{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# 2 - Damping" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.1 - Introduction\n", "\n", "In this notebook we describe a simple method for reduction of reflections at the computational boundaries of the domain $\\Omega$ when we simulate the acoustic wave equation. This method, called *Damping*, has been proposed by Sochaki. It adds a damping term, modifying the original wave equation at a boundary layer. We saw in the notebook Introduction to Acoustic Problem that the (artificial) wave reflections on the computational boundaries lead to a very noisy solution of the acoustic problem. \n", "\n", "We describe this method in the next Sections, omitting information already discussed in the notebook Introduction to Acoustic Problem, highlighting only the new elements necessary to apply Damping." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.2 - Acoustic Problem with Damping\n", "\n", "We define an extension of the spatial domain $\\Omega=\\left[x_{I}-L_{x},x_{F}+L_{x}\\right] \\times\\left[z_{I},z_{F}+L_{z}\\right]$, in which we added an *absorption region* to the previous spatial domain\n", "$\\Omega_{0}=\\left[x_{I},x_{F}\\right]\\times\\left[z_{I},z_{F}\\right]$. \n", "The *absorption region* is composed by two bands of length $L_{x}$ at the beginning and end of the domain in the direction $x$ and of a band of length $L_{z}$ at the end of the domain in the $z$ direction. Again, $\\partial\\Omega$ denotes the boundary of $\\Omega$. The figure below shows the extended domain $\\Omega$, with the absorption region highlighted in blue.\n", "\n", "\n", "\n", "The damping acoustic problem equation is given by:\n", "\n", "\\begin{equation}\n", "u_{tt}(x,z,t)+c^2(x,z)\\zeta(x,z)u_t(x,z,t)-c^2(x,z)\\Delta(u(x,z,t))=c^2(x,z)f(x,z,t),\n", "\\end{equation}\n", "\n", "where $u(x,z,t)$, $f(x,z,t)$ and $c(x,z)$ are as before. The wave equation has been modified by the introduction of the damping term $c^2(x,z)\\zeta(x,z)u_t(x,z,t)$, where $\\zeta$ is different from zero only in the absorption region, growing smoothly along the absorption bands from zero to its maximum at the outer boundary. The actual form of\n", "$\\zeta$ used in this notebook will be given ahead. We still use the same initial conditions\n", "\n", "\\begin{equation}\n", "u(x,z,0) = 0.0 \\hspace{.5cm} \\mbox{ and } \\hspace{.5cm} u_t(x,z,0)= 0.0.\n", "\\end{equation}\n", "\n", "and Dirichlet null boundary conditions at the (outer) bottom and lateral boundaries. At the surface we\n", "use a zero Neumman boundary condition.\n", "\n", "The source term and the velocity field are defined as before." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.3 - Finite Difference Operators and Discretization of Spatial and Temporal Domains\n", "\n", "The only difference with respect to the discretization used in the notebook Introduction to Acoustic Problem is the extra damping term. The temporal derivative of $u$ is approximated by a centered difference:\n", "$$ u_t(x_i,z_j,t_k) = \\frac{u_{i,j,k+1}-u_{i,j,k-1}}{2\\Delta t} $$. All the other terms are discretized as before.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.4 - Standard Problem\n", "\n", "Redeeming the Standard Problem definitions discussed on the notebook Introduction to Acoustic Problem we have that:\n", "\n", "- $x_{I}$ = 0.0 Km;\n", "- $x_{F}$ = 1.0 Km = 1000 m;\n", "- $z_{I}$ = 0.0 Km;\n", "- $z_{F}$ = 1.0 Km = 1000 m;\n", "- $L_x$ and $L_z$ will be defined ahead;\n", "\n", "The spatial discretization parameters are given by:\n", "- $\\Delta x$ = 0.01 km = 10m;\n", "- $\\Delta z$ = 0.01 km = 10m;\n", "\n", "Let's consider a $I$ the time domain with the following limitations:\n", "\n", "- $t_{I}$ = 0 s = 0 ms;\n", "- $t_{F}$ = 1 s = 1000 ms;\n", "\n", "The temporal discretization parameters are given by:\n", "\n", "- $\\Delta t$ $\\approx$ 0.0016 s = 1.6 ms;\n", "- $NT$ = 626.