unconve/homework 5/homework5_unconve_geomech.ipynb

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      "name": "homework5-unconve-geomech.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "authorship_tag": "ABX9TyPLX4E0BK6V5bR7MVF+D5/S",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/yohanesnuwara/reservoir-geomechanics/blob/master/unconve/homework%205/homework5_unconve_geomech.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wJFXMac4uzVC",
        "colab_type": "text"
      },
      "source": [
        "# **Homework 5. Reservoir Seismology**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VebMlZefutWb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1pTn_3oLwMj_",
        "colab_type": "code",
        "outputId": "eaa29394-8d50-49f2-a83e-b0a51a24f8a7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 776
        }
      },
      "source": [
        "# get wellA, wellB, wellC, wellD data from course webpage\n",
        "\n",
        "!wget https://courses.edx.org/assets/courseware/v1/717146fd2ab45b7b2fe333806785188b/asset-v1:StanfordOnline+GEOPHYSX0004+1T2020+type@asset+block/GP208_HW5_Well_A.txt\n",
        "!wget https://courses.edx.org/assets/courseware/v1/c61f00c835a6403f99d39b0420542599/asset-v1:StanfordOnline+GEOPHYSX0004+1T2020+type@asset+block/GP208_HW5_Well_B.txt\n",
        "!wget https://courses.edx.org/assets/courseware/v1/7bd7ff0ac6115b772d4d7dd548b6a585/asset-v1:StanfordOnline+GEOPHYSX0004+1T2020+type@asset+block/GP208_HW5_Well_C.txt\n",
        "!wget https://courses.edx.org/assets/courseware/v1/8a862ab410b9f3bbc4b55cbde6989240/asset-v1:StanfordOnline+GEOPHYSX0004+1T2020+type@asset+block/GP208_HW5_Well_D.txt"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-05-21 05:44:06--  https://courses.edx.org/assets/courseware/v1/717146fd2ab45b7b2fe333806785188b/asset-v1:StanfordOnline+GEOPHYSX0004+1T2020+type@asset+block/GP208_HW5_Well_A.txt\n",
            "Resolving courses.edx.org (courses.edx.org)... 107.23.242.160, 54.209.244.105, 54.85.51.136\n",
            "Connecting to courses.edx.org (courses.edx.org)|107.23.242.160|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 221105 (216K) [text/plain]\n",
            "Saving to: ‘GP208_HW5_Well_A.txt’\n",
            "\n",
            "\rGP208_HW5_Well_A.tx   0%[                    ]       0  --.-KB/s               \rGP208_HW5_Well_A.tx 100%[===================>] 215.92K  --.-KB/s    in 0.04s   \n",
            "\n",
            "2020-05-21 05:44:07 (5.36 MB/s) - ‘GP208_HW5_Well_A.txt’ saved [221105/221105]\n",
            "\n",
            "--2020-05-21 05:44:10--  https://courses.edx.org/assets/courseware/v1/c61f00c835a6403f99d39b0420542599/asset-v1:StanfordOnline+GEOPHYSX0004+1T2020+type@asset+block/GP208_HW5_Well_B.txt\n",
            "Resolving courses.edx.org (courses.edx.org)... 107.23.242.160, 54.209.244.105, 54.85.51.136\n",
            "Connecting to courses.edx.org (courses.edx.org)|107.23.242.160|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 268285 (262K) [text/plain]\n",
            "Saving to: ‘GP208_HW5_Well_B.txt’\n",
            "\n",
            "GP208_HW5_Well_B.tx 100%[===================>] 262.00K  --.-KB/s    in 0.04s   \n",
            "\n",
            "2020-05-21 05:44:10 (6.34 MB/s) - ‘GP208_HW5_Well_B.txt’ saved [268285/268285]\n",
            "\n",
            "--2020-05-21 05:44:15--  https://courses.edx.org/assets/courseware/v1/7bd7ff0ac6115b772d4d7dd548b6a585/asset-v1:StanfordOnline+GEOPHYSX0004+1T2020+type@asset+block/GP208_HW5_Well_C.txt\n",
            "Resolving courses.edx.org (courses.edx.org)... 107.23.242.160, 54.209.244.105, 54.85.51.136\n",
            "Connecting to courses.edx.org (courses.edx.org)|107.23.242.160|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 326895 (319K) [text/plain]\n",
            "Saving to: ‘GP208_HW5_Well_C.txt’\n",
            "\n",
            "GP208_HW5_Well_C.tx 100%[===================>] 319.23K  --.-KB/s    in 0.05s   \n",
            "\n",
            "2020-05-21 05:44:15 (5.91 MB/s) - ‘GP208_HW5_Well_C.txt’ saved [326895/326895]\n",
            "\n",
            "--2020-05-21 05:44:19--  https://courses.edx.org/assets/courseware/v1/8a862ab410b9f3bbc4b55cbde6989240/asset-v1:StanfordOnline+GEOPHYSX0004+1T2020+type@asset+block/GP208_HW5_Well_D.txt\n",
