拟共震源高密度面波法数据反演模拟算法及应用
收稿日期: 2023-08-29
修回日期: 2023-10-17
录用日期: 2023-10-19
网络出版日期: 2023-11-16
基金资助
国网浙江省电力有限公司科技项目(5211QZ2000U6)
Inversion and Simulation Algorithm of High-Density Surface Wave Method for Pseudo Co-Seismic Source and Its Application
Received date: 2023-08-29
Revised date: 2023-10-17
Accepted date: 2023-10-19
Online published: 2023-11-16
岩溶的精准探测对基础设施施工至关重要,传统面波法的数据采集和处理方法难以满足长大断面基础设施施工的要求.在传统面波法的基础上对数据采集和数据处理算法进行改进,提出拟共震源高密度面波法,通过高密度采集大量的数据,拟共震源在反演时将同一检测点采集到的不同震源数据叠加在一起,提高了探测效率和数据利用率.提出拟共震源高密度面波法的数值模型建立流程,并进行了验证.最后,对拟共震源高密度面波法进行现场应用.结果表明:拟共震源高密度面波法岩溶探测结果与钻孔勘探结果吻合较好,岩溶探测效果显著提高.研究成果为长大断面基础工程下岩溶的快速精准探测提供了参考.
金韬 , 高斌 , 王强强 , 周行 , 何文 , 冯少孔 . 拟共震源高密度面波法数据反演模拟算法及应用[J]. 上海交通大学学报, 2025 , 59(7) : 1029 -1040 . DOI: 10.16183/j.cnki.jsjtu.2023.430
Accurate detection of karst is of utmost importance for infrastructure construction. However, traditional surface wave methods for data acquisition and processing fall short in meeting the requirements of large-scale infrastructure projects in karst areas. In order to address these limitations, an improved approach called the high-density pseudo-source surface wave method has been proposed based on the traditional surface wave method. This method involves the collection of a large volume of data through high-density data acquisition, where multiple measurements at the same location with different pseudo-sources are combined during the inversion process, significantly enhancing the efficiency and utilization of the detection process. A workflow for establishing numerical models using the high-density pseudo-source surface wave method has been developed and validated. Additionally, field applications of this method have been conducted. The research findings demonstrate a strong correlation between the results obtained from the high-density pseudo-source surface wave method and those from drilling exploration, highlighting a significant improvement in karst detection. These achievements provide valuable insights and references for the rapid and accurate detection of karst in large-scale infrastructure projects.
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