0 引言
随着西部大开发战略的推进,水利水电工程逐步向高海拔山区转移[1],高寒缺氧、地形地貌和地质条件复杂、高压线干扰、前期勘察周期短和基础资料缺乏,都给传统物探方法在高海拔区的开展带来巨大挑战。背景噪声面波法通过对台站记录的背景噪声进行互相关计算,提取台站间的经验格林函数,用以地下地质结构成像,具备无需人工震源、施工便捷、成本低且环保的优势,同时与传统主动源面波法相比背景噪声面波法频带宽、探测深度大。自地震学家Aki[2]提出以来,背景噪声成像技术已经广泛应用于地壳地幔[3]、区域尺度结构[4-5]、近地表速度结构[6-7]、盆地沉积结构[8]、古建筑地基探测[9]、地热勘探[10]和活动断层[11-12]等方面的研究。
高海拔区还存在噪声源数量少、能量弱的问题,需要长时间的数据采集,因此带来了巨大的计算量。基于前人的研究成果,本文提出基于功率谱密度的原始噪声筛选方法,通过对原始噪声进行功率谱密度分析,确定噪声能量在时频域的分布规律,进而筛选出强噪声数据进行处理。利用某高海拔区域采集的92 h背景噪声数据,成功筛选出了43 h的强噪声数据,通过互相关计算得到虚拟震源单炮。结果表明经过数据筛选不仅计算时长大幅减少,也提高了面波的信噪比,减少了高视速度干扰波,并获得了浅层0~140 m较高分辨率的横波速度剖面。同时又佐证了高频背景噪声面波方法在高海拔区域的适用性,为今后高海拔区域开展水利水电勘察工作提供借鉴意义。
1 数据与方法
1.1 数据
研究区地形平坦,适宜背景噪声面波方法的开展。综合考虑到野外工作难度、工作量和面波方法体积效应的问题,选用密集的线性排列。沿东北至西南方向,以20 m的道间距,布设了53台EPS短周期数字地震仪,全长1 040 m,台站分布如图1所示,另外为了使地震仪与地面充分耦合并减少风的影响,我们将台站充分掩埋。以500 Hz的采样率,自2022年9月13日12:00至17日8:00共采集了92 h的背景噪声数据,由于部分台站GPS损坏,共成功采集到50个台站的数据。与空间自相关方法相比被动源面波多道分析方法(MAPS)[17]更适宜于线性阵列的频散提取[18],因此本研究选用Z分量数据,采用MAPS方法处理背景噪声数据,以获得地下横波速度结构。
图1
1.2 基于功率谱密度的数据筛选方法
1.2.1 功率谱密度原理
周期时间序列
其中:
其中:
1.2.2 数据筛选方法
测区处于牧区草场内,海拔约3 300 m,人迹罕至,噪声源数量少、能量弱,为了快速获得高信噪比的面波信号,我们提出基于功率谱密度的背景噪声数据筛选技术。首先对原始噪声进行功率谱密度分析,获得噪声时频域能量变化规律,进而筛选出强噪声数据和弱噪声数据,再结合功率谱密度分析获得的噪声频带信息,对强噪声数据进行处理,最后获得高分辨率的横波速度结构,如图2所示。
图2
2 数据筛选与处理
2.1 数据筛选
图3
图3
部分道原始噪声波形(a)和原始噪声平均功率谱密度(b)
Fig.3
Partial channel original noise waveform(a) and average power spectral density of original noise(b)
2.2 数据处理
2.2.1 预处理
2.2.2 互相关计算
图4
图5
图5
不同类型数据虚拟单炮信噪比及计算时长
Fig.5
Virtual source single shot signal-to-noise ratio and calculation duration of different types of data
2.2.3 频散提取与反演
采用相移法,选用虚拟单炮的炮点所在道和其后的23道作为一个排列进行频散分析,再依次往前滚动处理其他虚拟单炮,以获得不同位置的面波频散信息。图6为第7点为虚拟震源时面波的频率—相速度,面波频散能量集中、收敛性好,分布于3~20 Hz,满足准确提取频散曲线的条件。
图6
根据面波影响深度(深色范围),设置100 m、8层的初始模型,层厚梯度0.5,用最小二乘法反演,经过15次迭代,均方根值为5.82 m/s,误差约1.56%,反演结果与相速度曲线吻合良好,如图7所示,并将其作为排列中点的横波速度信息。然后依次反演每一个虚拟源单炮获得的频散曲线,进而获得长580 m、深140 m的横波速度剖面,如图8所示。根据横波速度剖面特征,可以大致将其分为3层:①速度200~400 m/s,深度约0~20 m,速度结构非常稳定,横向均匀性和纵向成层性好;②速度400~700 m/s,深度约20~60 m,速度结构稳定,纵向成层性好,速度等值线密集,梯度变化大,横向速度结构呈沿测线方向逐渐变薄的趋势;③速度700~1 200 m/s,深度约60~140 m,速度结构较稳定,横向存在一定程度起伏,其中横向260~400 m处横波速度略低。图1所示距测线约1.25 km的钻孔,所揭露的地层也可大致分为3层:①0~26.3 m,干燥、稍密的沙土层;②26.3~63.5 m,稍湿、稍密—中密的粉土、砂卵石和砂砾石互层;③63.5~120 m,湿、中密的砂、粉质黏土和砂砾石互层。横波速度层与钻孔所揭露的地层基本吻合,表明该方法的有效性。
图7
图8
3 结论
在噪声源数量少、能量弱的高海拔区,开展背景噪声方法往往需要长时间的数据采集,带来巨大计算量,并且难以获得高信噪比面波,因此笔者提出了基于功率谱密度的背景噪声数据筛选方法,利用某高海拔区域53台仪器采集的92 h背景噪声数据开展研究,得到如下结论:
1)根据功率谱密度图的噪声能量分布特征,能够有效筛选出可靠的强噪声数据,基于筛选结果进行数据处理,能够大幅提升互相关计算效率,提高面波的信噪比,并减少异常高视速度同相轴的干扰。
2)该方法具备不依赖人工震源和布设简便的特点,极大降低了工作的难度和成本,能够快速获得高分辨率的横波速度结构,对高海拔等特殊区域的水利、电力工程建设具有重要意义。
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