            "Resolving courses.edx.org (courses.edx.org)... 107.23.242.160, 54.209.244.105, 54.85.51.136\n",
            "Connecting to courses.edx.org (courses.edx.org)|107.23.242.160|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 178515 (174K) [text/plain]\n",
            "Saving to: ‘GP208_HW5_Well_D.txt’\n",
            "\n",
            "GP208_HW5_Well_D.tx 100%[===================>] 174.33K  --.-KB/s    in 0.04s   \n",
            "\n",
            "2020-05-21 05:44:19 (4.24 MB/s) - ‘GP208_HW5_Well_D.txt’ saved [178515/178515]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "um7780ypEIUp",
        "colab_type": "code",
        "outputId": "33ba6897-4a96-47d3-d7aa-f46eb24d3a50",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        }
      },
      "source": [
        "colnames = [\"EventNumber\",\"AcqDateLocal\",\"AcqTimeLocal\",\"OriginDateLocal\",\"OriginTimeLocal\",\"OriginTimePartS\",\"TZ\",\"Easting\",\"Northing\",\"Depth\",\"Magnitude\",\"Confidence\",\"EventFile\"]\n",
        "\n",
        "well_a = pd.read_csv(\"/content/GP208_HW5_Well_A.txt\", skiprows=1, delimiter=\"\\t\", names=colnames)\n",
        "well_b = pd.read_csv(\"/content/GP208_HW5_Well_B.txt\", skiprows=1, delimiter=\"\\t\", names=colnames)\n",
        "well_c = pd.read_csv(\"/content/GP208_HW5_Well_C.txt\", skiprows=1, delimiter=\"\\t\", names=colnames)\n",
        "well_d = pd.read_csv(\"/content/GP208_HW5_Well_D.txt\", skiprows=1, delimiter=\"\\t\", names=colnames)\n",
        "\n",
        "well_a.head(10)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>EventNumber</th>\n",
              "      <th>AcqDateLocal</th>\n",
              "      <th>AcqTimeLocal</th>\n",
              "      <th>OriginDateLocal</th>\n",
              "      <th>OriginTimeLocal</th>\n",
              "      <th>OriginTimePartS</th>\n",
              "      <th>TZ</th>\n",
              "      <th>Easting</th>\n",
              "      <th>Northing</th>\n",
              "      <th>Depth</th>\n",
              "      <th>Magnitude</th>\n",
              "      <th>Confidence</th>\n",
              "      <th>EventFile</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2395</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.459873</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.459873</td>\n",
              "      <td>0.928</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-528.80</td>\n",
              "      <td>4508.42</td>\n",
              "      <td>5612.38</td>\n",
              "      <td>-2.81</td>\n",
              "      <td>2.38</td>\n",
              "      <td>20140831t160213_794000z</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2396</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.459942</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.459942</td>\n",
              "      <td>0.462</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-546.84</td>\n",
              "      <td>4478.53</td>\n",
              "      <td>5585.97</td>\n",
              "      <td>-2.79</td>\n",
              "      <td>1.52</td>\n",
              "      <td>20140831t160219_328250z</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2397</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.460301</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.460301</td>\n",
              "      <td>0.488</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-369.76</td>\n",
              "      <td>4448.37</td>\n",
              "      <td>5724.29</td>\n",
              "      <td>-2.96</td>\n",
              "      <td>2.76</td>\n",
              "      <td>20140831t160250_342250z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2398</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.464190</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.464190</td>\n",
              "      <td>0.768</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-450.02</td>\n",
              "      <td>4449.97</td>\n",
              "      <td>5745.04</td>\n",
              "      <td>-2.72</td>\n",
              "      <td>2.15</td>\n",
              "      <td>20140831t160826_614250z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2399</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.465231</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.465231</td>\n",
