﻿ 近地表速度建模研究现状及发展趋势

1.中国石油化工股份有限公司石油物探技术研究院,江苏 南京 211103
2.中国石油大学(华东)地球科学与技术学院,山东 青岛 266580

Research Status and Development Trend of Near-Surface Velocity Modeling
Wang Zhenyu1,2, Yang Qinyong1, Li Zhenchun2, Hu Guanghui1, Yin Li1,2, Wang Jie1
1.Sinopec Geophysical Research Institute, Nanjing 211103, China
2.School of Geosciences, China University of Petroleum, Qingdao 266580, China
Abstract

Seismic velocity is a critical factor in reflecting underground structure and lithology. The accuracy of near-surface velocity directly influences the results of static correction, velocity analysis and the final imaging in exploration areas. Near-surface modeling methods and technologies commonly used are based on the ray theory of high-frequency approximation, which barely meet the highaccuracy request in current nearsurface modeling. Through an overall investigation into nearsurface modeling technologies such as micro logging, mini refraction, surface wave method, traveltime tomography and Full Waveform Inversion (FWI), this paper summarizes their adaptability, advantages and disadvantages, research and application status, points out that by combining traveltime tomography and waveform inversion, the step-by-step and multiscale inversion strategy in the time domain is an effective means and trend of near-surface high-accuracy modeling, which can improve modeling accuracy effectively and meet the requirements of high accuracy imaging. Thus, the method has widespread application prospects in near-surface mineral prospecting, engineering geophysics and hydrocarbon exploration.

Keyword: Traveltime tomography; Full waveform inversion; Multiscale; Joint inversion strategy; High-accuracy.
1 引言

 Figure Option 图1 复杂近地表概况Fig 1 Complicated near surface general situation

2 近地表速度建模方法

2.1 微测井

2.2 小折射法

2.3 面波法

2.4 层析反演方法

L∆s=∆t, (1)

3 全波形反演

20世纪80年代, Gauthier[33]等和Mora[34]实现了二维地震资料全波形反演。随着计算机水平的提高, 三维全波形反演在90年代中后期陆续出现[35, 36], 2010年, Sirgue等[37]率先对挪威北海油田OBC数据实现了全波形反演, 对浅层气云进行了准确描述, 并对周边充气的断裂构造进行了精细的刻画, 发展了直接对高精度速度体进行地震资料解释的新思路。随后, 全波形反演海上三维实际资料应用陆续出现[38, 39]。在缺少低频的情况下, Shin[40]采用拉普拉斯域联合频率域全波形反演, 首先利用拉普拉斯域全波形反演对频率不敏感的特性来恢复长波长分量, 继而以此为初始模型利用频率域全波形反演恢复短波长分量实现高精度建模。

2012年, 壳牌公司和东方地球物理公司合作实现了二维陆上资料的全波形反演[41]。但是这一研究是基于低频大偏移距的特殊的观测系统, 这在常规实际资料中是难以实现的, 在地震采集中也难以大规模实施。针对国内陆上探区特点, Hu[42]开展了面向目标层的全波形反演研究, 结果展示了全波形反演对浅中层建模的积极作用, 成像剖面有很大改善, 构造与测井信息更加吻合。

4 分步骤、多尺度联合反演策略

4.1 基本原理：

$E=12∑s∑g∫(δp(rg, t|rs))2dt2$

$δp(rg, t|rs)=pobs(rg, t|rs)-pcal(rg, t|rs)$(3)

$g(r)=2c(r)∑s∫p·(r, t|rs)p·'(r, t|rs)dt4$

$dk=-Pkgk+βkdk-15$

$k=1, 2, …, kmax$表示迭代次数, $g=g(r)$是速度模型的所有成像点, $P$是常规的几何扩散预处理因子[53]

