# Geologic model make a density and S wave velocity model
density = 2650*np.ones(shape) # botucatu
density[0:int(600/dz), :] = 2120 # bauru
density[int(600/dz):int(600/dz)+int(120/dz), :] = 2750 # basalt flow 1
density[int(600/dz)+int(120/dz):int(600/dz)+int(240/dz), :] = 2540 # basalt flow 2
pvel = 3200*np.ones(shape) # botucatu
pvel[0:int(600/dz), :] = 2181 # bauru
pvel[int(600/dz):int(600/dz)+int(120/dz), :] = 4800 # basalt flow 1
pvel[int(600/dz)+int(120/dz):int(600/dz)+int(240/dz), :] = 3540 # basalt flow 2
svel = 1600*np.ones(shape) # botucatu
svel[0:int(600/dz), :] = 1166 # bauru
svel[int(600/dz):int(600/dz)+int(120/dz), :] = 2611 # basalt flow 1
svel[int(600/dz)+int(120/dz):int(600/dz)+int(240/dz), :] = 1900 # basalt flow 2
mu = wavefd.lame_mu(svel, density)
lamb = wavefd.lame_lamb(pvel, svel, density)
# Make a wave source from a gauss derivative that vibrates in the z direction only
# (removes the shear component amplitude equals zero, simulating a default seismic acquisition)
sources = [[wavefd.GaussSource(2000, 0, area, shape, 0.0, 5.)], # x source or shear source
[wavefd.GaussSource(2000, 0, area, shape, 100.0, 25.)]] # z source or z compressional source
# Get the iterator for the simulation
dt = wavefd.maxdt(area, shape, np.max(pvel))
duration = 3.0
maxit = int(duration/dt)
stations = [[2200+i*dx, 0] for i in range(220)] # x, z coordinate of the seismometers
snapshot = int(0.004/dt) # Plot a snapshot of the simulation every 4 miliseconds
print "dt for simulation is ", dt
print "max iteration for simulation is ", maxit
"""
Seismic: 2D finite difference simulation of elastic SH wave propagation
"""
import numpy as np
from matplotlib import animation
from fatiando import gridder
from fatiando.seismic import wavefd
from fatiando.vis import mpl
# Set the parameters of the finite difference grid
shape = (150, 150)
area = [0, 60000, 0, 60000]
# Make a density and S wave velocity model
density = 2400 * np.ones(shape)
velocity = 3700
mu = wavefd.lame_mu(velocity, density)
# Make a wave source from a mexican hat wavelet
sources = [wavefd.MexHatSource(30000, 15000, area, shape, 100, 1, delay=2)]
# Get the iterator for the simulation
dt = wavefd.maxdt(area, shape, velocity)
duration = 20
maxit = int(duration / dt)
stations = [[50000, 0]] # x, z coordinate of the seismometer
snapshot = int(0.5 / dt) # Plot a snapshot of the simulation every 0.5 seconds
simulation = wavefd.elastic_sh(mu, density, area, dt, maxit, sources, stations,
snapshot, padding=50, taper=0.01)
# This part makes an animation using matplotlibs animation API
fig = mpl.figure(figsize=(14, 5))
Seismic: 2D finite difference simulation of elastic P and SV wave propagation
"""
import numpy as np
from matplotlib import animation
from fatiando import gridder
from fatiando.seismic import wavefd
from fatiando.vis import mpl
# Set the parameters of the finite difference grid
shape = (200, 200)
area = [0, 60000, 0, 60000]
# Make a density and S wave velocity model
density = 2400 * np.ones(shape)
pvel = 6600
svel = 3700
mu = wavefd.lame_mu(svel, density)
lamb = wavefd.lame_lamb(pvel, svel, density)
# Make a wave source from a mexican hat wavelet that vibrates in the x and z
# directions equaly
sources = [[wavefd.MexHatSource(30000, 40000, area, shape, 10000, 1, delay=1)],
[wavefd.MexHatSource(30000, 40000, area, shape, 10000, 1, delay=1)]]
# Get the iterator for the simulation
dt = wavefd.maxdt(area, shape, pvel)
duration = 20
maxit = int(duration / dt)
stations = [[55000, 0]] # x, z coordinate of the seismometer
snapshot = int(0.5 / dt) # Plot a snapshot of the simulation every 0.5 seconds
simulation = wavefd.elastic_psv(lamb,
mu,
"""
Seismic: 2D finite difference simulation of elastic SH wave propagation
"""
import numpy as np
from matplotlib import animation
from fatiando import gridder
from fatiando.seismic import wavefd
from fatiando.vis import mpl
# Set the parameters of the finite difference grid
shape = (150, 150)
area = [0, 60000, 0, 60000]
# Make a density and S wave velocity model
density = 2400 * np.ones(shape)
velocity = 3700
mu = wavefd.lame_mu(velocity, density)
# Make a wave source from a mexican hat wavelet
sources = [wavefd.MexHatSource(30000, 15000, area, shape, 100, 1, delay=2)]
# Get the iterator for the simulation
dt = wavefd.maxdt(area, shape, velocity)
duration = 20
maxit = int(duration / dt)
stations = [[50000, 0]] # x, z coordinate of the seismometer
snapshot = int(0.5 / dt) # Plot a snapshot of the simulation every 0.5 seconds
simulation = wavefd.elastic_sh(mu,
density,
area,
dt,
maxit,
