volcanic_notebook.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Rock Physics inversion for water/CO2 saturation from Volcanic attenuation tomography data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import volcaniQ as vq\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "volcanic_data = vq.CleanReadCSV()\n",
    "fluids = vq.FluidsReadCSV()\n",
    "calibration = vq.RockPhysicsModelCalibrator()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fluids"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First I have loaded some fluid data. I have taken the properties of CO<sub>2</sub> and water from the MNIST database based on their EOSs, the corresponding CSV file attached is created in Mathematica which relies on MNIST for thermodynamic data. The code in `FluidReadCSV` essentially loads these up i.e. reading the CSV from\n",
    "\n",
    "         fluids = FluidReadCSV()\n",
    "\n",
    "can then return dataframes for depth dependence of each fluid `fluids('Water')` or `fluids('CarbonDioxide')`.\n",
    "\n",
    "***please check these plotted below are reasonable!!***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "fig, axs = plt.subplots(1, 3,constrained_layout = True)\n",
    "\n",
    "fluid_names = {'Water':  '#0055FF', 'CarbonDioxide':'#FF5500'}\n",
    "labels = {'Modulus(GPa)':'modulus', 'Density(g/cm3)':'density', 'Viscosity(Pa.ms)': 'viscosity'}\n",
    "\n",
    "for lab, prop in enumerate(labels):\n",
    "    for fluid in fluid_names:\n",
    "        axs[lab].scatter(getattr(fluids(fluid),labels[prop]), -fluids(fluid).depth, c=fluid_names[fluid], s=20, edgecolors='black', label=fluid)\n",
    "        axs[lab].set_xlabel(prop)\n",
    "\n",
    "axs[0].legend()\n",
    "axs[0].set_ylabel('Depth(Km)')\n",
    "\n",
    "axs[1].tick_params(axis='y', which='both', left=False, right=False, labelleft=False)\n",
    "\n",
    "axs[2].set_xscale('log')\n",
    "axs[2].tick_params(axis='y', which='both', left=False, right=False, labelleft=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These will need to be combined into an effective fluid for partial saturation. This is done via `EffectiveFluid` class as per below. The two things that affect the squirt flow model, is the effective fluid modulus and the log frequency, both plotted below. The parameter `q` controls how unifrom the saturation is."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fl1 = vq.Fluid(density=1., viscosity=.5, modulus=2.5)\n",
    "fl2 = vq.Fluid(density=.5, viscosity=.002, modulus=.15)\n",
    "flmx = vq.EffectiveFluid(fl1, fl2)\n",
    "sat = np.arange(0,1.01,.01)\n",
    "def mod(q): return np.array([flmx(saturation=s, patch_parameter=q).modulus for s in sat])\n",
    "def log_omega(q): return np.log10(np.array([flmx(saturation=s, patch_parameter=q).omega_c for s in sat]))\n",
    "fig, ax = plt.subplots(2, 1,constrained_layout = True)\n",
    "ax[0].plot(sat, mod(1), label='q=1, uniform saturation')\n",
    "ax[0].plot(sat, mod(.1), label= 'q=.5, patchy saturation')\n",
    "ax[0].legend()\n",
    "ax[0].set_ylabel('Eff. Modulus(GPa)')\n",
    "ax[1].plot(sat, log_omega(1), label='q=1, uniform saturation')\n",
    "ax[1].plot(sat, log_omega(.1), label= 'q=.5, patchy saturation')\n",
    "ax[1].set_ylabel('Eff. log omega')\n",
    "ax[1].set_xlabel('fluid 1 saturation')\n",
    "# ax[0].spines.bottom.set_visible(False)\n",
    "ax[1].spines.top.set_visible(False)\n",
    "ax[0].xaxis.tick_top()\n",
    "\n",
    "ax[1].tick_params(labeltop=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model calibration"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now I need to calibrate the model, based on a fluid endpoint and the input parameters that we have. I have written a calibration class for this which is called in `RockPhysicsModelCalibrator()`. The way this works is more or less straightforward, call\n",
    "\n",
    "        calibration = RockPhysicsModelCalibrator()\n",
    "        model = calibration(Vp = vp, Vs = vs, Rho = rho, Qp=qp, phi=.15, Kf=kw)\n",
    "\n",
