Do you wish to request the book?
Enhancement of Potential Field Source Boundaries Using the Hyperbolic Domain (Gudermannian Function)
by
Alvandi, Ahmad
, Ardestani, Vahid E.
, Su, Kejia
, Ai, Hanbing
, Lyu, Chuan
in
Comparative analysis
/ Comparative studies
/ Data interpretation
/ Datasets
/ Detectors
/ Edge detection
/ Geological structures
/ Geomagnetism
/ Gravity anomalies
/ Gravity data
/ High resolution
/ Hyperbolic functions
/ Information retrieval
/ Potential fields
/ Sensors
2023
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Enhancement of Potential Field Source Boundaries Using the Hyperbolic Domain (Gudermannian Function)
Journal Article
Enhancement of Potential Field Source Boundaries Using the Hyperbolic Domain (Gudermannian Function)
2023
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Overview
Horizontal boundary identification of causative sources is an essential tool in potential field data interpretation due to the feasibility of automatically retrieving the boundary information of subsurface gravity or geomagnetic structures. Although many approaches have been proposed to address these issues, it is still a hot research topic for many researchers to derive novel methods or enhance existing techniques. We present two high-resolution edge detectors based on the Gudermannian function and the modifications of the second-order derivative of the field. The effectiveness of the newly proposed filters was initially tested on synthetic gravity anomalies and geomagnetic responses with different assumptions (2-D and 3-D; imposed and superimposed; noise-free and noise-contaminated). The obtained results verified that the two novel methods yield the capability of producing high-resolution, balanced amplitudes and accurate results for better imaging causative sources with different geometrical and geophysical properties, compared with the other nine representative edge enhancement techniques. Furthermore, the yielded results from the application of the two strategies to a real-world aeromagnetic data set measured from the Central Puget Lowland (C.P.L) of the United States and a gravity data set surveyed from the Jalal Abad area of Kerman province, Iran, with detailed comparative studies validated that the edges identified via the two methods are in good agreement with the major geological structures within the study areas and the determined lateral information using the tilt-depth, top-depth estimation method. These features make them valuable tools for solving edge detection problems.
Publisher
MDPI AG
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