12 - Welly Project and Multi Well.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Welly Multi Well Projects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "from welly import Project\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "0it [00:00, ?it/s]/Users/andy/opt/anaconda3/lib/python3.8/site-packages/welly/well.py:193: FutureWarning: From v0.5 the default will be 'original', keeping whatever is used in the LAS file. If you want to force conversion to metres, change your code to use `index='m'`.\n",
      "  warnings.warn(m, FutureWarning)\n",
      "/Users/andy/opt/anaconda3/lib/python3.8/site-packages/welly/curve.py:216: UserWarning: Irregular sampling in depth is not supported. Interpolating to regular basis.\n",
      "  warnings.warn(m)\n",
      "4it [00:06,  1.56s/it]\n"
     ]
    }
   ],
   "source": [
    "# Loading wells using Project\n",
    "wells = Project.from_las('welly_data/*.las')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Well Meta Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table><tr><th>Index</th><th>UWI</th><th>Data</th><th>Curves</th></tr><tr><td>0</td><td><strong>L06-06</strong></td><td>5&nbsp;curves</td><td>GR, DT, RHOB, DRHO, NPHI</td></tr><tr><td>1</td><td><strong>L07-01</strong></td><td>4&nbsp;curves</td><td>GR, DT, RHOB, NPHI</td></tr><tr><td>2</td><td><strong>L05-B-01</strong></td><td>5&nbsp;curves</td><td>GR, DT, RHOB, DRHO, NPHI</td></tr><tr><td>3</td><td><strong>L06-07</strong></td><td>5&nbsp;curves</td><td>GR, DT, RHOB, DRHO, NPHI</td></tr></table>"
      ],
      "text/plain": [
       "Project(4 wells: L06-06, L07-01, L05-B-01, L06-07)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Viewing contents of wells\n",
    "wells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['L06-06', 'L07-01', 'L05-B-01', 'L06-07']"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Call upon UWIs\n",
    "wells.uwis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Well(uwi: 'L06-06', 5 curves: ['GR', 'DT', 'RHOB', 'DRHO', 'NPHI'])\n",
      "Well(uwi: 'L07-01', 4 curves: ['GR', 'DT', 'RHOB', 'NPHI'])\n",
      "Well(uwi: 'L05-B-01', 5 curves: ['GR', 'DT', 'RHOB', 'DRHO', 'NPHI'])\n",
      "Well(uwi: 'L06-07', 5 curves: ['GR', 'DT', 'RHOB', 'DRHO', 'NPHI'])\n"
     ]
    }
   ],
   "source": [
    "# Print individual well details\n",
    "for well in wells:\n",
    "    print(well)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L06-06     53.808408           4.672192\n",
      "L07-01     53.722768           4.796468\n",
      "L05-B-01   53.705031           4.603479\n",
      "L06-07     53.706549           4.898703\n"
     ]
    }
   ],
   "source": [
    "# Print well name and location\n",
    "for well in wells:\n",
    "    print(f'{well.header.name} \\t {well.location.latitude} \\t {well.location.longitude}'.expandtabs(10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a dataframe of well header information\n",
    "\n",
    "well_dict = {}\n",
    "for well in wells:\n",
    "    well_dict[well.uwi] = {'well name':well.header.name, \n",
    "                          'Latitude':well.location.latitude,\n",
    "                          'Longitude':well.location.longitude}\n",
    "\n",
    "wells_df = pd.DataFrame.from_dict(well_dict, orient='index')\n",
    "\n",
    "wells_df.reset_index(inplace=True)\n",
    "\n",
    "wells_df.rename(columns={'index':'UWI'}, inplace=True)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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>UWI</th>\n",
       "      <th>well name</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>L06-06</td>\n",
       "      <td>L06-06</td>\n",
       "      <td>53.808408</td>\n",
       "      <td>4.672192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>L07-01</td>\n",
       "      <td>L07-01</td>\n",
       "      <td>53.722768</td>\n",
       "      <td>4.796468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>L05-B-01</td>\n",
       "      <td>L05-B-01</td>\n",
       "      <td>53.705031</td>\n",
       "      <td>4.603479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>L06-07</td>\n",
