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plot_seismicevents.py
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plot_seismicevents.py
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"""
Synthetic seismic
=================
This example shows how to use the :py:mod:`pylops.utils.seismicevents` module
to quickly create synthetic seismic data to be used for toy examples and tests.
"""
import numpy as np
import matplotlib.pyplot as plt
import pylops
plt.close('all')
############################################
# Let's first define the time and space axes as well as some auxiliary input
# parameters that we will use to create a Ricker wavelet
par = {'ox':-200, 'dx':2, 'nx':201,
'oy':-100, 'dy':2, 'ny':101,
'ot':0, 'dt':0.004, 'nt':501,
'f0': 20, 'nfmax': 210}
# Create axis
t, t2, x, y = pylops.utils.seismicevents.makeaxis(par)
# Create wavelet
wav = pylops.utils.wavelets.ricker(np.arange(41) * par['dt'],
f0=par['f0'])[0]
############################################
# We want to create a 2d data with a number of crossing linear events using the
# :py:func:`pylops.utils.seismicevents.linear2d` routine.
v = 1500
t0 = [0.2, 0.7, 1.6]
theta = [40, 0, -60]
amp = [1., 0.6, -2.]
mlin, mlinwav = pylops.utils.seismicevents.linear2d(x, t, v, t0,
theta, amp, wav)
############################################
# We can also create a 2d data with a number of crossing parabolic events using the
# :py:func:`pylops.utils.seismicevents.parabolic2d` routine.
px = [0, 0, 0]
pxx = [1e-5, 5e-6, 1e-6]
mpar, mparwav = pylops.utils.seismicevents.parabolic2d(x, t, t0, px,
pxx, amp, wav)
############################################
# And similarly we can create a 2d data with a number of crossing hyperbolic
# events using the :py:func:`pylops.utils.seismicevents.hyperbolic2d` routine.
vrms = [500, 700, 1700]
mhyp, mhypwav = pylops.utils.seismicevents.hyperbolic2d(x, t, t0,
vrms, amp, wav)
############################################
# We can now visualize the different events
# sphinx_gallery_thumbnail_number = 2
fig, axs = plt.subplots(1, 3, figsize=(9, 5))
axs[0].imshow(mlinwav.T, aspect='auto', interpolation='nearest',
vmin=-2, vmax=2, cmap='gray',
extent=(x.min(), x.max(), t.max(), t.min()))
axs[0].set_title('Linear events', fontsize=12, fontweight='bold')
axs[0].set_xlabel(r'$x(m)$')
axs[0].set_ylabel(r'$t(s)$')
axs[1].imshow(mparwav.T, aspect='auto', interpolation='nearest',
vmin=-2, vmax=2, cmap='gray',
extent=(x.min(), x.max(), t.max(), t.min()))
axs[1].set_title('Parabolic events', fontsize=12, fontweight='bold')
axs[1].set_xlabel(r'$x(m)$')
axs[1].set_ylabel(r'$t(s)$')
axs[2].imshow(mhypwav.T, aspect='auto', interpolation='nearest',
vmin=-2, vmax=2, cmap='gray',
extent=(x.min(), x.max(), t.max(), t.min()))
axs[2].set_title('Hyperbolic events', fontsize=12, fontweight='bold')
axs[2].set_xlabel(r'$x(m)$')
axs[2].set_ylabel(r'$t(s)$')
plt.tight_layout()
############################################
# Let's finally repeat the same exercise in 3d
phi = [20, 0, -10]
mlin, mlinwav = \
pylops.utils.seismicevents.linear3d(x, y, t, v, t0,
theta, phi, amp, wav)
fig, axs = plt.subplots(1, 2, figsize=(7, 5), sharey=True)
fig.suptitle('Linear events in 3d', fontsize=12,
fontweight='bold', y=0.95)
axs[0].imshow(mlinwav[par['ny']//2].T, aspect='auto',
interpolation='nearest', vmin=-2, vmax=2,
cmap='gray', extent=(x.min(), x.max(), t.max(), t.min()))
axs[0].set_xlabel(r'$x(m)$')
axs[0].set_ylabel(r'$t(s)$')
axs[1].imshow(mlinwav[:, par['nx']//2].T, aspect='auto',
interpolation='nearest', vmin=-2, vmax=2,
cmap='gray', extent=(y.min(), y.max(), t.max(), t.min()))
axs[1].set_xlabel(r'$y(m)$')
mhyp, mhypwav = \
pylops.utils.seismicevents.hyperbolic3d(x, y, t, t0, vrms, vrms, amp, wav)
fig, axs = plt.subplots(1, 2, figsize=(7, 5), sharey=True)
fig.suptitle('Hyperbolic events in 3d', fontsize=12,
fontweight='bold', y=0.95)
axs[0].imshow(mhypwav[par['ny']//2].T, aspect='auto',
interpolation='nearest', vmin=-2, vmax=2,
cmap='gray', extent=(x.min(), x.max(), t.max(), t.min()))
axs[0].set_xlabel(r'$x(m)$')
axs[0].set_ylabel(r'$t(s)$')
axs[1].imshow(mhypwav[:, par['nx']//2].T, aspect='auto',
interpolation='nearest', vmin=-2, vmax=2,
cmap='gray', extent=(y.min(), y.max(), t.max(), t.min()))
axs[1].set_xlabel(r'$y(m)$');