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水力发电学报 ›› 2021, Vol. 40 ›› Issue (2): 177-186.doi: 10.11660/slfdxb.20210218

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基于水平相关距离的土层厚度区域评价方法研究

  

  • 出版日期:2021-02-25 发布日期:2021-02-25

Study of soil thickness regional evaluation using horizontal scales of fluctuation

    

  • Online:2021-02-25 Published:2021-02-25

摘要: 近年来随着海上大型工程建设项目逐渐增多,建设场地的区域工程地质条件分析越来越得到重视。本文以南海海域的侧扫声呐数据为基础,采用递推空间改进法和相关函数法进行水平相关距离的计算,以计算所得的水平相关距离为基础选择数据,采用普通克里金方法对土层厚度进行插值,得到土层厚度分布图。结果表明:利用侧扫声呐数据对土层厚度进行空间自相关性和变异性分析是可行的;采用递推空间改进法计算所得水平相关距离值更加平稳且计算较简便,计算表明研究海域土层厚度的水平相关距离在400 ~ 600 m范围内;依据水平相关距离确定测线间距选择插值数据,基于普通克里金方法对土层厚度进行插值可获得一定精度的区域土层厚度分布;误差主要出现在相关距离值较小的位置,表明此周围土性变化较为明显,后续可根据工程需要在这些位置加密测线、适当增加钻孔数量。

关键词: 侧扫声呐, 水平相关距离, 区域评价, 土层厚度, 物探数据, 普通克里金插值

Abstract: In recent years, evaluation of site geological conditions attracts more attention as more offshore projects are developed. Based on side-scan sonar data, this study calculates the horizontal scale of fluctuation using an improved space average method and an autocorrelation function method, and obtains a map of soil thickness distribution on the seabed over an offshore area by applying the ordinary Kriging method and the data of horizontal scale calculations. Results show that it is feasible to analyze the spatial autocorrelation and variability of soil thickness using the side-scan sonar data, and our scale calculation method is more stable and simpler. It is found that this scale falls in the range of 400-600 m for the soil layers in the study area. Generally, the accuracy of soil thickness distribution calculated using a data interpolation scheme that is determined by the calculated scales is satisfactory. However, evaluation errors may be quite big for those locations with small correlation distance, indicating a significant special variation in soil properties. To reduce such errors, the sweeping path of the side-scan sonar and the number of boreholes near these locations should be replanned to meet project needs.

Key words: side-scan sonar, horizontal scale of fluctuation, regional evaluation, soil thickness, geophysical data, the ordinary Kriging interpolation method

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