       "      <td>L06-07</td>\n",
       "      <td>53.706549</td>\n",
       "      <td>4.898703</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        UWI well name   Latitude  Longitude\n",
       "0    L06-06    L06-06  53.808408   4.672192\n",
       "1    L07-01    L07-01  53.722768   4.796468\n",
       "2  L05-B-01  L05-B-01  53.705031   4.603479\n",
       "3    L06-07    L06-07  53.706549   4.898703"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wells_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mapping the Well Locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "import folium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=%3C%21DOCTYPE%20html%3E%0A%3Chead%3E%20%20%20%20%0A%20%20%20%20%3Cmeta%20http-equiv%3D%22content-type%22%20content%3D%22text/html%3B%20charset%3DUTF-8%22%20/%3E%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%3Cscript%3E%0A%20%20%20%20%20%20%20%20%20%20%20%20L_NO_TOUCH%20%3D%20false%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20L_DISABLE_3D%20%3D%20false%3B%0A%20%20%20%20%20%20%20%20%3C/script%3E%0A%20%20%20%20%0A%20%20%20%20%3Cstyle%3Ehtml%2C%20body%20%7Bwidth%3A%20100%25%3Bheight%3A%20100%25%3Bmargin%3A%200%3Bpadding%3A%200%3B%7D%3C/style%3E%0A%20%20%20%20%3Cstyle%3E%23map%20%7Bposition%3Aabsolute%3Btop%3A0%3Bbottom%3A0%3Bright%3A0%3Bleft%3A0%3B%7D%3C/style%3E%0A%20%20%20%20%3Cscript%20src%3D%22https%3A//cdn.jsdelivr.net/npm/leaflet%401.6.0/dist/leaflet.js%22%3E%3C/script%3E%0A%20%20%20%20%3Cscript%20src%3D%22https%3A//code.jquery.com/jquery-1.12.4.min.js%22%3E%3C/script%3E%0A%20%20%20%20%3Cscript%20src%3D%22https%3A//maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js%22%3E%3C/script%3E%0A%20%20%20%20%3Cscript%20src%3D%22https%3A//cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js%22%3E%3C/script%3E%0A%20%20%20%20%3Clink%20rel%3D%22stylesheet%22%20href%3D%22https%3A//cdn.jsdelivr.net/npm/leaflet%401.6.0/dist/leaflet.css%22/%3E%0A%20%20%20%20%3Clink%20rel%3D%22stylesheet%22%20href%3D%22https%3A//maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css%22/%3E%0A%20%20%20%20%3Clink%20rel%3D%22stylesheet%22%20href%3D%22https%3A//maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css%22/%3E%0A%20%20%20%20%3Clink%20rel%3D%22stylesheet%22%20href%3D%22https%3A//maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css%22/%3E%0A%20%20%20%20%3Clink%20rel%3D%22stylesheet%22%20href%3D%22https%3A//cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css%22/%3E%0A%20%20%20%20%3Clink%20rel%3D%22stylesheet%22%20href%3D%22https%3A//cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css%22/%3E%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%3Cmeta%20name%3D%22viewport%22%20content%3D%22width%3Ddevice-width%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20initial-scale%3D1.0%2C%20maximum-scale%3D1.0%2C%20user-scalable%3Dno%22%20/%3E%0A%20%20%20%20%20%20%20%20%20%20%20%20%3Cstyle%3E%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%23map_0b4ccbe340c54802a1f374c7a2de8f7e%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20position%3A%20relative%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20width%3A%20100.0%25%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20height%3A%20100.0%25%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20left%3A%200.0%25%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20top%3A%200.0%25%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%3C/style%3E%0A%20%20%20%20%20%20%20%20%0A%3C/head%3E%0A%3Cbody%3E%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%3Cdiv%20class%3D%22folium-map%22%20id%3D%22map_0b4ccbe340c54802a1f374c7a2de8f7e%22%20%3E%3C/div%3E%0A%20%20%20%20%20%20%20%20%0A%3C/body%3E%0A%3Cscript%3E%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20map_0b4ccbe340c54802a1f374c7a2de8f7e%20%3D%20L.map%28%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22map_0b4ccbe340c54802a1f374c7a2de8f7e%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20center%3A%20%5B53.735689%2C%204.7427105%5D