地震地质 ›› 2019, Vol. 41 ›› Issue (4): 960-978.DOI: 10.3969/j.issn.0253-4967.2019.04.010

• 研究论文 • 上一篇    下一篇

基于小波变换和均衡重力异常的断裂识别——以柴达木盆地及周边地区为例

付强1,2, 刘天佑3, 马龙4, 杨宇山3, 颜茂都1,5   

  1. 1. 中国科学院青藏高原研究所, 大陆碰撞与高原隆升重点实验室, 北京 100101;
    2. 中国科学院大学, 北京 100049;
    3. 中国地质大学(武汉)地球物理与空间信息学院, 武汉 430074;
    4. 青海省第三地质矿产勘查院, 西宁 810029;
    5. 中国科学院青藏高原地球科学卓越创新中心, 北京 100101
  • 收稿日期:2018-12-05 修回日期:2019-02-25 出版日期:2019-08-20 发布日期:2019-09-28
  • 通讯作者: 颜茂都,男,研究员,E-mail:maoduyan@itpcas.ac.cn
  • 作者简介:付强,男,1991年生,2015年于中国地质大学(武汉)地球物理与空间信息学院获地质工程硕士学位,现为中国科学院青藏高原研究所构造地质学专业在读博士研究生,研究方向为重磁数据处理与解释、构造古地磁以及岩石磁学,电话:18986133981,E-mail:qiangfu@itpcas.ac.cn。
  • 基金资助:
    国家重点研发计划项目(2017YFC0602803)、中国科学院战略性先导科技专项"泛第三极环境变化与绿色丝绸之路建设"(XDA20070201)、国家自然科学基金(41571198)和青藏高原第二次科考项目(2019QZKK0707)共同资助

WAVELET TRANSFORM ANALYSES OF FAULTS DETECTION ON ISOSTATIC GRAVITY ANOMALIES: A CASE STUDY FROM THE QAIDAM BASIN AND ITS ADJACENT AREAS

FU Qiang1,2, LIU Tian-you3, MA Long4, YANG Yu-shan3, YAN Mao-du1,5   

  1. 1. Key Laboratory of Continental Collision and Plateau Uplift, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China;
    4. The Third Geological Mineral Exploration Institute of Qinghai Province, Xining 810029, China;
    5. CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
  • Received:2018-12-05 Revised:2019-02-25 Online:2019-08-20 Published:2019-09-28

摘要: 均衡重力异常消除了地壳厚度引起的重力效应,包含着丰富的地质构造信息,利用重磁边界识别方法能够对该异常蕴含的断裂信息进行提取。但是,每种边界识别方法都有其各自的优势和不足。小波分析是近年来发展起来的一种较为有效的边界识别方法,其具有较强的抗噪声能力以及多尺度分解的特征,能够识别和提取更细致的断裂信息。文中建立了包含断裂带及其它类型地质体的综合模型并正演了其重力异常,之后对该异常进行了小波断裂分析,将提取出的边界及断裂信息与实际位置进行对比并评判该方法的应用效果。在此基础上,又将该方法应用到柴达木盆地及周边均衡重力异常的断裂识别中,并将识别出的断裂与区域已知断裂带进行对比。最后,将其分别与小波分析对布格重力异常断裂的识别效果以及另外几种常见方法对均衡重力异常断裂的识别效果进行对比。结果表明,小波多尺度变换结合均衡重力异常是一种较为有效的断裂识别手段。

关键词: 边界识别, 均衡重力异常, 小波分析, 柴达木盆地

Abstract: Isostasy is used to describe a condition to which the Earth's crust and mantle tend, in the absence of disturbing forces. Eliminating the gravity effect of crust, isostatic gravity anomalies contain abundant geological structure information, which can be extracted by edge detection methods of gravity or magnetic anomalies. In order to accurately obtain the edge information, a great variety of methods, such as analytical signal amplitude, tilt angle, theta map θ, etc., have been proposed by domestic and international scholars, and many significant advances have been made in recent days. However, each method has its advantages and disadvantages. Wavelet transform is an effective method developed in recent years. It has the enhanced noise resistance and a feature of multi-scale decomposition, and can be used to identify more detailed information of edge. Here with the aim of demonstrating its effectiveness in faults detection, we established a theoretical geological model, which consists of five geological bodies. The geological bodies with different density present a fault zone and the areas on its sides, as well as two geological bodies with different geological properties. We calculated the gravity anomalies caused by this model, in addition, we added 5% Gaussian noise to the gravity anomalies for a comparative analysis to analyze the effects of wavelet transform on edge detection. Finally, we applied wavelet transform method to the decomposition of isostatic gravity anomalies, obtained 1st to 5th order wavelet transform details of the gravity anomalies, and compared with the well-studied faults in the Qaidam Basin and its adjacent areas. The results obtained by wavelet transform matched well with the known faults, the anomalies of different order denote the location of different fault zone(e.g. the Tanan Fault is nearly invisible on the original and the first order isostasy gravity anomalies map, but is well expressed on the second order isostasy gravity anomalies map; The apparent details of the 4th and 5th indicate that faults in front of the Saishiteng-Xitieshan Shan are deep faults and they are likely to distribute continuously in the deep underground). Besides, we calculated the estimated depth of isostasy gravity anomalies of different order through power spectrum analysis as well, finding that different faults extend to different depth. For example, the Danghe-Nanshan Fault and the Southern Fault in the middle Qilian Shan are 10km in depth approximately, but the faults in front of the Saishiteng-Xitieshan Shan are more than 70km in depth. In addition, we made two comparative studies, the first one is comparing the results mentioned above with the result through wavelet transform of Bouguer gravity anomalies. The second one is comparing with the results through other edge detection methods of isostatic gravity anomalies. In spite of the inconformity between anomalies and the faults to some extent, which is likely caused by the change of lithology or faults distribution in the deep underground, we finally found that:more subtle details induced from faults can be detected from isostatic gravity anomalies by using wavelet transform because of its feature of multi-scale decomposition. The wavelet transform method is proved to be more accurate and reliable(at least in the Qaidam Basin and its adjacent areas)comparing with other methods.

Key words: edge detection, isostatic gravity anomalies, wavelet analysis, the Qaidam Basin

中图分类号: