Constraining Stress Magnitudes from Wellbore Failure.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Constraining Stress Magnitudes from Wellbore Failure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Build a stress polygon diagram to constrain the possible stress magnitudes for data from a well. Image logs from which the fractures are picked show no signs of drilling induced tensile fractures or wellbore breakouts. Use these key observations of the lack of wellbore failure combined with the relations for borehole stresses and frictional faulting theory to construct a stress polygon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import libraries\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 1A: Given values, use the values below for your calculations of the components of the stress polygon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Key Input variables\n",
    "Sv = 1.12  # (psi/ft). This is the vertical stress\n",
    "Pp = 0.63  # (psi/ft). This is the pore pressure\n",
    "μ = 0.60   # Coefficient of sliding friction\n",
    "wBO = 0    # Width of Wellbore Breakout (expressed as an angle), setting this value to 0\n",
    "T0 = 0     # (psi/ft). Rock tensile strength. Rocks are very weak in tension.\n",
    "Ceff = 3.5 # (psi/ft). Effective rock compressive strength\n",
    "ΔP = 0.16  # (psi/ft). Additional pore pressure from drilling mud weight\n",
    "σΔT = 0    # No thermal stresses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fμ = 3.119428454762872\n",
      "Maximum Stress (S1) = 2.1585199428338075 psi/ft\n",
      "Minimum Stress (S3) = 0.7870800571661927 psi/ft\n"
     ]
    }
   ],
   "source": [
    "# Reformulating the Frictional Faulting Theory equation for S1 and S3:\n",
    "# S1 = fμ * (S3 - Pp) + Pp\n",
    "# S3 = ((S1 - Pp) / fμ) + Pp\n",
    "fμ = ((μ**2+1)**0.5+μ)**2    # Coefficient ratio of sliding friction\n",
    "print('fμ =', fμ)\n",
    "\n",
    "# Determine S1 - Maximum Stress\n",
    "S3a = Sv     # Set S3 to be Sv\n",
    "S1 = fμ * (S3a - Pp) + Pp\n",
    "print('Maximum Stress (S1) =',S1, 'psi/ft')\n",
    "\n",
    "# Determine S3 - Minimum Stress\n",
    "S1a = Sv     # Set S1 to be Sv\n",
    "S3 = ((S1a - Pp) / fμ) + Pp\n",
    "print('Minimum Stress (S3) =', S3, 'psi/ft')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 2: Calculate stress magnitude constraints for each faulting regime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use frictional faulting theory relationships to calculate the stress magnitude constraints for each faulting regime in units of psi/ft."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from skimage import io\n",
    "\n",
    "io.imshow(io.imread(\"https://sp.lyellcollection.org/content/specpubgsl/458/1/273/F4.large.jpg\"))\n",
    "io.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.7870800571661927, 0.7870800571661927] [0.7870800571661927, 1.12] [1.12, 1.12] [1.12, 2.1585199428338075] [2.1585199428338075, 2.1585199428338075]\n"
     ]
    }
   ],
   "source": [
    "# Need 5 sets of points zig zagging from bottom left to top right of the figuer above.\n",
    "Corner1 = [S3, S3]\n",
    "Corner2 = [S3, Sv]\n",
    "Corner3 = [Sv, Sv]\n",
    "Corner4 = [Sv, S1]\n",
    "Corner5 = [S1, S1]\n",
    "print(Corner1, Corner2, Corner3, Corner4, Corner5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sh_min (psi/ft)</th>\n",
       "      <th>Sh_max (psi/ft)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.78708</td>\n",
       "      <td>0.78708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.78708</td>\n",
       "      <td>1.12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.12000</td>\n",
       "      <td>1.12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.12000</td>\n",
       "      <td>2.15852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.15852</td>\n",
       "      <td>2.15852</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sh_min (psi/ft)  Sh_max (psi/ft)\n",
       "0          0.78708          0.78708\n",
       "1          0.78708          1.12000\n",
       "2          1.12000          1.12000\n",
       "3          1.12000          2.15852\n",
       "4          2.15852          2.15852"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Based on the diagram above, here are the Shmin and Shmax lists\n",
    "Sh_min = [S3, S3, Sv, Sv, S1]\n",
    "Sh_max = [S3, Sv, Sv, S1, S1]\n",
    "\n",
    "# Create a zipped list of tuples from above lists\n",
    "x = zip(Sh_min, Sh_max)\n",
    "\n",
    "# Creating a dataframe object from a ziped list\n",