\n", "\n", "With respect to the $f(x,z,t)$ external force term, we will consider a Ricker source with the following properties:\n", "\n", "- Position at $x:$ $\\bar{x} = 500 m = 0.5 Km$;\n", "- Position at $z:$ $\\bar{z} = 10 m = 0.01 Km$;\n", "- Peak frequency: $f_{0} = 10 Hz = 0.01 Khz$;\n", "\n", "The graph of $f(\\bar{x},\\bar{z},t)$ will be generated when building the code. We will use a velocity profile $c(x, z)$ with the following properties:\n", "\n", "- Minimum propagation velocity: $v_{min} = 1500 m/s = 1,5 Km/s$;\n", "- Maximum propagation velocity: $v_{max} = 2500 m/s = 2,5 Km/s$;\n", "\n", "The figure of the velocity profile will be generated when building the code. We introduce receivers along the $x$ direction, that is, at all discrete points between $0.0$ Km and $1.0$ Km , at depth $z=0.01$ Km to generate the seismogram." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.5 - Damping Functions\n", "\n", "Sochaki proposed various forms for the damping function $\\zeta$, including linear, cubic or exponential functions. In general, the damping functions have a similar characteristic: they are zero in the \"interior\" domain $\\Omega_{0}$ and increase toward the outer boundary $\\partial\\Omega$. \n", "\n", "Our particular damping function will be chosen as follows.\n", " We define the pair of functions $\\zeta_{1}(x,z)$ and $\\zeta_{2}(x,z)$ given, respectively, by:\n", "\n", "\\begin{equation}\n", "\\zeta_{1}(x,z)=\\left\\{ \\begin{array}{ll}\n", "0, & \\textrm{if $x\\in \\left(x_{I},x_{F}\\right)$,}\\\\ \\bar{\\zeta}_{1}(x,z)\\left(\\displaystyle\\frac{\\vert x-x_{I} \\vert}{L_{x}}-\\displaystyle\\frac{1}{2\\pi}\\sin\\left(\\displaystyle\\frac{2\\pi\\vert x-x_{I} \\vert}{L_{x}}\\right)\\right) , & \\textrm{if $x_{I}-L_{x}\\leq x \\leq x_{I}$,}\\\\ \\bar{\\zeta}_{1}(x,z)\\left(\\displaystyle\\frac{\\vert x-x_{F} \\vert}{L_{x}}-\\displaystyle\\frac{1}{2\\pi}\\sin\\left(\\displaystyle\\frac{2\\pi\\vert x-x_{F} \\vert}{L_{x}}\\right)\\right) , & \\textrm{if $x_{F}\\leq x \\leq x_{F}+L_{x}$.}\\end{array}\\right.\n", "\\end{equation} \n", "\n", "\\begin{equation}\n", "\\zeta_{2}(x,z)=\\left\\{ \\begin{array}{ll}\n", "0, & \\textrm{if $z\\in \\left(z_{I},z_{F}\\right)$,} \\\\ \\bar{\\zeta}_{2}(x,z)\\left(\\displaystyle\\frac{\\vert z-z_{F} \\vert}{L_{z}}-\\displaystyle\\frac{1}{2\\pi}\\sin\\left(\\displaystyle\\frac{2\\pi\\vert z-z_{F} \\vert}{L_{z}}\\right)\\right) , & \\textrm{if $z_{F}\\leq z \\leq z_{F}+L_{z}$.}\\end{array}\\right.\n", "\\end{equation} \n", "\n", "Thus, we define the function $\\zeta(x,z)$ as being the following function:\n", "\n", "\\begin{equation}\n", "\\zeta(x,z) = \\displaystyle\\frac{1}{v_{max}}\\left(\\displaystyle\\frac{\\zeta_{1}(x,z)}{\\Delta x}+\\displaystyle\\frac{\\zeta_{2}(x,z)}{\\Delta z} \\right) ,\n", "\\end{equation}\n", "\n", "where $v_{max}$denotes the maximum velocity of propagation of $c(x,z)$. Below we display the shape of the function $\\zeta_1(x,z)$ with $\\bar{\\zeta_{1}}(x,z)=0.26$ at the left band of the domain. It is similar at the other ones. The figures of the damping profiles will be generated when building the code." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.6 - Numerical Simulations\n", "\n", "In the numerical simulations we import the following Python and Devito packages:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "import numpy as np\n", "import matplotlib.pyplot as plot\n", "import math as mt\n", "import matplotlib.ticker as mticker \n", "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", "from matplotlib import cm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From Devito's library of examples we import the following structures:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "%matplotlib inline\n", "from examples.seismic import TimeAxis\n", "from examples.seismic import RickerSource\n", "from examples.seismic import Receiver\n", "from devito import SubDomain, Grid, NODE, TimeFunction, Function, Eq, solve, Operator" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The mesh parameters define the domain $\\Omega_{0}$. The absorption region will be included bellow." