{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n# Synthetic seismic\nThis example shows how to use the :py:mod:`pylops.utils.seismicevents` module\nto quickly create synthetic seismic data to be used for toy examples and tests.\n\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import numpy as np\nimport matplotlib.pyplot as plt\n\nimport pylops\n\nplt.close('all')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's first define the time and space axes as well as some auxiliary input\nparameters that we will use to create a Ricker wavelet\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "par = {'ox':-200, 'dx':2, 'nx':201,\n 'oy':-100, 'dy':2, 'ny':101,\n 'ot':0, 'dt':0.004, 'nt':501,\n 'f0': 20, 'nfmax': 210}\n\n# Create axis\nt, t2, x, y = pylops.utils.seismicevents.makeaxis(par)\n\n# Create wavelet\nwav = pylops.utils.wavelets.ricker(np.arange(41) * par['dt'],\n f0=par['f0'])[0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We want to create a 2d data with a number of crossing linear events using the\n:py:func:`pylops.utils.seismicevents.linear2d` routine.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "v = 1500\nt0 = [0.2, 0.7, 1.6]\ntheta = [40, 0, -60]\namp = [1., 0.6, -2.]\n\nmlin, mlinwav = pylops.utils.seismicevents.linear2d(x, t, v, t0,\n theta, amp, wav)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also create a 2d data with a number of crossing parabolic events using the\n:py:func:`pylops.utils.seismicevents.parabolic2d` routine.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "px = [0, 0, 0]\npxx = [1e-5, 5e-6, 1e-6]\n\nmpar, mparwav = pylops.utils.seismicevents.parabolic2d(x, t, t0, px,\n pxx, amp, wav)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And similarly we can create a 2d data with a number of crossing hyperbolic\nevents using the :py:func:`pylops.utils.seismicevents.hyperbolic2d` routine.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "vrms = [500, 700, 1700]\n\nmhyp, mhypwav = pylops.utils.seismicevents.hyperbolic2d(x, t, t0,\n vrms, amp, wav)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can now visualize the different events\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# sphinx_gallery_thumbnail_number = 2\nfig, axs = plt.subplots(1, 3, figsize=(9, 5))\naxs[0].imshow(mlinwav.T, aspect='auto', interpolation='nearest',\n vmin=-2, vmax=2, cmap='gray',\n extent=(x.min(), x.max(), t.max(), t.min()))\naxs[0].set_title('Linear events', fontsize=12, fontweight='bold')\naxs[0].set_xlabel(r'$x(m)$')\naxs[0].set_ylabel(r'$t(s)$')\naxs[1].imshow(mparwav.T, aspect='auto', interpolation='nearest',\n vmin=-2, vmax=2, cmap='gray',\n extent=(x.min(), x.max(), t.max(), t.min()))\naxs[1].set_title('Parabolic events', fontsize=12, fontweight='bold')\naxs[1].set_xlabel(r'$x(m)$')\naxs[1].set_ylabel(r'$t(s)$')\naxs[2].imshow(mhypwav.T, aspect='auto', interpolation='nearest',\n vmin=-2, vmax=2, cmap='gray',\n extent=(x.min(), x.max(), t.max(), t.min()))\naxs[2].set_title('Hyperbolic events', fontsize=12, fontweight='bold')\naxs[2].set_xlabel(r'$x(m)$')\naxs[2].set_ylabel(r'$t(s)$')\nplt.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's finally repeat the same exercise in 3d\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "phi = [20, 0, -10]\n\nmlin, mlinwav = \\\n pylops.utils.seismicevents.linear3d(x, y, t, v, t0,\n theta, phi, amp, wav)\n\nfig, axs = plt.subplots(1, 2, figsize=(7, 5), sharey=True)\nfig.suptitle('Linear events in 3d', fontsize=12,\n fontweight='bold', y=0.95)\naxs[0].imshow(mlinwav[par['ny']//2].T, aspect='auto',\n interpolation='nearest', vmin=-2, vmax=2,\n cmap='gray', extent=(x.min(), x.max(), t.max(), t.min()))\naxs[0].set_xlabel(r'$x(m)$')\naxs[0].set_ylabel(r'$t(s)$')\naxs[1].imshow(mlinwav[:, par['nx']//2].T, aspect='auto',\n interpolation='nearest', vmin=-2, vmax=2,\n cmap='gray', extent=(y.min(), y.max(), t.max(), t.min()))\naxs[1].set_xlabel(r'$y(m)$')\n\nmhyp, mhypwav = \\\n pylops.utils.seismicevents.hyperbolic3d(x, y, t, t0, vrms, vrms, amp, wav)\n\nfig, axs = plt.subplots(1, 2, figsize=(7, 5), sharey=True)\nfig.suptitle('Hyperbolic events in 3d', fontsize=12,\n fontweight='bold', y=0.95)\naxs[0].imshow(mhypwav[par['ny']//2].T, aspect='auto',\n interpolation='nearest', vmin=-2, vmax=2,\n cmap='gray', extent=(x.min(), x.max(), t.max(), t.min()))\naxs[0].set_xlabel(r'$x(m)$')\naxs[0].set_ylabel(r'$t(s)$')\naxs[1].imshow(mhypwav[:, par['nx']//2].T, aspect='auto',\n interpolation='nearest', vmin=-2, vmax=2,\n cmap='gray', extent=(y.min(), y.max(), t.max(), t.min()))\naxs[1].set_xlabel(r'$y(m)$');" ] } ], "metadata": { "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": "3.6.12" } }, "nbformat": 4, "nbformat_minor": 0 }