              "      <td>0.672</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-465.37</td>\n",
              "      <td>4450.05</td>\n",
              "      <td>5702.69</td>\n",
              "      <td>-2.77</td>\n",
              "      <td>2.69</td>\n",
              "      <td>20140831t160956_509250z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2400</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.466516</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.466516</td>\n",
              "      <td>0.636</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-575.91</td>\n",
              "      <td>4508.30</td>\n",
              "      <td>5510.99</td>\n",
              "      <td>-2.59</td>\n",
              "      <td>3.22</td>\n",
              "      <td>20140831t161147_517500z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2401</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.469086</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.469086</td>\n",
              "      <td>0.188</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-473.13</td>\n",
              "      <td>4396.04</td>\n",
              "      <td>5735.92</td>\n",
              "      <td>-2.70</td>\n",
              "      <td>1.98</td>\n",
              "      <td>20140831t161529_047000z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2402</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.470208</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.470208</td>\n",
              "      <td>0.922</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-356.29</td>\n",
              "      <td>4461.45</td>\n",
              "      <td>5763.09</td>\n",
              "      <td>-2.76</td>\n",
              "      <td>1.89</td>\n",
              "      <td>20140831t161706_764250z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2403</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.471887</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.471887</td>\n",
              "      <td>0.259</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-238.75</td>\n",
              "      <td>4478.45</td>\n",
              "      <td>5728.36</td>\n",
              "      <td>-2.75</td>\n",
              "      <td>2.12</td>\n",
              "      <td>20140831t161931_098250z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2404</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.472581</td>\n",
              "      <td>40420</td>\n",
              "      <td>0.472581</td>\n",
              "      <td>0.766</td>\n",
              "      <td>-05:00</td>\n",
              "      <td>-456.88</td>\n",
              "      <td>4448.34</td>\n",
              "      <td>5723.89</td>\n",
              "      <td>-2.68</td>\n",
              "      <td>1.47</td>\n",
              "      <td>20140831t162031_404500z</td>\n",
              "    </tr>\n",
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            ],
            "text/plain": [
              "   EventNumber  AcqDateLocal  ...  Confidence                EventFile\n",
              "0         2395         40420  ...        2.38  20140831t160213_794000z\n",
              "1         2396         40420  ...        1.52  20140831t160219_328250z\n",
              "2         2397         40420  ...        2.76  20140831t160250_342250z\n",
              "3         2398         40420  ...        2.15  20140831t160826_614250z\n",
              "4         2399         40420  ...        2.69  20140831t160956_509250z\n",
              "5         2400         40420  ...        3.22  20140831t161147_517500z\n",
              "6         2401         40420  ...        1.98  20140831t161529_047000z\n",
              "7         2402         40420  ...        1.89  20140831t161706_764250z\n",
              "8         2403         40420  ...        2.12  20140831t161931_098250z\n",
              "9         2404         40420  ...        1.47  20140831t162031_404500z\n",
              "\n",
              "[10 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OUvcVn6zwyn3",
        "colab_type": "code",
        "outputId": "a5ac6e74-b417-48ad-943e-8dcf6dc1c5c2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        }
      },
      "source": [
        "from mpl_toolkits.mplot3d import Axes3D\n",
        "\n",
        "mag = well_d['Magnitude'].values\n",