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "nptx = 101\n", "nptz = 101\n", "x0 = 0.\n", "x1 = 1000. \n", "compx = x1-x0\n", "z0 = 0.\n", "z1 = 1000.\n", "compz = z1-z0;\n", "hxv = (x1-x0)/(nptx-1)\n", "hzv = (z1-z0)/(nptz-1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Observation:** In this code we need to work with symbolic values and the real values of $\\Delta x$ and $\\Delta z$, then the numerica values of $\\Delta x$ and $\\Delta z$ are represented by *hxv* and *hzv*, respectively. The symbolic values of $\\Delta x$ and $\\Delta z$ will be given after.\n", "\n", "In this case, we need to define the size of the bands $L_{x}$ and $L_{z}$ that extend the domain $\\Omega_{0}$ for $\\Omega$. The code that we will implement will build the values $L_{x}$ and $L_{z}$ from choosing a certain amount of points in each direction. Without loss of generality, we say that the size $L_{x}$ is such that:\n", "\n", "- $L_{x}$ = npmlx*$\\Delta x$;\n", "- *0\n", "\n", "The advantage of dividing into regions is that the equations will be calculated where they actually operate and thus we gain computational efficiency, as we decrease the number of operations to be done. After defining the spatial parameters and constructing the *subdomains*, we set the *spatial grid* with the following command:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "grid = Grid(origin=origin, extent=extent, shape=shape, subdomains=(d0_domain,d1_domain,d2_domain,d3_domain), dtype=np.float64)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again, we use a velocity field given by a binary file. The reading and scaling of the velocity field for the Devito work units is done with the following commands:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "v0 = np.zeros((nptx,nptz)) \n", "X0 = np.linspace(x0,x1,nptx)\n", "Z0 = np.linspace(z0,z1,nptz)\n", " \n", "x10 = x0+lx\n", "x11 = x1-lx\n", " \n", "z10 = z0\n", "z11 = z1 - lz\n", "\n", "xm = 0.5*(x10+x11)\n", "zm = 0.5*(z10+z11)\n", " \n", "pxm = 0\n", "pzm = 0\n", " \n", "for i in range(0,nptx):\n", " if(X0[i]==xm): pxm = i\n", " \n", "for j in range(0,nptz):\n", " if(Z0[j]==zm): pzm = j\n", " \n", "p0 = 0 \n", "p1 = pzm\n", "p2 = nptz\n", " \n", "v0[0:nptx,p0:p1] = 1.5\n", "v0[0:nptx,p1:p2] = 2.5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Previously we introduce the local variables *x10,x11,z10,z11,xm,zm,pxm* and *pzm* that help us to create a specific velocity field, where we consider the whole domain (including the absorpion region). Below we include a routine to plot the velocity field." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "def graph2dvel(vel):\n", " plot.figure()\n", " plot.figure(figsize=(16,8))\n", " fscale = 1/10**(3)\n", " scale = np.amax(vel[npmlx:-npmlx,0:-npmlz])\n", " extent = [fscale*(x0+lx),fscale*(x1-lx), fscale*(z1-lz), fscale*(z0)]\n", " fig = plot.imshow(np.transpose(vel[npmlx:-npmlx,0:-npmlz]), vmin=0.,vmax=scale, cmap=cm.seismic, extent=extent)\n", " plot.gca().xaxis.set_major_formatter(mticker.FormatStrFormatter('%.1f km'))\n", " plot.gca().yaxis.set_major_formatter(mticker.FormatStrFormatter('%.1f km'))\n", " plot.title('Velocity Profile')\n", " plot.grid()\n", " ax = plot.gca()\n", " divider = make_axes_locatable(ax)\n", " cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", " cbar = plot.colorbar(fig, cax=cax, format='%.2e')\n", " cbar.set_label('Velocity [km/s]')\n", " plot.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Below we include the plot of velocity field." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "graph2dvel(v0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Time parameters are defined and constructed by the following sequence of commands:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "t0 = 0.