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20crs%3A%20L.CRS.EPSG3857%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20zoom%3A%207%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20zoomControl%3A%20true%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20preferCanvas%3A%20false%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%29%3B%0A%0A%20%20%20%20%20%20%20%20%20%20%20%20%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20tile_layer_4205138f9dd64c32a5f3d82a334a2c47%20%3D%20L.tileLayer%28%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22https%3A//%7Bs%7D.tile.openstreetmap.org/%7Bz%7D/%7Bx%7D/%7By%7D.png%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7B%22attribution%22%3A%20%22Data%20by%20%5Cu0026copy%3B%20%5Cu003ca%20href%3D%5C%22http%3A//openstreetmap.org%5C%22%5Cu003eOpenStreetMap%5Cu003c/a%5Cu003e%2C%20under%20%5Cu003ca%20href%3D%5C%22http%3A//www.openstreetmap.org/copyright%5C%22%5Cu003eODbL%5Cu003c/a%5Cu003e.%22%2C%20%22detectRetina%22%3A%20false%2C%20%22maxNativeZoom%22%3A%2018%2C%20%22maxZoom%22%3A%2018%2C%20%22minZoom%22%3A%200%2C%20%22noWrap%22%3A%20false%2C%20%22opacity%22%3A%201%2C%20%22subdomains%22%3A%20%22abc%22%2C%20%22tms%22%3A%20false%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%29.addTo%28map_0b4ccbe340c54802a1f374c7a2de8f7e%29%3B%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20marker_edee5a34c9424de58ef37925b8ceccc3%20%3D%20L.marker%28%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5B53.808408%2C%204.672192%5D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7B%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%29.addTo%28map_0b4ccbe340c54802a1f374c7a2de8f7e%29%3B%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20var%20popup_7434a5f0301241ff850f16d76d329881%20%3D%20L.popup%28%7B%22maxWidth%22%3A%20%22100%25%22%7D%29%3B%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20html_ed2278713fca4a9ea8355ee4dbd86d2f%20%3D%20%24%28%60%3Cdiv%20id%3D%22html_ed2278713fca4a9ea8355ee4dbd86d2f%22%20style%3D%22width%3A%20100.0%25%3B%20height%3A%20100.0%25%3B%22%3EL06-06%3C/div%3E%60%29%5B0%5D%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20popup_7434a5f0301241ff850f16d76d329881.setContent%28html_ed2278713fca4a9ea8355ee4dbd86d2f%29%3B%0A%20%20%20%20%20%20%20%20%0A%0A%20%20%20%20%20%20%20%20marker_edee5a34c9424de58ef37925b8ceccc3.bindPopup%28popup_7434a5f0301241ff850f16d76d329881%29%0A%20%20%20%20%20%20%20%20%3B%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20marker_bd64e2814868462cb75dfd15f3487e1e%20%3D%20L.marker%28%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5B53.722768%2C%204.796468%5D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7B%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%29.addTo%28map_0b4ccbe340c54802a1f374c7a2de8f7e%29%3B%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20var%20popup_3c2c9ed7ca8e42b38e985b665c3e0839%20%3D%20L.popup%28%7B%22maxWidth%22%3A%20%22100%25%22%7D%29%3B%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20html_490c51e5b54b433f8f762698de4ff0e3%20%3D%20%24%28%60%3Cdiv%20id%3D%22html_490c51e5b54b433f8f762698de4ff0e3%22%20style%3D%22width%3A%20100.0%25%3B%20height%3A%20100.0%25%3B%22%3EL07-01%3C/div%3E%60%29%5B0%5D%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20popup_3c2c9ed7ca8e42b38e985b665c3e0839.setContent%28html_490c51e5b54b433f8f762698de4ff0e3%29%3B%0A%20%20%20%20%20%20%20%20%0A%0A%20%20%20%20%20%20%20%20marker_bd64e2814868462cb75dfd15f3487e1e.bindPopup%28popup_3c2c9ed7ca8e42b38e985b665c3e0839%29%0A%20%20%20%20%20%20%20%20%3B%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20marker_cbebe74369c8479185e160dec3d817d5%20%3D%20L.marker%28%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5B53.705031%2C%204.603479%5D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7B%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%29.addTo%28map_0b4ccbe340c54802a1f374c7a2de8f7e%29%3B%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20var%20popup_b48670ce3863400e8cccf1232a3f8eba%20%3D%20L.popup%28%7B%22maxWidth%22%3A%20%22100%25%22%7D%29%3B%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