| 一种改进的重力梯度全张量数据的边界识别方法 |
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| 引用本文： | 杜威, 吴贺宇, 陈祥忠, 刘俊成, 张阳阳, 惠梦琳. 2021. 一种改进的重力梯度全张量数据的边界识别方法. 地球物理学报, 64(9): 3358-3367, doi: 10.6038/cjg2021O0465 |
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| 作者姓名： | 杜威 吴贺宇 陈祥忠 刘俊成 张阳阳 惠梦琳 |
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| 作者单位： | 1. 中国科学院地球化学研究所矿床地球化学重点研究实验室, 贵阳 550081; 2. 吉林大学地球探测科学与技术学院, 长春 130026; 3. 北京桔灯地球物理勘探股份有限公司, 北京 102200; 4. 安徽省勘查技术院, 合肥 230031 |
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| 摘 要： | 边界识别是重力资料解释中的一项重要任务.随着重力梯度测量技术的迅速发展,重力梯度张量数据在边界识别中的应用越来越广泛.本文重点研究了随着深度的增加,边界识别能力下降,正负异常中出现假边缘的问题.另外,有些边缘检测方法对走向不同的地质体识别能力有所差异.本文对基于重力梯度张量的水平方向Theta法进行改进,通过选择合适的...
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| 关 键 词： | 重力梯度全张量 边界识别 改进的水平方向Theta法 阈值 |
| 收稿时间： | 2020-12-03 |
| 修稿时间： | 2021-06-12 |
An improved edge detection method for full gravity gradient tensor data |
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| DU Wei, WU HeYu, CHEN XiangZhong, LIU JunCheng, ZHANG YangYang, HUI MengLin. 2021. An improved edge detection method for full gravity gradient tensor data. Chinese Journal of Geophysics (in Chinese), 64(9): 3358-3367, doi: 10.6038/cjg2021O0465 |
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| Authors: | DU Wei WU HeYu CHEN XiangZhong LIU JunCheng ZHANG YangYang HUI MengLin |
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| Affiliation: | 1. State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China; 2. College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China; 3. Beijing Orangelamp Geophysical Exploration Company Limited, Beijing 102200, China; 4. Geological Exploration Technology Institute of Anhui Province, Hefei 230031, China |
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| Abstract: | Edge detection is an essential task in interpretations of gravity and magnetic data. With the rapid development of gravity gradient measurement technology, gravity gradient tensor data has been increasingly used in edge detection. This article focuses on the problem that with the depth increase, the ability to recognize the edge decreases and false edges occur in positive and negative anomalies when using some edge detection methods. In addition, some methods have different recognition abilities for geological bodies with different strikes. Here we propose a new edge detection method which is based on the improved horizontal Theta method of gravity gradient tensors and choosing an appropriate threshold to reduce false anomalies. Comparison of model tests demonstrates that the proposed method is no longer affected by the strike of geological structures. The edges of geological bodies at different depths detected are clear and continuous, and there are no false boundaries between positive and negative anomalies. Finally, this method is applied to the real gravity gradient tensor data in St. Georges Bay, Canada, revealing more geological details. |
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| Keywords: | Gravity gradient tensor Edge detection Improved horizontal Theta method Threshold |
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