\n", "tn = 1000. \n", "CFL = 0.4\n", "vmax = np.amax(v0) \n", "dtmax = np.float64((min(hxv,hzv)*CFL)/(vmax))\n", "ntmax = int((tn-t0)/dtmax)+1\n", "dt0 = np.float64((tn-t0)/ntmax)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With the temporal parameters, we generate the time informations with *TimeAxis* as follows:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "time_range = TimeAxis(start=t0,stop=tn,num=ntmax+1)\n", "nt = time_range.num - 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The symbolic values associated with the spatial and temporal grids that are used in the composition of the equations are given by:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "(hx,hz) = grid.spacing_map \n", "(x, z) = grid.dimensions \n", "t = grid.stepping_dim\n", "dt = grid.stepping_dim.spacing" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We chose a single Ricker source, whose frequency is $ 0.005Khz $. This source is positioned at $\\bar{x}$ = 35150m and $\\bar{z}$ = 32m. We then defined the following variables that represents our choice:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "f0 = 0.01\n", "nsource = 1\n", "xposf = 0.5*(compx-2*npmlx*hxv)\n", "zposf = hzv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we know, Ricker's source is generated by the *RickerSource* command. Using the parameters listed above, we generate and position the Ricker source with the following sequence of commands:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "src = RickerSource(name='src',grid=grid,f0=f0,npoint=nsource,time_range=time_range,staggered=NODE,dtype=np.float64)\n", "src.coordinates.data[:, 0] = xposf\n", "src.coordinates.data[:, 1] = zposf" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Below we include the plot of Ricker source." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "src.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With respect to receivers, the number of receivers is the same number of discrete points in the $x$ direction. So, we position these receivers along the direction $x$, at height $\\bar{z}$ = 10m. In this way, our variables are chosen as:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "nrec = nptx\n", "nxpos = np.linspace(x0,x1,nrec)\n", "nzpos = hzv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we know, receivers are generated by the command *Receiver*. Thus, we use the parameters listed above and using the *Receiver* command, we create and position the receivers:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "rec = Receiver(name='rec',grid=grid,npoint=nrec,time_range=time_range,staggered=NODE,dtype=np.float64)\n", "rec.coordinates.data[:, 0] = nxpos\n", "rec.coordinates.data[:, 1] = nzpos" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The displacement field *u* is a second order field in time and space, which uses points of type *non-staggered*. In this way, we construct the displacement field *u* with the command *TimeFunction*:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "u = TimeFunction(name=\"u\",grid=grid,time_order=2,space_order=2,staggered=NODE,dtype=np.float64)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The velocity field, the source term and receivers are defined as in the previous notebook: " ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "vel0 = Function(name=\"vel0\",grid=grid,space_order=2,staggered=NODE,dtype=np.float64)\n", "vel0.data[:,:] = v0[:,:]" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "src_term = src.inject(field=u.forward,expr=src*dt**2*vel0**2)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "rec_term = rec.interpolate(expr=u)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The next step is to create the sequence of structures that reproduce the function $\\zeta(x,z)$. Initially, we define the region $\\Omega_{0}$, since the damping function uses the limits of that region. We previously defined the limits of the $\\Omega$ region to be *x0*, *x1*, *z0* and *z1*. Now, we define the limits of the region $\\Omega_{0}$ as: *x0pml* and *x1pml* in the direction $x$ and *z0pml* and *z1pml* in the direction $z$. These points