        "x = well_d['Easting'].values\n",
        "y = well_d['Northing'].values\n",
        "z = -well_d['Depth'].values\n",
        "\n",
        "fig = plt.figure(figsize=(15,10))\n",
        "ax = fig.add_subplot(111, projection='3d')\n",
        "p = ax.scatter(x, y, z, c=mag, cmap='bwr', vmin=min(mag)+1, vmax=max(mag)-1)\n",
        "\n",
        "fig.colorbar(p)\n",
        "ax.set_xlabel('Easting')\n",
        "ax.set_ylabel('Northing')\n",
        "ax.set_zlabel('Depth')\n",
        "ax.set_title('Well D', size=20, pad=20)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0.92, 'Well D')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uHBAP22hZ0qz",
        "colab_type": "text"
      },
      "source": [
        "## Part 1. Gutenberg-Richter Analysis"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DhMUpIHjGOw1",
        "colab_type": "code",
        "outputId": "15fd8952-746b-430f-d19f-3181ec934f43",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 626
        }
      },
      "source": [
        "# plotting histogram of magnitudes of each well\n",
        "\n",
        "plt.figure(figsize=(18,10))\n",
        "\n",
        "plt.subplot(2,2,1)\n",
        "plt.hist(well_a['Magnitude'], bins=50, color='blue', alpha=0.5)\n",
        "plt.title('Histogram of Magnitude of Well A')\n",
        "plt.xlabel('Magnitudes'); plt.ylabel('Occurences')\n",
        "\n",
        "plt.subplot(2,2,2)\n",
        "plt.hist(well_b['Magnitude'], bins=50, color='red', alpha=0.5)\n",
        "plt.title('Histogram of Magnitude of Well B')\n",
        "plt.xlabel('Magnitudes'); plt.ylabel('Occurences')\n",
        "\n",
        "plt.subplot(2,2,3)\n",
        "plt.hist(well_c['Magnitude'], bins=50, color='green', alpha=0.5)\n",
        "plt.title('Histogram of Magnitude of Well C')\n",
        "plt.xlabel('Magnitudes'); plt.ylabel('Occurences')\n",
        "\n",
        "plt.subplot(2,2,4)\n",
        "plt.hist(well_d['Magnitude'], bins=50, color='purple', alpha=0.5)\n",
        "plt.title('Histogram of Magnitude of Well D')\n",
        "plt.xlabel('Magnitudes'); plt.ylabel('Occurences')\n",
        "\n",
        "plt.tight_layout(pad=2)\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x720 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_kpK_HnChxwf",
        "colab_type": "text"
      },
      "source": [
        "### A. Plot Gutenberg-Richter $log(N \\geq M)$ vs. $M$ "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3PKJFJN2LeU0",
        "colab_type": "code",
        "outputId": "95711d9b-e140-4270-a382-a674f0944565",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "source": [
        "mag_all = np.concatenate([np.array(well_a['Magnitude']), np.array(well_b['Magnitude']), \n",
        "                          np.array(well_c['Magnitude']), np.array(well_d['Magnitude'])])\n",
        "\n",
        "min_mag_all = min(mag_all); max_mag_all = max(mag_all)\n",
        "print('Minimum magnitude (M) of all the recorded earthquakes of all wells:', min_mag_all, 'and maximum M:', max_mag_all)\n",
        "\n",
        "\" compute cumulative events more than -3.8 for per bins \"\n",
        "\n",
        "num_bins = 100 # number of bins\n",
        "bins = np.linspace(min_mag_all, max_mag_all, num_bins) # magnitude bins\n",
        "\n",
        "# this will compute number of events between two bins e.g. N events between M=1 and M=2 (1<N<2)\n",
        "well_a_hist = np.histogram(well_a['Magnitude'], bins)\n",
        "well_b_hist = np.histogram(well_b['Magnitude'], bins)\n",
        "well_c_hist = np.histogram(well_c['Magnitude'], bins)\n",
        "well_d_hist = np.histogram(well_d['Magnitude'], bins)\n",
        "\n",
        "# this will revert the number of events between two bins\n",
        "well_a_hist_r = well_a_hist[0][::-1]\n",
        "well_b_hist_r = well_b_hist[0][::-1]\n",
        "well_c_hist_r = well_c_hist[0][::-1]\n",
        "well_d_hist_r = well_d_hist[0][::-1]\n",
        "\n",
        "# cumulative sum of the reverted number of events between two bins\n",
        "# to compute number of events above certain mag (N>=M), started from the largest magnitude\n",
        "cumsum_well_a = np.cumsum(well_a_hist_r)\n",
        "cumsum_well_b = np.cumsum(well_b_hist_r)\n",
        "cumsum_well_c = np.cumsum(well_c_hist_r)\n",