    "df = pd.DataFrame(x, columns = ['Sh_min (psi/ft)', 'Sh_max (psi/ft)'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 3: Calculate stress magnitude constraints from wellbore failure observations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use relationships for wellbore stress magnitudes to calculate the stress magnitude constraints in units of psi/ft."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sh_min (psi/ft)</th>\n",
       "      <th>Sh_max (psi/ft)</th>\n",
       "      <th>Sh_max_bo (psi/ft)</th>\n",
       "      <th>Sh_max_tf (psi/ft)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.78708</td>\n",
       "      <td>0.78708</td>\n",
       "      <td>1.902360</td>\n",
       "      <td>0.94124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.78708</td>\n",
       "      <td>1.12000</td>\n",
       "      <td>1.902360</td>\n",
       "      <td>0.94124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.12000</td>\n",
       "      <td>1.12000</td>\n",
       "      <td>2.013333</td>\n",
       "      <td>1.94000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.12000</td>\n",
       "      <td>2.15852</td>\n",
       "      <td>2.013333</td>\n",
       "      <td>1.94000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.15852</td>\n",
       "      <td>2.15852</td>\n",
       "      <td>2.359507</td>\n",
       "      <td>5.05556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sh_min (psi/ft)  Sh_max (psi/ft)  Sh_max_bo (psi/ft)  Sh_max_tf (psi/ft)\n",
       "0          0.78708          0.78708            1.902360             0.94124\n",
       "1          0.78708          1.12000            1.902360             0.94124\n",
       "2          1.12000          1.12000            2.013333             1.94000\n",
       "3          1.12000          2.15852            2.013333             1.94000\n",
       "4          2.15852          2.15852            2.359507             5.05556"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Wellbore Breakouts inputs\n",
    "thetaB = 180-wBO\n",
    "cos_thetaB = np.cos(np.deg2rad(thetaB))\n",
    "\n",
    "# Create new columns to calculate the Wellbore breakout and tensile fracture stresses in psi/ft\n",
    "df['Sh_max_bo (psi/ft)']= ((Ceff+2*Pp+ΔP+σΔT)-(df['Sh_min (psi/ft)']*(1+2*cos_thetaB)))/(1-2*cos_thetaB) # break-out stress\n",
    "df['Sh_max_tf (psi/ft)']= Shmax_tf = 3*df['Sh_min (psi/ft)'] - 2*Pp - ΔP - T0 - σΔT               # tensile fracture stress\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sh_min (psi/ft)</th>\n",
       "      <th>Sh_max (psi/ft)</th>\n",
       "      <th>Sh_max_bo (psi/ft)</th>\n",
       "      <th>Sh_max_tf (psi/ft)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.78708</td>\n",
       "      <td>0.78708</td>\n",
       "      <td>1.902360</td>\n",
       "      <td>0.94124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.15852</td>\n",
       "      <td>2.15852</td>\n",
       "      <td>2.359507</td>\n",
       "      <td>5.05556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sh_min (psi/ft)  Sh_max (psi/ft)  Sh_max_bo (psi/ft)  Sh_max_tf (psi/ft)\n",
       "0          0.78708          0.78708            1.902360             0.94124\n",
       "4          2.15852          2.15852            2.359507             5.05556"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop certain rows to retain corner points 1 and 5 - so that, a line can be drawn connecting these 2 points\n",
    "df1 = df.drop(df.index[[1,2,3]])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,9))\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax1.set_title('Stress Polygon', fontsize = '16')\n",
    "plt.xlabel('Sh_min (psi/ft)', fontsize = '14')\n",
    "plt.ylabel('Sh_max (psi/ft)', fontsize = '14')\n",
    "ax1.set_xlim(df['Sh_min (psi/ft)'].min()-0.1, df['Sh_min (psi/ft)'].max()+0.1)\n",
    "ax1.set_ylim(df['Sh_max (psi/ft)'].min()-0.1, df['Sh_max (psi/ft)'].max()+0.1)\n",
    "plt.tight_layout()\n",
    "plt.grid()\n",
    "#plt.scatter(df['Sh_min (psi/ft)'], df['Sh_max (psi/ft)'])\n",
    "plt.plot(df['Sh_min (psi/ft)'], df['Sh_max (psi/ft)'], '-o', c='b')\n",
    "plt.plot(df['Sh_min (psi/ft)'], df['Sh_max_bo (psi/ft)'], '-o', c='r', linewidth=4)\n",
    "plt.plot(df['Sh_min (psi/ft)'], df['Sh_max_tf (psi/ft)'], '-o', c='g',linewidth=4)\n",
    "plt.plot(df['Sh_min (psi/ft)'], df['Sh_max (psi/ft)'], '-o', c='b')\n",
    "plt.plot(df1['Sh_min (psi/ft)'], df1['Sh_max (psi/ft)'], '-o', c='b')\n",
    "plt.plot(Corner2, Corner4, 'b')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Break-out and tensile fracture stresses indicate a reverse faulting regime."
   ]
  }
 ],
 "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": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}