Rvelslant(Rvelslant)
Rvelslant()所属R语言包：Rvelslant
Downhole Seismic Analysis In R
在R井下地震分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function Rvelslant is the main function for analyzing downhole seismic data and interpreting layered velocity models.
函数Rvelslant的主要功能是为井下地震数据进行分析和解释层状速度模型。
The travel time at depth z is given by the equation:
在深度z的行进时间由下式给出：
for i = 1, 2, \ldots, N where h_i is layer thickness, s_i is the layer slowness (v = 1/s), and n_i is the number of transits of each layer (1 for all layers above the measurement depth z, 0 for all layers below). When refracted waves are considered, h_i is adjusted to be the length of the raypath in each layer according to Snell's law, then:
i = 1, 2, \ldots, N其中h_i是层厚度，s_i是一层缓慢（v = 1/s），和n_i是过境的每一层（1所有层以上的测量深度z，下面的所有层为0）。当折射波被认为是，h_i被调整到的射线路径的长度，在每一层中，根据斯涅耳定律，然后：
The slowness, s_i for i = 1, 2, \ldots, N, of each layer, is calculated by
缓慢，s_ii = 1, 2, \ldots, N，每一层，计算方法
and
和
Two-point ray-tracing is calculated with the function path4sl which is based on the FORTRAN subroutine path4sl by:
双点射线追踪计算与函数path4sl的FORTRAN子程序path4sl它是基于根据：
David Boore <boore@usgs.gov><br> U.S. Geological Survey<br> Mail Stop 977<br> 345 Middlefield Road<br> Menlo Park, CA 94025 USA<br>
大卫Boore <boore@usgs.gov>参考美国地质调查局<BR>邮站345米德尔路977参考参考门洛帕克，CA 94025 USA参考
用法----------Usage----------
Rvelslant(data, snell = TRUE, bot = NULL, auto = FALSE, cex = 1,
nticks = NULL, grid = FALSE, depth = "v", profile = "slow")
参数----------Arguments----------
参数：data
a list containing the following elements:
一个列表，其中包含以下元素：
z:array of the depths of travel-time measurements, in meters (length = k).
z：阵列的旅游时间测量的深处，以米（长度=k）。
tt.slant:array of observed travel-time measurements in seconds (length = k).
tt.slant：阵列观测到的旅行时间在几秒钟内测量（长度=k）。
hoffset:the horizontal offset at the surface from the borehole.
hoffset：从钻孔的表面处的水平偏移。
sig:array of the standard deviation of the travel-time measurements normalized to the standard deviation of the best pick. Defaults to 1 if none is given. Used for weighting the travel-time measurements in the regression.
sig：阵列的标准偏差归一化的标准偏差的最佳回升的行程时间的测量。如果没有给出，默认为1。用于加权的行程时间测量的回归。
参数：snell
logical value for calculating the raypath according to Snell's Law, defaults is TRUE. If snell == FALSE, then the raypath is approximated by a slanted line and the inversion is much faster.
根据Snell定律计算的射线路径的逻辑值，默认值是TRUE。如果snell == FALSE，然后射线路径近似斜线和逆变器的速度要快得多。
参数：bot
an optional array (length = n) of depth to layer interfaces for the starting model. If not provided, then the initial model is a single layer extending from the surface to the depth of the last measurement.
一个可选的数组（长度=n）的深度初始模型层的接口。如果没有提供，则初始模型是一个单一的层，从表面延伸到最后的测量的深度。
参数：auto
logical value for if the depths to boundaries should be autopicked for initial model. Default is TRUE
初始模型的边界应autopicked深处的逻辑值。默认值是TRUE
参数：cex
see par function in R package "graphics".
par R封装的图形功能。
参数：nticks
approximate number of tick marks desired for depth-axis on travel-time plots. See pretty function in R package "base".
所需的深度轴的刻度，旅游时间图上的近似数。见pretty函数在R封装的“碱基”。
参数：grid
logical value for plotting grid lines on travel-time plots.
旅游时间图上绘制网格线的逻辑值。
参数：depth
layout of plots. Value can be "v" for vertical or "h" for horizontal orientation of the depth-axis on travel-time plots.
图布局。值可以是垂直或“h”的旅游时间图上的深度轴水平方向的V。
参数：profile
defaults to "slow" for plotting the slowness profile with the travel-times and residuals. Any other value, i.e. "vel" will plot the velocity profile instead.
