1 Harbin Natural Resources Survey, China Geological Survey, Harbin 150081, China
2 Northeast Geological S&T Innovation Center of China Geological Survey, Shenyang 110034, China
3 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Central South University), Ministry of Education, Changsha 410083, China
4 School of Geophysics and Information Technology, China University of Geosciences(Beijing), Beijing 100083, China
5 Scientific Monitoring and Research Station of Earth Critical Zone on Black Soil in Harbin, Ministry of Natural Resources of the People’s Republic of China, Harbin 150086, China
6 Nanjing Center, China Geological Survey, Nanjing 210016, China
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文章历史+
Received
Published
Revised
2025-09-23
2026-09-28
2026-02-12
Online Date
2026-10-09
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摘要
黑土地地表基质调查是面向黑土地保护与利用开展的自然资源国情国力调查,是地质调查工作支撑服务自然资源管理与生态文明建设的全新领域。如何高分辨率、经济快速地获取地下50 m以浅的横波速度,是东北黑土地地表基质层结构调查面临的核心技术问题之一。主动源与被动源结合的面波混合源精细勘查技术,可实现两种不同震源面波勘探方法的优势互补,能够获取高分辨率的地表基质速度结构并完成地质分层。采用基于多道瞬态面波法(multi-channel analysis of surface waves,MASW)的线性阵列多次滚动观测系统,在同一测点同步采集人工源与天然源地震数据;在对多种频散分析方法进行计算对比后,优选扩展空间自相关法(extended spatial autocorrelation,ESPAC)进行处理,随后合并主动源与被动源的频散能量图,提取频散曲线后利用遗传算法迭代反演得到面波速度结构。经已知钻孔旁的标定验证,该方法可靠性良好。在调查区域采用点距约5 km的稀疏网格化观测部署,根据解译结果编制完成地表基质调查区的土岩界面埋深图。研究结果表明:ESPAC法支持利用主动源观测阵列采集被动源数据,所得频散谱在衔接段一致性良好,同时可显著提升施工效率。研究结果为地表基质结构调查以及浅层地球物理调查领域提供了技术示范。
Abstract
Ground substrate survey in black soil regions is a national assessment of natural resource conditions and national strength for the protection and utilization of black soil. It represents a new frontier where geological survey work provides support and services for natural resource management and ecological civilization. The high-resolution, cost-effective, and rapid acquisition of S-wave velocities at depths shallower than 50 m remains a critical technical challenge for investigating the structure of ground substrate layers in the black soil region of Northeast China. A mixed source surface wave exploration technique, combining active and passive sources, enables complementary advantages between these two distinct excitation methods. This approach facilitates the acquisition of high-resolution velocity structures and geological stratification of the ground substrate. A linear array with a roll-along geometry based on MASW(multi-channel analysis of surface waves) was used to acquire seismic data from both active and passive sources at identical survey points. Following a computational comparison of several dispersion analysis methods, the ESPAC (extended spatial autocorrelation) method was selected. Subsequently, dispersion energy maps from active and passive sources were merged, dispersion curves were extracted, and the surface wave velocity structure was iteratively inverted using a genetic algorithm. The reliability of the method was verified through calibration against known boreholes. Regionally, a sparse grid deployment with a point spacing of approximately 5 km was implemented, and a depth-to-bedrock map was compiled from the interpretation results. The results demonstrate that the ESPAC method enables the acquisition of passive source data using the observation array intended for active sources. The resulting dispersion spectra exhibit high consistency in the overlapping frequency bands, and survey efficiency was significantly improved. This result provides a technical demonstration for ground substrate surveys and the broader field of shallow geophysical exploration.
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