    "and you get a rock physics model that will have the Qp, Vp, Vs values at a reference frequency, which I have taken to be the squirt flow frequency of water saturated rock. The assumption is that the matrix is quartz \n",
    "\n",
    "***does quarz make sense?***\n",
    "\n",
    "With these assumptions, you can calibrate the model and check it returns the right values when `omegac` (the log squirt flow frequency of the model relative to water) is zero. Code below does that for some generic parameters and playing with them seems to work."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'calculated': {'p-modulus': (67.55+1.5j),\n",
       "  's-modulus': (14.32+0.04j),\n",
       "  'qp': 45.03333333333333},\n",
       " 'observed': {'p-modulus': 67.5, 's-modulus': 14.283, 'qp': 45}}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ref_vp, ref_vs, ref_rho, ref_qp = 5., 2.3, 2.7, 45\n",
    "model = calibration(Vp = ref_vp, Vs = ref_vs, Rho = ref_rho, Qp=ref_qp, phi=.34, Kf=2.25)\n",
    "cij_at_calibration = np.round(model(omegac=0., fluid_modulus=2.25).squirt_flow_model(0),2)\n",
    "q = (lambda x: np.real(x)/np.imag(x))\n",
    "tuple(model(omegac=0., fluid_modulus=2.25).squirt_flow_model(0)[[0,5],[0,5]]), (lambda x: np.real(x)/np.imag(x))(model(omegac=0, fluid_modulus=2.25).squirt_flow_model(0)[0,0])\n",
    "{'calculated': {\"p-modulus\":cij_at_calibration[0,0], \"s-modulus\":cij_at_calibration[5,5], \"qp\":q(cij_at_calibration[0,0])}, 'observed':{\"p-modulus\":ref_vp**2*ref_rho, \"s-modulus\":ref_vs**2*ref_rho, \"qp\":ref_qp}}"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The data"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a couple of crucial questions regarding the data.\n",
    " - is the calibration point rightly chosen where the white rectangle is? It seems to be relatively consistent down to about 5 km BSL, relative coordinates `x=17, y=-11`\n",
    " - are Qp and Qs derived at the same frequency? I have assumed so, but it is not clear and also the Qp/Qs that the model predicts at the same frequency is realatively constant but can vary wildly if the frequency of measurement of Qp and that of Qs vary by up to an order of magnitude. If that is so, there is some really exciting modelling to be done for the inversion. Actually, only need to know if the central frequency at which  the Qp and Qs were calculated might be different, if so, the difference can feed into a grid search."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "x=%{x}<br>y=%{y}<br>Qp=%{marker.color}<extra></extra>",
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   ],
   "source": [
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "xmin, xmax = 15, 18\n",
    "ymin, ymax = -10, -12\n",
    "fig = px.scatter(volcanic_data.data[volcanic_data.data['z'] ==-5], x='x', y='y',\n",
    "              color='Qp')\n",
    "fig.add_shape(type=\"rect\",\n",
    "    x0=xmin, y0=ymin, x1=xmax, y1=ymax,\n",
    "    line=dict(color=\"White\"),\n",
    "    fillcolor=\"White\",\n",
    "    opacity=0.7,\n",
    ")\n",
    "fig.add_annotation(\n",
    "            x=16., y=-9,\n",
    "            text=f\"Calibration(100% water)\",\n",
    "            showarrow=True,\n",
    "            font=dict(\n",
    "                family=\"sans-serif\",\n",
    "                size=12,\n",
    "                color=\"#ffffff\"\n",
    "            ),\n",
    "            arrowcolor=\"#ffffff\",\n",
    "            arrowhead=1)\n",
    "fig.update_yaxes(\n",
    "      scaleanchor=\"x\",\n",
    "      scaleratio=1,\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The model calibrated on the data"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Noting all the above, I have calibrated the model on the basis that the white calibration square is water only and assume the rock physics model is to change every km of earth (since that's the resoultion of the data). I have taken into account the change of fluid properties as depth increases so the saturation should give a calibrated model at every depth. At the rock physics level, calibration is done for the values of K, mu and Qp that are in the data on the white square. I have assumed quartz all the way and constant porosity of 15%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calibration_model_by_depth(depth:int, xmin:int=15, xmax:int=18, ymin:int=-12, ymax:int=-10):\n",