默认为慢的图缓慢的旅游时间和残差的档案。任何其他值，即“VEL”将绘制的速度剖面。
值----------Value----------
a list containing model info and original data. The specific elements of the list are: <table summary="R valueblock"> <tr valign="top"><td>A</td> <td> A = sum(n_i * h_i * s_i)</td></tr> <tr valign="top"><td>s</td> <td> array containing the slowness of each layer (length = n).</td></tr> <tr valign="top"><td>v</td> <td> array containing the velocity of each layer (length = n).</td></tr> <tr valign="top"><td>n</td> <td> integer number of layers in the velocity model.</td></tr> <tr valign="top"><td>k</td> <td> number of travel-time measurements.</td></tr> <tr valign="top"><td>h</td> <td> array of thicknesses of each layer (length = n).</td></tr> <tr valign="top"><td>bot</td> <td> array of depth to bottoms of each layer (length = n).</td></tr> <tr valign="top"><td>tt</td> <td> array of observed travel-time arrivals (length = k).</td></tr> <tr valign="top"><td>z</td> <td> array of depths of each travel-time measurement, in meters (length = k).</td></tr> <tr valign="top"><td>hoffset</td> <td> horizontal offset at the surface from the borehole.</td></tr> <tr valign="top"><td>N</td> <td> k by n matrix of transits.</td></tr> <tr valign="top"><td>theta</td> <td> k by n matrix of angles of incidence when snell == TRUE. Otherwise defaults to 0.</td></tr> <tr valign="top"><td>LM.tt</td> <td> array of predicted travel-times (length = k).</td></tr> <tr valign="top"><td>wt</td> <td> array of weights used in the regression (length = k). Defaults to 1 if sig is unspecified. Calculated as 1/sig^2</td></tr> <tr valign="top"><td>sig</td> <td> array of the standard deviation of the travel-time measurements normalized to the standard deviation of the best pick (length = k).</td></tr> <tr valign="top"><td>se</td> <td> array of standard error of slowness for each layer (length = n). Used to calculate the upper and lower bounds in the velocity model.</td></tr> <tr valign="top"><td>sigma.hat</td> <td> sqrt(sum(res^2*wt)/(k-n)) </td></tr> <tr valign="top"><td>v.upper</td> <td> array of layer velocities corresponding to s_i - se_i (length = n).</td></tr> <tr valign="top"><td>v.lower</td> <td> array of layer velocities corresponding to s_i + se_i (length = n).</td></tr> <tr valign="top"><td>tt.slant</td> <td> array of observed travel-time measurements (length = k).</td></tr> <tr valign="top"><td>snell</td> <td> logical value for if the Snell's Law raypaths should be used. If FALSE, then raypaths are assumed to be straight lines from source to receiver.</td></tr>
一个列表，其中包含模型信息和原始数据。列表中的具体内容是：<table summary="R valueblock"> <tr valign="top"> <TD> A</ TD> <TD> A = sum(n_i * h_i * s_i)</ TD> < / TR> <tr valign="top"> <TD> s </ TD> <TD>数组，包含每个层（长度=n）</ TD> </ TR缓慢的> <tr valign="top"> <TD> v </ TD> <TD>数组，包含每一层的速度（长=n）</ TD> </ TR> < TR VALIGN =“顶”> <TD>n </ TD> <TD>整数速度模型层。</ TD> </ TR> <tr valign="top"> <TD> k</ TD>旅行时测量<TD>数。</ TD> </ TR> <tr valign="top"> <TD>h</ TD> <TD>每一层阵列的厚度（长度=n）</ TD> </ TR> <tr valign="top"> <TD> bot</ TD> <TD>数组的深度每一层的底部（长度=n）</ TD> </ TR> <tr valign="top"> <TD>tt </ TD> <TD>阵列观测到的旅游时来港定居人士（长度=k）</ TD> </ TR> <tr valign="top"> <TD>z </ TD> <TD>阵列的每一个旅游的深度测量时间，单位为米（长度=k）</ TD> </ TR> <tr valign="top"> <TD> hoffset</ TD> <TD>水平偏移从钻孔中。</ TD> </ TR> <tr valign="top"> <TD>N </ TD> <TD>kn矩阵的表面过境。</ TD> </ TR> <tr valign="top"> <TD>theta </ TD> <TD>kn矩阵发病时的角度snell == TRUE。否则默认为0。</ TD> </ TR> <tr valign="top"> <TD> LM.tt </ TD> <TD>阵列的预测旅行时间（长度=k ）</ TD> </ TR> <tr valign="top"> <TD> wt </ TD> <TD>的回归权重数组（长度=k）。默认为1，如果信号是不确定的。计算公式为1/sig^2</ TD> </ TR> <tr valign="top"> <TD>sig </ TD> <TD>阵列归的行程时间测量的标准偏差最好的选择（长度=k）</ TD> </ TR> <tr valign="top"> <TD>se </ TD> <TD>阵列的标准偏差缓慢的每一层的标准误差（长度=n）。用于计算速度模型的上限和下限。</ TD> </ TR> <tr valign="top"> <TD>sigma.hat </ TD> <TD>sqrt(sum(res^2*wt)/(k-n)) / TD> </ TR> <tr valign="top"> <TD> v.upper </ TD> <TD>阵列层的速度相应s_i - se_i（长=n） </ TD> </ TR> <tr valign="top"> <TD> v.lower</ TD> <TD>阵列层的速度相应s_i + se_i（长=n ）</ TD> </ TR> <tr valign="top"> <TD>tt.slant </ TD> <TD>阵列观测到的旅行时间测量（长度=k） </ TD> </ TR> <tr valign="top"> <TD>snell </ TD>斯涅尔定律的射线路径，应使用<TD>逻辑值。如果为FALSE，然后的射线路径被假定为从源到接收器的直线。</ TD> </ TR>
</table>
</ TABLE>
（作者）----------Author(s)----------
Eric M. Thompson <eric.thompson@tufts.edu>
参考文献----------References----------
Boore, D. M. (2003) A compendium of p- and s-wave velocities from surface-to-borehole logging: Summary and reanalysis of previously published data and analysis of unpublished data U.S. Geological Survey Open-File Report 03-191.