        "cumsum_well_d = np.cumsum(well_d_hist_r)\n",
        "\n",
        "print('Number of events above max magnitude', max_mag_all, 'is', 0, 'in well A, ', 0, 'in well B, ', 0, 'in well C, and', 0, 'in well D.')\n",
        "print('Number of events above the second max magnitude bin', np.round(bins[-2], 2), 'is', cumsum_well_a[0], 'in well A, ', cumsum_well_b[0], 'in well B, ', cumsum_well_c[0], 'in well C, and', cumsum_well_d[0], 'in well D.')\n",
        "print('Number of events above min magnitude', min_mag_all, 'is', cumsum_well_a[-1], 'in well A, ', cumsum_well_b[-1], 'in well B, ', cumsum_well_c[-1], 'in well C, and', cumsum_well_d[-1], 'in well D.')\n",
        "\n",
        "# finally append zero (0) to the first element of cumulative sum array\n",
        "cumsum_well_a = np.append(0, cumsum_well_a)\n",
        "cumsum_well_b = np.append(0, cumsum_well_b)\n",
        "cumsum_well_c = np.append(0, cumsum_well_c)\n",
        "cumsum_well_d = np.append(0, cumsum_well_d)\n",
        "\n",
        "# our bins are ordered from smallest to largest, but our cumulative events are ordered from largest to smallest\n",
        "# so revert again our cumulative events \n",
        "# cumsum_well_a = cumsum_well_a[::-1]\n",
        "# cumsum_well_b = cumsum_well_b[::-1]\n",
        "# cumsum_well_c = cumsum_well_c[::-1]\n",
        "# cumsum_well_d = cumsum_well_d[::-1]"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Minimum magnitude (M) of all the recorded earthquakes of all wells: -3.8 and maximum M: -0.76\n",
            "Number of events above max magnitude -0.76 is 0 in well A,  0 in well B,  0 in well C, and 0 in well D.\n",
            "Number of events above the second max magnitude bin -0.79 is 0 in well A,  1 in well B,  0 in well C, and 0 in well D.\n",
            "Number of events above min magnitude -3.8 is 1967 in well A,  2394 in well B,  2920 in well C, and 1584 in well D.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1yaIGZZobnkl",
        "colab_type": "code",
        "outputId": "cc559888-6c78-4da4-b304-eeeb174d09fc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 755
        }
      },
      "source": [
        "# plot the log(cumulative events) or log(N>M) vs magnitude\n",
        "\n",
        "# log the cumulative events\n",
        "log_cumsum_well_a = np.log10(cumsum_well_a[::-1])\n",
        "log_cumsum_well_b = np.log10(cumsum_well_b[::-1])\n",
        "log_cumsum_well_c = np.log10(cumsum_well_c[::-1])\n",
        "log_cumsum_well_d = np.log10(cumsum_well_d[::-1])\n",
        "\n",
        "plt.figure(figsize=(10,10))\n",
        "plt.step(bins, log_cumsum_well_a, label=\"Well A\")\n",
        "plt.step(bins, log_cumsum_well_b, label=\"Well B\")\n",
        "plt.step(bins, log_cumsum_well_c, label=\"Well C\")\n",
        "plt.step(bins, log_cumsum_well_d, label=\"Well D\")\n",
        "\n",
        "plt.title('Gutenberg-Richter Plot of Wells')\n",
        "plt.legend()\n",
        "plt.xlabel('Magnitude')\n",
        "plt.ylabel('log(N>=M)')\n",
        "plt.ylim(ymin=0)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:4: RuntimeWarning: divide by zero encountered in log10\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:5: RuntimeWarning: divide by zero encountered in log10\n",
            "  \"\"\"\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:6: RuntimeWarning: divide by zero encountered in log10\n",
            "  \n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:7: RuntimeWarning: divide by zero encountered in log10\n",
            "  import sys\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XMvW3U6jZvPW",
        "colab_type": "text"
      },
      "source": [
        "### Jump to C. Determine b-values of the 4 wells"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v6ro1JwlZ9ND",
        "colab_type": "text"
      },
      "source": [
        "I use `Plotly` to find the cutoff. Adjust with whichever well you'd like to analyse, place the cursor on the plot to hover over, and get the cutoff."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pIeug-aMUhK0",
        "colab_type": "code",
        "outputId": "76b269a8-24f3-432f-fd3b-bb56abd00c61",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        }
      },
      "source": [
        "import plotly.graph_objects as go\n",
        "\n",
        "fig = go.Figure()\n",