    "    # data = volcanic_data.data\\\n",
    "    # [\n",
    "    # volcanic_data.data[\"z\"].between(depth,depth)\n",
    "    # ]\n",
    "    result = volcanic_data.data\\\n",
    "    [\n",
    "    volcanic_data.data[\"z\"].between(depth,depth) &\\\n",
    "    volcanic_data.data[\"x\"].between(xmin, xmax) &\\\n",
    "    volcanic_data.data[\"y\"].between(ymin, ymax)\n",
    "    ]\\\n",
    "    .groupby('z')\\\n",
    "    .mean()\n",
    "    k, rho, mu, qp = tuple(result[['K','ρ', 'μ','Qp']].values[0])\n",
    "    kw, rhow, etaw = tuple(fluids('Water').temp_df[fluids('Water').temp_df['Depth(Km)']==depth][['Modulus(GPa)', 'Density(g/cm3)', 'Viscosity(Pa.ms)']].values[0])\n",
    "    kco2, rhoco2, etaco2 = tuple(fluids('CarbonDioxide').temp_df[fluids('CarbonDioxide').temp_df['Depth(Km)']==depth][['Modulus(GPa)', 'Density(g/cm3)', 'Viscosity(Pa.ms)']].values[0])\n",
    "    water = vq.Fluid(density=rhow, viscosity=etaw, modulus=kw)\n",
    "    co2 = vq.Fluid(density=rhoco2, viscosity=etaco2, modulus=kco2)\n",
    "    watCo2mix = vq.EffectiveFluid(water, co2)\n",
    "    watCo2mix.brooks_corey_lambda = 1.\n",
    "    vp = np.sqrt((k + 4/3*mu)/rho)\n",
    "    vs = np.sqrt(mu/rho)\n",
    "    model = calibration(Vp = vp, Vs = vs, Rho = rho, Qp=qp, phi=.15, Kf=kw)\n",
    "    def saturation_dependent_model(sw, q):\n",
    "        mix = watCo2mix(saturation=sw, patch_parameter=q, reference_frequency=1)\n",
    "        omega_c,fluid_modulus = np.log10(mix.omega_c), mix.modulus\n",
    "        return model(omegac=omega_c, fluid_modulus=fluid_modulus)\n",
    "    return saturation_dependent_model"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I am faced with the problem of whether the (central) frequency content that was used to calculate Q is the same for the p and the s waves. If so, then the Qp/Qs ratio is more or less the same along saturations, but if they are different (which I think in earthquakes, they are) then I'd need to know by how much before I can invert the data for saturation. At this stage suffices to know if *assuming* they are different is reasonable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17f1ecfa0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model3 = calibration_model_by_depth(depth = -5)\n",
    "s = np.arange(0,1.01,0.01)\n",
    "def forward_data(freq): return np.array([model3(s1, 1).squirt_flow_model(freq) for s1 in s])\n",
    "q = (lambda x: np.real(x)/np.imag(x))\n",
    "\n",
    "y = q(forward_data(0)[:,0,0])\n",
    "y1 = q(forward_data(1)[:,5,5])\n",
    "y2 = q(forward_data(0)[:,5,5])\n",
    "y3 = q(forward_data(-1)[:,5,5])\n",
    "fig, ax = plt.subplots()\n",
    "ax.set_xlim(0,1)\n",
    "ax.set_ylim(100, 10000)\n",
    "ax.set_yscale('log')\n",
    "ax.plot(s, y, label='P-wave Q')\n",
    "ax.plot(s, y2, label='S-wave Q @ same frequency')\n",
    "ax.plot(s, y1, label='S-wave Q @ frequency/10')\n",
    "ax.plot(s, y3, label='S-wave Q @ 10 x frequency')\n",
    "ax.set_ylabel('Q')\n",
    "ax.set_xlabel('fluid 1 saturation')\n",
    "\n",
    "ax.legend()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='z'>"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "volcanic_data.data\\\n",
    "    [\n",
    "    volcanic_data.data[\"z\"].between(-6,6) &\\\n",
    "    volcanic_data.data[\"x\"].between(xmin, xmax) &\\\n",
    "    volcanic_data.data[\"y\"].between(ymin, ymax)\n",
    "    ]\\\n",
    "    .groupby('z')\\\n",
    "    .mean()\\\n",
    "    .plot(y='Qp', style='o')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "volcaniQ",
   "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": "3.9.13"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "899cda1e268102809178cbbc586bb41cca1b53730d360f88b61c797f3824fc07"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}