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Enhtheta: A new balanced filter for Edge Detection of Potential Field anomalies | ||
| فیزیک زمین و فضا | ||
| مقاله 4، دوره 51، شماره 4، اسفند 1404، صفحه 45-64 اصل مقاله (1.26 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2025.400924.1007716 | ||
| نویسنده | ||
| Kamal Alamdar* | ||
| Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran. | ||
| چکیده | ||
| Magnetic and gravity data are types of potential field data. The magnetic method is based on variations in the magnetic field caused by lateral differences in the magnetization of the subsurface sources. Magnetic interpretation, similar to gravity interpretation, operates at several levels of complexity. It can range from simple identification and location of anomalous magnetic bodies in the subsurface (edge detection approaches) to three-dimensional modeling for complete characterization of an anomaly. The most commonly used edge detection filters for enhancing potential field data are vertical or horizontal derivatives. These derivative filters can be combined to produce a new edge detection filter (analytic signal and total horizontal derivative for example). On the other hand, balanced derivative filters (or local phase filters) are used to simultaneously emphasize potential field signals from sources at different depths. In this paper, an improved balanced filter, the Enhanced Theta filter (Enhtheta), is presented, which replaces the conventional THDR and ASA with balanced THDR and ASA in the Theta filter equation. In particular, the presence of overlying shallow and deep magnetic/gravity sources leads to the creation of strong and weak anomalies. Thus, if the observed data contain anomalies with a large variation in amplitude, then geologically important anomalies with small amplitudes may be hard to recognize. In such a dataset, closely-spaced sources are difficult to delineate due to the superposition effect. This new filtering technique balances the strong and weak anomalies in the original image, thereby producing a balanced theta map. The maximum value of this filter delineates the edges of the anomalies. Moreover, its total horizontal derivative (THDR_Enhthet) can be used as an edge detector filter. The maximum value of the THDR_Enhtheta filter shows the edges of the anomalies. The capability of the proposed algorithm is demonstrated using both noise-free and noise-contaminated synthetic magnetic data generated from prismatic models, as well as real aeromagnetic data from the Bushveld Complex, South Africa. The results of the new filter are compared with other edge detection filters, namely TDR, Theta and TDX. Enhtheta and its total horizontal derivative provide more accurate detection of the source edges compared to other filtering techniques. Therefore, interpretation of potential field data is facilitated using the Enhtheta filtering method. | ||
| کلیدواژهها | ||
| Analytic Signal؛ Edge detection؛ Theta filter؛ TDR؛ Enhtheta؛ Bushveld | ||
| مراجع | ||
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