Fengjun WU, Xin-Ai XU

An enhancement filter utilizing the modified arctangent function for the structural and tectonic interpretation of causative sources: Application to WGM2012 gravity data from the Rafsanjan Plain, Iran

Introduction

An enhancement filter utilizing the modified arctangent function for the structural and tectonic interpretation of causative sources: application to wgm2012 gravity data from the rafsanjan plain, iran. Enhance gravity data edge detection for structural & tectonic interpretation with the Modified Arctangent Function (MAT) filter. Validated on WGM2012 Rafsanjan Plain, Iran.

Abstract

Gravity data edge detection methods play a crucial role in identifying the horizontal positions of buried sources and enhancing the interpretation of subsurface structures. Among these methods, the Total Horizontal Gradient (THG) filter is widely used due to its noise stability and straightforward formulation. However, the THG filter has inherent limitations, prompting the development of refined edge detection techniques. To address these shortcomings, various approaches based on local phase analysis or normalized filters have been introduced, many of which incorporate the arctangent function to combine horizontal and vertical gradients. While these methods improve edge detection, they also exhibit drawbacks, such as the generation of spurious edges and restricted resolution. In this study, we propose the Modified Arctangent Function (MAT), which enhances gravity source edge detection by integrating the total horizontal gradient with a modified arctangent function. The effectiveness of the MAT filter is systematically evaluated against conventional filters that utilize the arctangent function and/or the total horizontal gradient. Its performance is validated through synthetic gravity data tests, both with and without noise contamination. To further assess its applicability, the MAT filter is applied to high-resolution gravity data from the WGM2012 (World Gravity Map) over the Rafsanjan Plain in Iran. Additionally, an approximated derivative calculation method is incorporated to mitigate noise amplification during the derivative computation process. The results from both synthetic and real data confirm that the MAT filter effectively detects and delineates gravity anomalies, demonstrating its potential as a valuable tool for geophysical interpretation.

Review

This paper introduces a novel enhancement filter, the Modified Arctangent Function (MAT), aimed at improving the detection and interpretation of buried gravity sources for structural and tectonic studies. The authors effectively contextualize the importance of gravity data edge detection methods, while also acknowledging the widespread use and inherent limitations of conventional techniques such as the Total Horizontal Gradient (THG) filter. They highlight that while existing arctangent-based approaches have sought to refine edge detection, these often suffer from issues like spurious edge generation and restricted resolution. The proposed MAT filter directly addresses these shortcomings by integrating the total horizontal gradient with a uniquely modified arctangent function. The methodology for the MAT filter is presented as a refinement designed to overcome the limitations of its predecessors. The effectiveness of the MAT filter is rigorously evaluated through a two-pronged approach. Firstly, its performance is benchmarked against established conventional filters using synthetic gravity data, meticulously tested both with and without noise contamination to assess its robustness. Secondly, the filter's practical utility is demonstrated by applying it to high-resolution WGM2012 gravity data from the Rafsanjan Plain in Iran, a real-world geological setting. A noteworthy aspect of the methodology is the incorporation of an approximated derivative calculation method, specifically implemented to mitigate noise amplification during the critical derivative computation step, a common challenge in geophysical data processing. The abstract concludes that the MAT filter effectively detects and delineates gravity anomalies in both synthetic and real-world scenarios. Overall, this study presents a well-motivated and systematically evaluated enhancement filter with promising applications in geophysical interpretation. The clear identification of limitations in current edge detection methods provides a strong rationale for the development of the MAT filter. The comprehensive validation, encompassing both synthetic data under varying noise conditions and a real-world application, significantly bolsters the credibility of the proposed method. A key strength appears to be the strategic integration of an approximated derivative calculation to enhance noise stability, which is crucial for practical applications. While the abstract effectively highlights the filter's capabilities in detecting and delineating anomalies, a full exposition of *how* the arctangent function is modified to specifically address issues like spurious edges and restricted resolution, and a quantitative comparison of improvement in these specific aspects, would be highly anticipated in the full manuscript. This work holds significant potential as a valuable tool for geoscientists seeking clearer insights into subsurface structural and tectonic features.

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