        "\n",
        "fig.add_trace(go.Scatter(x=np.round(bins, 4), y=log_cumsum_well_c,\n",
        "                    mode='lines+markers',\n",
        "                    name='magnitude well'))\n",
        "\n",
        "fig.update_layout(\n",
        "    title={\n",
        "        'text': \"Gutenberg-Richter Plot of Well C\",\n",
        "        'y':0.9,\n",
        "        'x':0.5,\n",
        "        'xanchor': 'center',\n",
        "        'yanchor': 'top'})"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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      "metadata": {
        "id": "jYNG9HclbzB0",
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      "source": [
        "Magnitude cutoffs obtained (magnitude has been rounded to 4 decimals):\n",
        "\n",
        "* Well A: -2.2646\n",
        "* Well B: -2.0804\n",
        "* Well C: -2.3875\n",
        "* Well D: -2.2032\n",
        "\n",
        "Next, using `np.where()` to find the `index` of the cutoff where the arrays of `bins` and `log_cumsum_well_xxxx` have to be sliced off.\n",
        "\n",
        "Some results of `log_cumsum_well_xxxx` comes in `-inf` (because $log(0) = -\\infty$ when $N=0$), this also should be cleaned off. \n",
        "\n",
        "Do regression using `np.polyfit` to get `a` and `b` from equation $log(N)=a-bM$, finally plot the regression line."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gPNncpRpn9KS",
        "colab_type": "code",
        "outputId": "68e196e6-2f14-4adc-c86b-2dc3231729d9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "source": [
        "# find index of cutoff\n",
        "bins_round = np.round(bins, 4)\n",
        "\n",
        "index_a = np.where(bins_round == -2.2646)[0][0]\n",
        "index_b = np.where(bins_round == -2.0804)[0][0]\n",
        "index_c = np.where(bins_round == -2.4182)[0][0]\n",
        "index_d = np.where(bins_round == -2.2032)[0][0]\n",
        "\n",
        "# slicing magnitude bins and cumulative event arrays\n",
        "bins_a = bins[index_a:]\n",
        "bins_b = bins[index_b:]\n",
        "bins_c = bins[index_c:]\n",
        "bins_d = bins[index_d:]\n",
        "\n",
        "cum_a = log_cumsum_well_a[index_a:]\n",
        "cum_b = log_cumsum_well_b[index_b:]\n",
        "cum_c = log_cumsum_well_c[index_c:]\n",
        "cum_d = log_cumsum_well_d[index_d:]\n",
        "\n",
        "# clean off the -inf values, first find index at array cumsum, then slice both cumsum and bins array\n",
        "idinf_a = np.where(np.isinf(cum_a))[0][0]\n",
        "idinf_b = np.where(np.isinf(cum_b))[0][0]\n",
        "idinf_c = np.where(np.isinf(cum_c))[0][0]\n",
        "idinf_d = np.where(np.isinf(cum_d))[0][0]\n",
        "\n",
        "\n",
        "clean_cum_a = cum_a[:idinf_a]\n",
        "clean_cum_b = cum_b[:idinf_b]\n",
        "clean_cum_c = cum_c[:idinf_c]\n",
        "clean_cum_d = cum_d[:idinf_d]\n",
        "\n",
        "\n",
        "clean_bins_a = bins_a[:idinf_a]\n",
        "clean_bins_b = bins_b[:idinf_b]\n",
        "clean_bins_c = bins_c[:idinf_c]\n",
        "clean_bins_d = bins_d[:idinf_d]\n",
        "\n",
        "\n",
        "b_A, a_A = np.polyfit(clean_bins_a, clean_cum_a, deg=1) # b (slope) and a (intercept) of well A\n",
        "b_B, a_B = np.polyfit(clean_bins_b, clean_cum_b, deg=1) # b (slope) and a (intercept) of well B\n",
        "b_C, a_C = np.polyfit(clean_bins_c, clean_cum_c, deg=1) # b (slope) and a (intercept) of well C\n",
        "b_D, a_D = np.polyfit(clean_bins_d, clean_cum_d, deg=1) # b (slope) and a (intercept) of well D\n",
        "\n",
        "\n",
        "print('b-value of Well A:', -b_A)\n",
        "print('b-value of Well B:', -b_B)\n",
        "print('b-value of Well C:', -b_C)\n",
        "print('b-value of Well D:', -b_D)\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "b-value of Well A: 2.2905977209649935\n",
            "b-value of Well B: 2.0236367714742394\n",
            "b-value of Well C: 1.866161989933815\n",
            "b-value of Well D: 1.96543742365093\n"
          ],
          "name": "stdout"
        }
      ]
    },
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        "id": "yMa3lq6XtpsG",
        "colab_type": "code",
        "outputId": "011a294a-33ec-42d3-cb39-77c5739b9d03",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        }
