{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Variable wedge"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Building on spectral wedge... I would like a wedge that varies rock properties in the *y*-dimension."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"% matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Set up the model parameters."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"length = 100.# x range\n",
"width = 100. # y range\n",
"depth = 240. # z range"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Use the wedge code from Spectral_wedge.ipynb. The main difference is that we will need to use the rock properties directly, rather than building an array of ints first. "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 0.798 0.798 0.588 0.588]\n"
]
}
],
"source": [
"rocks = [(2800, 2850), (2800, 2850), (2400, 2450), (2400,2450)]\n",
"\n",
"def make_ai(rocks):\n",
" rx = np.array(rocks)\n",
" return rx[:,0] * rx[:,1] / 10e6\n",
"\n",
"ai = make_ai(rocks)\n",
"print ai"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def make_earth(depth, length, width, ai):\n",
" \n",
" earth = np.ones((depth,length,width))\n",
" \n",
" for xslice in range(int(length)):\n",
" thickness = (depth/3)*(1 + xslice/length)\n",
" mix = (ai[1]*xslice/length) + (ai[2]*(length-xslice)/length)\n",
" \n",
" # Draw wedge\n",
" earth[:,xslice,:] *= mix \n",
"\n",
" earth[thickness:,xslice,:] = ai[0]\n",
"\n",
" # Put the top on\n",
" earth[:depth/3,:,:] = ai[3]\n",
" \n",
" return earth"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"earth = make_earth(depth, length, width, ai)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we have a 3D model. We'd like to look at it. Without getting into Mayavi, the easiest thing to do is to just look at some x, y, and z slices. Let's make a function to do this, since we'll want it again for the synthetic. "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"def plot_slices(data, interpolation='nearest', cmap='Greys', vmin=0., vmax=1.):\n",
" plt.figure(figsize=(16,12))\n",
" \n",
" for j in range(3):\n",
" plt.subplot(3,4,j+1)\n",
" plt.title('y = ' + str(int(j*(length/3))))\n",
" plt.imshow(data[:,:,int(j*(length/3))], interpolation=interpolation, cmap=cmap, vmax=vmax, vmin=vmin)\n",
" plt.subplot(3,4,4)\n",
" plt.title('y = ' + str(int(length-1)))\n",
" plt.imshow(data[:,:,-1], interpolation=interpolation, cmap=cmap, vmax=vmax, vmin=vmin)\n",
" \n",
" for j in range(3):\n",
" plt.subplot(3,4,5+j)\n",
" plt.title('x = ' + str(int(j*(width/3))))\n",
" plt.imshow(data[:,int(j*(width/3)),:], interpolation=interpolation, cmap=cmap, vmax=vmax, vmin=vmin)\n",
" plt.subplot(3,4,8)\n",
" plt.title('x = ' + str(int(width-1)))\n",
" plt.imshow(data[:,-1,:], interpolation=interpolation, cmap=cmap, vmax=vmax, vmin=vmin)\n",
" \n",
" for j in range(3):\n",
" plt.subplot(3,4,9+j)\n",
" plt.title('z = ' + str(1 + int(1 + depth/3 + j*depth/(3*3))))\n",
" plt.imshow(data[1 + int(depth/3 + j*depth/(3*3)),:,:], interpolation=interpolation, cmap=cmap, vmax=vmax, vmin=vmin)\n",
" plt.subplot(3,4,12)\n",
" plt.title('z = ' + str(int(2*depth/3 - 1)))\n",
" plt.imshow(data[int(2*depth/3 - 1),:,:], interpolation=interpolation, cmap=cmap, vmax=vmax, vmin=vmin)\n",
" \n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
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EFRUV2rhxo/bt29ftY6Kjo/WLX/xCe/fu1e7du/XLX/5S+/btU0FBgbKyslRZ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\nwN1oFE7x/CualmVp586dKi8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qo/SJSOFUo33pU6JRt2HR7KHjx4/r7rvvVklJiSoqKrRx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\nYII=\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_slices(earth, interpolation='nearest', cmap='jet')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Making a synthetic"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can compute reflection coefficients"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"def make_rc(earth):\n",
" upper = earth[:-1][:][:]\n",
" lower = earth[1:][:][:]\n",
" \n",
" return (lower - upper) / (lower + upper)\n",
"\n",
"rc = make_rc(earth)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And we need a wavelet:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"from scipy.signal import ricker"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"n_samples = depth\n",
"n_traces = length\n",
"n_xlines = width\n",
"\n",
"def make_synth(rc, f=20):\n",
" points = 128\n",
" synth = np.zeros((n_samples+points-2, n_traces, n_xlines))\n",
" wavelet = ricker(points, 1000/(4.*f))\n",
" wavelet = wavelet / max(wavelet)\n",
" for i in range(int(n_traces)):\n",
" for j in range(int(n_xlines)):\n",
" synth[:,i,j] = np.convolve(rc[:,i,j], wavelet)\n",
" synth = synth[np.ceil(len(wavelet))/2:-np.ceil(len(wavelet))/2,:,:]\n",
" return synth\n",
"\n",
"def forward_model(model=None, rocks=None, earth=None, freq=20):\n",
" \"\"\"\n",
" Meta function to do everything from scratch\n",
" \"\"\"\n",
" if model:\n",
" ai = make_ai(rocks)\n",
" earth = assign_rocks(model, ai) \n",
" rc = make_rc(earth)\n",
" return make_synth(rc,freq)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Generate the 3D synthetic seismic volume."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"synthmod = forward_model(earth=earth, freq=20)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And plot, using the same routine as before. "
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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SQ0ODmpqagnXuJsCmpib5vh8Eap+ZywTX2toavDk6/PlD9tICM+NjZpPSfdnL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\nQmCC\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"maxrc = np.amax(abs(synthmod))\n",
"plot_slices(synthmod, interpolation='bilinear', vmax=maxrc, vmin=-maxrc)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Making an RGB blend"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"from scipy.signal import hilbert"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"def make_triplet(model=None, ai=None, earth=None, freqs=(60,30,15)):\n",
" if model:\n",
" obj = model\n",
" else:\n",
" obj = earth\n",
" \n",
" triplet = np.empty((obj.shape[0]-2, obj.shape[1], obj.shape[2], 3))\n",
" \n",
" for f in freqs:\n",
" if model:\n",
" triplet[:,:,:,freqs.index(f)] = forward_model(model=model, ai=ai, freq=f)\n",
" else:\n",
" triplet[:,:,:,freqs.index(f)] = forward_model(earth=earth, freq=f)\n",
" \n",
" return triplet\n",
"\n",
"def scaled_rgb(triplet):\n",
" envelope = abs(hilbert(triplet))\n",
" for i in range(3):\n",
" envelope[:,:,:,i]= envelope[:,:,:,i]/np.amax(envelope[:,:,:,i])\n",
" return envelope"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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tSRDxeXln53IqgBPalbVyaoCjXRY6R2KayItzPdmaPPaeQMuiNrJWeS+loDte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19+v1/f+c534l1+yqLRTEPf/va3lZeXp6amJu3atUtbtmzRj370I0mfhO1b3/qWDh06pEOHDik7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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"rgb = scaled_rgb(make_triplet(earth=earth, freqs=(25,20,15)))\n",
"plot_slices(rgb, interpolation='bilinear')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Bugs, improvements"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"See comments on Spectral_wedge.ipynb."
]
}
],
"metadata": {
"anaconda-cloud": {},
"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": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 1
}