Faraway, J. J. (2005) Linear Models with R Chapman & Hall/CRC.
实例----------Examples----------
# Load table of Dave Boore's downhole seismic data:[戴夫Boore的井下地震数据装入表：]
data(tt.s) # S-wave arrivals[S-波到]
# Select hole code 293:[选择孔码293：]
f <- tt.s$hole.code == 293
example <- tt.s[f, ]
data <- list(tt.slant = example$tt.slant,
hoffset = example$hoffset[1],
z = example$z,
sig = example$sig,
hole.code = 293)
# If Using the Windows GUI, it is best to uncheck the 'Buffered output'[如果使用的是Windows图形用户界面，它是最好不要选择“缓冲输出”]
# option in the Misc pull-down menu. This will allow you to see the[在“杂项”的下拉菜单中的选项。这将允许你看到的]
# outputs to the console as they occur rather than all at once at the[输出到控制台所发生的，而不是一次在]
# end.[结束。]
# The command to calculate the layered model is:[计算分层模型的命令是：]
mod1 <- Rvelslant(data)
# The default is to use depth on the vertical axis. However, if you[默认情况下是使用深度的垂直轴。但是，如果您]
# prefer depth to be displayed on the horizontal axis, use:[宁愿深度上要显示在水平轴上，使用：]
mod1 <- Rvelslant(data, depth = "h")
#####################################################[＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃ ＃＃]
# Notes:[注：]
# You can select layer boundaries by clicking on the[您可以通过点击选择层边界]
# travel-time or residual plots. You can remove a[旅游时间或剩余图。您可以删除]
# boundary by left clicking on it in the velocity[边界用鼠标左键点击它的速度]
# profile plot.[剖面图。]
# Right-click anywhere once your have found a model[右键单击任何地方，一旦你发现了一个模型]
# that you want to save.[要保存。]
# -> In WINDOWS must select 'stop' after right-click[ - > WINDOWS后，用鼠标右键单击，选择“停止”]
# -> In MAC OS, can use ESC key instead if you don't[ - >在MAC OS中，可以使用ESC键，而是如果你不这样做]
# have a second mouse button.[第二个鼠标按钮。]
# The layered model depth to bottom, thickness, and[上下的分层模型的深度，厚度，以及]
# velocity will be printed to the terminal.[速度将被打印到终端。]
# The default is to calculate the refracted ray path[默认值是计算折射光线路径]
# according to Snell's law and iteratively update[根据斯奈尔定律和迭代更新]
# the velocity mode. To override this, and do the[速度模式。要覆盖，并做]
# inversion assuming the raypaths are straight lines[反转假设射线路径是直线]
# from source to receiver, use:[从源到接收器，使用：]
mod2 <- Rvelslant(data, snell = FALSE, ntick = 10, grid = TRUE)
# To use the auto picker:[要使用自动选择器：]
mod3 <- Rvelslant(data, auto = TRUE)
# To manually enter layer interfaces:[要手动输入层接口：]
mod4 <- Rvelslant(data, bot = c(6.2, 9.5, 14.5, 29.5,
47, 54.5, 74.5, 89.5))
# To view the profiles, type:[要查看配置文件，请键入：]
velprofile(mod1)
velprofile(mod2, col = "green")
# If you have more than one model and you want to compare the profiles:[如果你有一个以上的模型，你要比较的配置文件：]
velprofile(mod1, col = "black")
velprofile(mod2, add = TRUE, col = "red")
velprofile(mod3, add = TRUE, col = "blue")
# To view the fit of travel-times and the residuals:[要查看适合的旅行时间和残差：]
par(mfrow = c(1, 2))
plotmod(mod1)
plotresid(mod1)
# To save the model to a file[要保存到一个文件中的模型]
writemod(mod1, prefix = "hc293")
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-29 00:00:53