      },
      "source": [
        "plt.figure(figsize=(10,10))\n",
        "plt.step(clean_bins_a, clean_cum_a, label=\"Well A\", color='blue')\n",
        "plt.step(clean_bins_b, clean_cum_b, label=\"Well B\", color='orange')\n",
        "plt.step(clean_bins_c, clean_cum_c, label=\"Well C\", color='green')\n",
        "plt.step(clean_bins_d, clean_cum_d, label=\"Well D\", color='red')\n",
        "\n",
        "plt.title('Cut-off Gutenberg-Richter Plot of Wells')\n",
        "plt.legend()\n",
        "plt.xlabel('Magnitude')\n",
        "plt.ylabel('log(N>=M)')\n",
        "plt.ylim(ymin=0)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cY0ZQhy_iSRC",
        "colab_type": "text"
      },
      "source": [
        "### B. Find the Lowest Magnitude ($M$ at which the cumulative number of events is 5% of the total number of events)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z7qdkQJBMYhs",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def ecdf(data):\n",
        "    \"\"\"Compute ECDF for a one-dimensional array of measurements.\"\"\"\n",
        "    # Number of data points: n\n",
        "    n = len(data)\n",
        "\n",
        "    # x-data for the ECDF: x\n",
        "    x = np.sort(data)\n",
        "\n",
        "    # y-data for the ECDF: y\n",
        "    y = np.arange(1, n+1) / n\n",
        "\n",
        "    return x, y"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JqEkPDPJZLgG",
        "colab_type": "code",
        "outputId": "3096363c-d8db-4c85-cee0-5a367048bc2b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 638
        }
      },
      "source": [
        "xa, ya = ecdf(well_a['Magnitude'])\n",
        "xb, yb = ecdf(well_b['Magnitude'])\n",
        "xc, yc = ecdf(well_c['Magnitude'])\n",
        "xd, yd = ecdf(well_d['Magnitude'])\n",
        "\n",
        "plt.figure(figsize=(10,10))\n",
        "\n",
        "plt.plot(xa, ya, '.', label='Well A')\n",
        "plt.plot(xb, yb, '.', label='Well B')\n",
        "plt.plot(xc, yc, '.', label='Well C')\n",
        "plt.plot(xd, yd, '.', label='Well D')\n",
        "plt.title('CDF Plot of Magnitudes of Each Well')\n",
        "plt.legend()\n",
        "plt.xlabel('Magnitudes'); plt.ylabel('Cumulative Distribution Function')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Cumulative Distribution Function')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qg6JEeXUamT1",
        "colab_type": "code",
        "outputId": "6978ea7d-1a54-4cdb-ac67-957ef25a20b8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "source": [
        "# for well A\n",
        "rounded_a_cdf = np.round(ya, 3)\n",
        "find_5a_percent = np.where(rounded_a_cdf == 0.050)\n",
        "magnitude_a_arr = []\n",
        "\n",
        "for i in range(len(find_5a_percent[0])):\n",
        "  magnitude_a_ = xa[find_5a_percent[0][i]]\n",
        "  magnitude_a_arr.append(magnitude_a_)\n",
        "\n",
        "lowest_mag_a = np.mean(magnitude_a_arr)\n",
        "print('Well A lowest magnitude at which the cumulative number of events is 5% of the total number of events:', lowest_mag_a)\n",
        "\n",
        "# for well B\n",
        "rounded_b_cdf = np.round(yb, 3)\n",
        "find_5b_percent = np.where(rounded_b_cdf == 0.050)\n",
        "magnitude_b_arr = []\n",
        "\n",
        "for i in range(len(find_5b_percent[0])):\n",
        "  magnitude_b_ = xb[find_5b_percent[0][i]]\n",
        "  magnitude_b_arr.append(magnitude_b_)\n",
        "\n",
        "lowest_mag_b = np.mean(magnitude_b_arr)\n",
        "print('Well B lowest magnitude at which the cumulative number of events is 5% of the total number of events:', lowest_mag_b)\n",
        "\n",
        "# for well C\n",
        "rounded_c_cdf = np.round(yc, 3)\n",
        "find_5c_percent = np.where(rounded_c_cdf == 0.050)\n",
        "magnitude_c_arr = []\n",
        "\n",
        "for i in range(len(find_5c_percent[0])):\n",
        "  magnitude_c_ = xc[find_5c_percent[0][i]]\n",
        "  magnitude_c_arr.append(magnitude_c_)\n",
        "\n",
        "lowest_mag_c = np.mean(magnitude_c_arr)\n",
        "print('Well C lowest magnitude at which the cumulative number of events is 5% of the total number of events:', lowest_mag_c)\n",
        "\n",
        "# for well D\n",
        "rounded_d_cdf = np.round(yd, 3)\n",