satisfy the following relationships with the lengths $L_{x}$ and $L_{z}$:\n", "\n", "- x0pml = x0 + $L_{x}$;\n", "- x1pml = x1 - $L_{x}$;\n", "- z0pml = z0;\n", "- z1pml = z1 - $L_{z}$;\n", "\n", "In terms of program variables, we have the following definitions:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "x0pml = x0 + npmlx*hxv \n", "x1pml = x1 - npmlx*hxv \n", "z0pml = z0 \n", "z1pml = z1 - npmlz*hzv " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Having built the $\\Omega$ limits, we then create a function, which we will call *fdamp*, which computationally represents the $\\zeta(x,z)$ function. In the *fdamp* function, we highlight the following elements:\n", "\n", "- *quibar* represents a constant choice for $\\bar{\\zeta_{1}}(x,z)$ and $\\bar{\\zeta_{2}}(x,z)$, satisfying $\\bar{\\zeta_{1}}(x,z)=\\bar{\\zeta_{2}}(x,z)$;\n", "- *adamp* denotes the function $\\zeta_{1}(x,z)$;\n", "- *bdamp* denotes the function $\\zeta_{2}(x,z)$;\n", "- The terms *a* and *b* locate the $(x,z)$ points that are passed as an argument to the *fdamp* function.\n", "\n", "The *fdamp* function is defined using the following structure:" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "def fdamp(x,z):\n", "\n", " quibar = 1.5*np.log(1.0/0.001)/(40)\n", " cte = 1./vmax\n", " \n", " a = np.where(x<=x0pml,(np.abs(x-x0pml)/lx),np.where(x>=x1pml,(np.abs(x-x1pml)/lx),0.))\n", " b = np.where(z<=z0pml,(np.abs(z-z0pml)/lz),np.where(z>=z1pml,(np.abs(z-z1pml)/lz),0.))\n", " adamp = quibar*(a-(1./(2.*np.pi))*np.sin(2.*np.pi*a))/hxv\n", " bdamp = quibar*(b-(1./(2.*np.pi))*np.sin(2.*np.pi*b))/hzv\n", " fdamp = cte*(adamp+bdamp)\n", "\n", " return fdamp" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Created the damping function, we define an array that loads the damping information in the entire domain $\\Omega$. The objective is to assign this array to a *Function* and use it in the composition of the equations. To generate this array, we will use the function *generatemdamp*. In summary, this function generates a *non-staggered* grid and evaluates that grid in the *fdamp* function. At the end, we generate an array that we call *D0* and which will be responsible for providing the damping value at each of the $\\Omega$ points. The *generatemdamp* function is expressed as follows:" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "def generatemdamp():\n", " \n", " X0 = np.linspace(x0,x1,nptx) \n", " Z0 = np.linspace(z0,z1,nptz) \n", " X0grid,Z0grid = np.meshgrid(X0,Z0) \n", " D0 = np.zeros((nptx,nptz)) \n", " D0 = np.transpose(fdamp(X0grid,Z0grid))\n", " \n", " return D0" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Built the function *generatemdamp* we will execute it using the command:" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "D0 = generatemdamp();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Below we include a routine to plot the damping field." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "def graph2damp(D): \n", " plot.figure()\n", " plot.figure(figsize=(16,8))\n", " fscale = 1/10**(-3)\n", " fscale = 10**(-3)\n", " scale = np.amax(D)\n", " extent = [fscale*x0,fscale*x1, fscale*z1, fscale*z0]\n", " fig = plot.imshow(np.transpose(D), vmin=0.,vmax=scale, cmap=cm.seismic, extent=extent)\n", " plot.gca().xaxis.set_major_formatter(mticker.FormatStrFormatter('%.1f km'))\n", " plot.gca().yaxis.set_major_formatter(mticker.FormatStrFormatter('%.1f km'))\n", " plot.title('Absorbing Layer Function')\n", " plot.grid()\n", " ax = plot.gca()\n", " divider = make_axes_locatable(ax)\n", " cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", " cbar = plot.colorbar(fig, cax=cax, format='%.2e')\n", " cbar.set_label('Damping')\n", " plot.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Below we include the plot of damping field." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "graph2damp(D0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Like the velocity function $c(x,z)$, the damping function $\\zeta(x,z)$ is constant in time. Therefore, the damping function will be a second-order *Function* in space, which uses points of the non-staggered type and which we will evaluate with the D0 array. The symbolic name *damp* will be assigned to this field." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "damp = Function(name=\"damp\",grid=grid,space_order=2,staggered=NODE,dtype=np.float64)\n", "damp.data[:,:] = D0" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The expressions for the acoustic equation with damping can be separeted between the white and blue regions.\n", "\n", "Translating these expressions in terms of an *eq* that can be inserted in a Devito code, we have that in the white region the equation takes the form:\n", "\n", "- eq1 = u.dt2 - vel0 * vel0 * u.laplace,\n", "\n", "and in the blue region we have the following equation:\n", "\n", "- eq2 = u.dt2 + vel0 * vel0 * damp * u.dtc - vel0 * vel0 * u.laplace.\n", "\n", "Here *u.dtc* represents the centered derivative with respect to the variable $t$ for the field *u*. Then, we set the two pdes for the two regions\n" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "pde0 = Eq(u.dt2 - u.laplace*vel0**2)\n", "pde1 = Eq(u.dt2 - u.laplace*vel0**2 + vel0**2*damp*u.dtc)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we did on the notebook Introduction to Acoustic Problem, we define the *stencils* for each of the *pdes* that we created previously. In the case of *pde0* it is defined only in the white region, which is represented by *subdomain* *d0*. Then, we define the *stencil0* which resolves *pde0* in *d0* and it is defined as follows:" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "stencil0 = Eq(u.forward, solve(pde0,u.forward),subdomain = grid.subdomains['d0'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The *pde1* will be applied in the blue region, the union of the subdomains *d1*, *d2* and *d3*. In this way, we create a vector called *subds* that comprises these three *subdomains*, and we are ready to set the corresponding stencil" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "subds = ['d1','d2','d3']" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "stencil1 = [Eq(u.forward, solve(pde1,u.forward),subdomain = grid.subdomains[subds[i]]) for i in range(0,len(subds))]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The boundary conditions of the problem are kept the same as the notebook Introduction to Acoustic Problem. So these are placed in the term *bc* and have the following form:" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "bc = [Eq(u[t+1,0,z],0.),Eq(u[t+1,nptx-1,z],0.),Eq(u[t+1,x,nptz-1],0.),Eq(u[t+1,x,0],u[t+1,x,1])]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We then define the operator (*op*) that join the acoustic equation, source term, boundary conditions and receivers.\n", "\n", "- 1. The acoustic wave equation in the *d0* region: *[stencil0];*\n", "- 2. The acoustic wave equation in the *d1*, *d2* and *d3* region: *[stencil1];*\n", "- 3. Source term: *src_term;*\n", "- 4. Boundary conditions: *bc;*\n", "- 5. Receivers: *rec_term;*\n" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "op = Operator([stencil0,stencil1] + src_term + bc + rec_term,subs=grid.spacing_map)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We reset the field *u*:" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": [ "u.data[:] = 0." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We assign in *op* the number of time steps it must execute and the size of the time step in the local variables *time* and *dt*, respectively. " ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Operator `Kernel` run in 0.02 s\n" ] }, { "data": { "text/plain": [ "PerformanceSummary([(PerfKey(name='section0', rank=None),\n", " PerfEntry(time=0.013632000000000042, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n", " (PerfKey(name='section1', rank=None),\n", " PerfEntry(time=3.799999999999999e-05, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n", " (PerfKey(name='section2', rank=None),\n", " PerfEntry(time=3.3e-05, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n", " (PerfKey(name='section3', rank=None),\n", " PerfEntry(time=0.00027800000000000025, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n", " (PerfKey(name='section4', rank=None),\n", " PerfEntry(time=0.0010460000000000092, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[]))])" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "op(time=nt,dt=dt0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To view the result of the displacement field at the end time, we use the *graph2d* routine given by:" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "def graph2d(U): \n", " plot.figure()\n", " plot.figure(figsize=(16,8))\n", " fscale = 1/10**(3)\n", " scale = np.amax(U[npmlx:-npmlx,0:-npmlz])/10.\n", " extent = [fscale*x0pml,fscale*x1pml,fscale*z1pml,fscale*z0pml]\n", " fig = plot.imshow(np.transpose(U[npmlx:-npmlx,0:-npmlz]),vmin=-scale, vmax=scale, cmap=cm.seismic, extent=extent)\n", " plot.gca().xaxis.set_major_formatter(mticker.FormatStrFormatter('%.1f km'))\n", " plot.gca().yaxis.set_major_formatter(mticker.FormatStrFormatter('%.1f km'))\n", " plot.axis('equal')\n", " plot.title('Map - Acoustic Problem with Devito')\n", " plot.grid()\n", " ax = plot.gca()\n", " divider = make_axes_locatable(ax)\n", " cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", " cbar = plot.colorbar(fig, cax=cax, format='%.2e')\n", " cbar.set_label('Displacement [km]')\n", " plot.draw()\n", " plot.show()" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "graph2d(u.data[0,:,:])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that the solution obtained here has a reduction in noise when compared to the results displayed on the notebook Introduction to Acoustic Problem. To plot the result of the Receivers we use the *graph2drec* routine." ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [], "source": [ "def graph2drec(rec): \n", " plot.figure()\n", " plot.figure(figsize=(16,8))\n", " fscaled = 1/10**(3)\n", " fscalet = 1/10**(3)\n", " scale = np.amax(rec[:,npmlx:-npmlx])/10.\n", " extent = [fscaled*x0pml,fscaled*x1pml, fscalet*tn, fscalet*t0]\n", " fig = plot.imshow(rec[:,npmlx:-npmlx], vmin=-scale, vmax=scale, cmap=cm.seismic, extent=extent)\n", " plot.gca().xaxis.set_major_formatter(mticker.FormatStrFormatter('%.1f km'))\n", " plot.gca().yaxis.set_major_formatter(mticker.FormatStrFormatter('%.1f s'))\n", " plot.axis('equal')\n", " plot.title('Receivers Signal Profile with Damping - Devito')\n", " ax = plot.gca()\n", " divider = make_axes_locatable(ax)\n", " cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", " cbar = plot.colorbar(fig, cax=cax, format='%.2e')\n", " plot.show()" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "\n", "graph2drec(rec.data)" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [], "source": [ "assert np.isclose(np.linalg.norm(rec.data), 990, rtol=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.6 - Conclusions\n", "\n", "\n", "- The damping strategy is a simple way to reduce artificial wave reflections coming from the computational boundaries, leading to a solution with less noise at the end of the simulation, when compared to the results of the notebook Introduction to Acoustic Problem. However, the level of artificial reflections on the boundaries is still high. In the following notebooks we present methods which are more effective." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.7 - Reference\n", "\n", "- Sochaki, J., Kubichek, R., George, J., Fletcher, W.R. and Smithson, S. (1987). \"Absorbing boundary conditions and surface waves,\" Geophysics, 52(1), 60-71. DOI: 10.1190/1.1442241. Reference Link." ] } ], "metadata": { "hide_input": false, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.5" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false }, "widgets": { "state": {}, "version": "1.1.2" } }, "nbformat": 4, "nbformat_minor": 1 }