$βk=gTk·(Pkgk-Pk-1gk-1)gTk-1·Pk-1gk-16$

$ck+1r=ckr+λkdkr(7)$

Sheng等[45]提出的最早至波形层析的新方法(Early-arrival Waveform Tomography, EWT), 通过对地震数据加窗仅仅反演最早至波场。与传统的全波形反演相比, 由于需要更少的数据匹配, 降低了非线性, 但是反演中的高频数据使目标函数仍然具有高度的非线性, EWT还是会遇到局部极小问题。Bunks等[29]提出时间域多尺度波形层析, 利用Hamming-window 滤波器对地震子波和地震数据进行低通滤波, 使反演从低频到高频数据依次进行。由于对于慢度的目标函数在低频比在高频更加线性, 多尺度波形层析(Mutiscale Waveform Tomography, MWT)更容易达到局部极小。而Bunks等[29]利用Hamming-window function进行低通滤波对于时间域MWT不是最有效的滤波器。而且在反演过程中, 频带选择是任意的。对于每一个频带, 反演进行多次迭代, 这就导致过多的频带花费大量的计算时间。在频率域, Sirgue等[57]提出了一种最优频带选择策略, 极大地减少了波形反演的计算量, 把这种方法应用到时间域, 2009年, Chaiwoot Boonyasiriwats结合Bunks等提出的多尺度层析以及Sirgue等在频率域提出的最优频带选择策略将Sheng等的方法推进一步, 不再是仅仅利用折射数据, 而利用全波场信息, 通过滤波并选择最优频带在时间域运用分频带和变化网格相结合的方法来克服波形反演中的严重局部极小值问题, 分步骤、分尺度的联合初至走时层析和全波形反演进行近地表速度建模, 提高了收敛速度和计算效率, 精确地恢复了速度模型的低波数成分和高波数成分[58~60]

4.2 对于MWT的有效的低通滤波

Bunks[29]利用Hamming-windowfunction[61]对震源子波和数据进行低通滤波。震源子波在反演之前已经被估计得到[62~65]。维纳滤波器一般应用在频率域, 它的一个优点是把一个信号滤到接近另一个目标信号。低通维纳滤波可以通过下式计算:

$fWiener(ω)=Wtarget(ω)Woriginal†(ω)Woriginal(ω)2+ε28$

4.3 最优频带选择策略

Sirgue 等[57]提出的在频率域波形反演中选择最优频带范围策略被延伸到时间域来减少恢复的速度结构中的波数冗余。单一频率中, 一个炮检对的贡献仅仅是一个波数成分。速度模型中一系列的垂直波数成分可以通过一系列炮检对来更新。

Sirgue等[57]提出的选择频带公式是:

$fn+1=fnαmin9$

 Figure Option 图2 时间域波形层析最优频带选择策略[58]Fig 2 Strategy for choosing optimal frequency bands for time-domain wave form tomography[58]

$kzminn=4πfminnαminc010kzmaxn=4πfmaxnc011$

$kzminn+1=kzmaxn(12)$

4.4 模型测试

 Figure Option 图3 时间域多尺度波形反演结果(a)5Hz峰值频率数据MWT结果; (b)5Hz和20Hz峰值频率数据MWT反演结果; (c)20Hz峰值频率数据SWT反演结果; (d)真实速度模型[58]Fig 3 Time-domain multiscale waveform inversion results(a)MWT velocity tomogram obtained after inversion using 5-Hz peak-frequency data; (b)MWT velocity tomogram obtained after inversions using 5- and 20-Hz peak-frequency data; (c)SWT velocity tomogram obtained after inversion using 20-Hz peak-frequency data; (d)the true velocity model[58]

4.5 海上实际资料应用

 Figure Option 图4 墨西哥湾海洋数据反演结果(a)走时层析反演结果; (b)MWT反演结果[59]Fig 4 Inversion results from the marine data(a)The initial velocity model obtained from traveltime tomography; (b)The velocity tomogram obtained from waveform tomography[59]

 Figure Option 图5 墨西哥湾海洋数据偏移结果(a)走时层析偏移结果; (b)MWT偏移结果[59]Fig 5 Migration images from the marine data.(a)The Kirchhoff migration image obtained using the original data and the traveltime tomogram; (b)The Kirchhoff migration image obtained using the waveform tomogram[59]

 Figure Option 图6 偏移成像放大结果对比(a)和b)分别是图5a实线框和虚线框放大结果; (c)和(d)分别是图5b实线框和虚线框放大结果[59]Fig 6 Zoomed views of migration images from the marine data.Using the traveltime tomogram, the Kirchhoff migration images in(a)the solid box and(b)the dashed box are obtained. Using the waveform tomogram, the Kirchhoff migration image in(c)the solid box and(d)the dashed box are obtained[59]

 Figure Option 图7 共成像点道集(CIGs)对比 [59](a)走时层析结果CIGs; (b)MWT结果CIGsFig 7 Common image gathers (CIGs) obtained from the marine data migrated(a)traveltime tomogram; (b)waveform tomogram as the velocity model[59]

5 结论与展望

The authors have declared that no competing interests exist.

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