        "find_5d_percent = np.where(rounded_d_cdf == 0.050)\n",
        "magnitude_d_arr = []\n",
        "\n",
        "for i in range(len(find_5d_percent[0])):\n",
        "  magnitude_d_ = xd[find_5d_percent[0][i]]\n",
        "  magnitude_d_arr.append(magnitude_d_)\n",
        "\n",
        "lowest_mag_d = np.mean(magnitude_d_arr)\n",
        "print('Well D lowest magnitude at which the cumulative number of events is 5% of the total number of events:', lowest_mag_d)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Well A lowest magnitude at which the cumulative number of events is 5% of the total number of events: -2.91\n",
            "Well B lowest magnitude at which the cumulative number of events is 5% of the total number of events: -3.06\n",
            "Well C lowest magnitude at which the cumulative number of events is 5% of the total number of events: -3.19\n",
            "Well D lowest magnitude at which the cumulative number of events is 5% of the total number of events: -3.35\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mn0rU0jIMYhk",
        "colab_type": "text"
      },
      "source": [
        "## Part 2. Seismic Moment and Surface Area"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iM5FP0iONZqH",
        "colab_type": "text"
      },
      "source": [
        "Determine the seismic moment, $M_0$ using the equation below.\n",
        "\n",
        "$$ M_w=\\frac{2}{3} (log_{10}M_0-9)$$\n",
        "\n",
        "Re-arranging the equation becomes:\n",
        "\n",
        "$$ M_0 = 10 ^{\\frac{3M_w}{2} +9}$$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tGJZnwtrhs0j",
        "colab_type": "code",
        "outputId": "1293f333-62c3-4a8d-9f86-d1430b95bf5a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "source": [
        "M0_a = 10**((3 * well_a['Magnitude'] / 2) + 9)\n",
        "M0_b = 10**((3 * well_b['Magnitude'] / 2) + 9)\n",
        "M0_c = 10**((3 * well_c['Magnitude'] / 2) + 9)\n",
        "M0_d = 10**((3 * well_d['Magnitude'] / 2) + 9)\n",
        "\n",
        "print('Total seismic moment in Well A:', sum(M0_a))\n",
        "print('Total seismic moment in Well B:', sum(M0_b))\n",
        "print('Total seismic moment in Well C:', sum(M0_c))\n",
        "print('Total seismic moment in Well D:', sum(M0_d))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total seismic moment in Well A: 934687598.5997992\n",
            "Total seismic moment in Well B: 1006178607.050319\n",
            "Total seismic moment in Well C: 1606197224.225522\n",
            "Total seismic moment in Well D: 1415936334.3759482\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IyX18MidQ6EA",
        "colab_type": "text"
      },
      "source": [
        "Assume a unifrom stress drop for all events $\\Delta \\tau = 0.5 MPa$, and a circular fault patch. Calculate the total surface area using this equation.\n",
        "\n",
        "$$ \\pi r^2 = S = \\pi (\\frac {7M_0}{16\\Delta\\tau})^\\frac{2}{3} $$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SLnrt_AxQ5c9",
        "colab_type": "code",
        "outputId": "1b4d87c0-cb24-44a0-aac2-9674a671d274",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "source": [
        "stress_drop = 0.5 * 1E+06 # MPa to Pa\n",
        "\n",
        "area_a = np.pi * ((7 * M0_a) / (16 * stress_drop))**(2/3)\n",
        "area_b = np.pi * ((7 * M0_b) / (16 * stress_drop))**(2/3)\n",
        "area_c = np.pi * ((7 * M0_c) / (16 * stress_drop))**(2/3)\n",
        "area_d = np.pi * ((7 * M0_d) / (16 * stress_drop))**(2/3)\n",
        "\n",
        "Area_D=np.pi*np.power((7*M0_d)/(16*0.5*10.0**6.),2/3)\n",
        "\n",
        "print('Total fault surface area in Well A:', sum(area_a), 'm2')\n",
        "print('Total fault surface area in Well B:', sum(area_b), 'm2')\n",
        "print('Total fault surface area in Well C:', sum(area_c), 'm2')\n",
        "print('Total fault surface area in Well D:', sum(area_d), 'm2')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total fault surface area in Well A: 2923.782636817326 m2\n",
            "Total fault surface area in Well B: 2954.414617810344 m2\n",
            "Total fault surface area in Well C: 3902.1097080397126 m2\n",
            "Total fault surface area in Well D: 3186.7472790454185 m2\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}