20html_8c6285f8d9e949418c943adb63923b16%20%3D%20%24%28%60%3Cdiv%20id%3D%22html_8c6285f8d9e949418c943adb63923b16%22%20style%3D%22width%3A%20100.0%25%3B%20height%3A%20100.0%25%3B%22%3EL05-B-01%3C/div%3E%60%29%5B0%5D%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20popup_b48670ce3863400e8cccf1232a3f8eba.setContent%28html_8c6285f8d9e949418c943adb63923b16%29%3B%0A%20%20%20%20%20%20%20%20%0A%0A%20%20%20%20%20%20%20%20marker_cbebe74369c8479185e160dec3d817d5.bindPopup%28popup_b48670ce3863400e8cccf1232a3f8eba%29%0A%20%20%20%20%20%20%20%20%3B%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20marker_896f232d3ac04964bc518d9e0594e506%20%3D%20L.marker%28%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5B53.706549%2C%204.898703%5D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7B%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%29.addTo%28map_0b4ccbe340c54802a1f374c7a2de8f7e%29%3B%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%20%20%20%20%20%20%20%20var%20popup_2933a83ac68a437ea405cbdfeeb88e36%20%3D%20L.popup%28%7B%22maxWidth%22%3A%20%22100%25%22%7D%29%3B%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20var%20html_889a707f318c4361903703ea2b8a9514%20%3D%20%24%28%60%3Cdiv%20id%3D%22html_889a707f318c4361903703ea2b8a9514%22%20style%3D%22width%3A%20100.0%25%3B%20height%3A%20100.0%25%3B%22%3EL06-07%3C/div%3E%60%29%5B0%5D%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20popup_2933a83ac68a437ea405cbdfeeb88e36.setContent%28html_889a707f318c4361903703ea2b8a9514%29%3B%0A%20%20%20%20%20%20%20%20%0A%0A%20%20%20%20%20%20%20%20marker_896f232d3ac04964bc518d9e0594e506.bindPopup%28popup_2933a83ac68a437ea405cbdfeeb88e36%29%0A%20%20%20%20%20%20%20%20%3B%0A%0A%20%20%20%20%20%20%20%20%0A%20%20%20%20%0A%3C/script%3E onload=\"this.contentDocument.open();this.contentDocument.write(    decodeURIComponent(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fe67a186670>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_lat = wells_df['Latitude'].mean()\n",
    "mean_long = wells_df['Longitude'].mean()\n",
    "\n",
    "m = folium.Map(location=[mean_lat, mean_long],zoom_start=7)\n",
    "\n",
    "for index, well_location in wells_df.iterrows():\n",
    "    folium.Marker([well_location['Latitude'], well_location['Longitude']],\n",
    "                 popup=well_location['well name']).add_to(m)\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting Curves from Multiple Wells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot GR from all wells\n",
    "fig, axs = plt.subplots(figsize=(14, 10), ncols=len(wells))\n",
    "\n",
    "for i, (ax, well) in enumerate(zip(axs, wells)):\n",
    "    gr = well.get_curve('GR')\n",
    "    if gr is not None:\n",
    "        ax = gr.plot(ax=ax, c='green')\n",
    "    ax.set_title(f\"GR for\\n{well.header.name}\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA+gAAALICAYAAADseNpmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAABp60lEQVR4nO3de5wcVZn4/8+TyQ0Iw1UxEATUKAIqaLiJ66KsCOgKq8CC+5Msy5rVxfsNBHdBBBfdVbyjcWEBF0G+iMAiihFlkZVbuF+VyEUSuUgCmUBCLpPz+6Oqmc5keqZnpruruvvzfr3q1VWnTlU9VcwJ/XRVnRMpJSRJkiRJUrEmFB2AJEmSJEkyQZckSZIkqRRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQ1RIR8TcR8WhEPBsRuxUdj6TGs51Lnc92LnU223jxTNA7SEQ8HBEr8gb1eEScExHTqtafExGnDtpm+4hIETGxquyNEfGriFgWEUsj4n8iYqeq9ftGxNr8OM9GxKKI+PwI4f0H8KGU0rSU0m2NOmep29jOpc5nO5c6m21cwzFB7zx/nVKaBuwK7AZ8djQbR8TewC+Ay4CtgR2AO4D/i4iXVVX9U95wpwFvAo6JiEOG2fV2wD2jiaUqpp6xbCd1MNu51Pls51Jns41rSCboHSql9DhwFVmjH40vA+ellL6eUlqWUlqSUvoccANwco1jPQT8Fthp8LqImBIRzwI9wB0R8Ye8/NURcU1EPBMR90TEu6q2OScizoyIKyPiOeAtozwHqSvYzqXOZzuXOpttXIOZoHeoiJgBHAgsGMU2GwJvBP7fEKsvAt5WY7uZwD5k/yCsI6W0Mv/FDuB1KaWXR8Qk4H/IfvV7MfBh4PyIeFXVpu8FTgM2Bq6r9xykbmI7lzqf7VzqbLZxDWaC3nkujYhlwKPAk8BJg9Z/Kv8F7JmIeAa4s2rd5mR/E48Nsd/HgC2rlrfO99EH/B64kfob5V7ANOD0lNKqlNKvgCuAI6vqXJZS+r+U0tqU0vN17lfqFrZzqfPZzqXOZhvXkEzQO88hKaWNgX2BHVm3gQL8R0pp08oEvLZq3dPAWmD6EPudDjxVtfynfB+9wKbACuDcOmPcGng0pbS2quwRYJuq5Ufr3JfUjWznUueznUudzTauIZmgd6iU0v8C55D1xFjvNs8B1wOHDbH6cODqGtstBX4I/HWdh/oTsG1EVP/9vRRYVL3bOvcldS3budT5bOdSZ7ONa7CJI1dRG/sa8HBEvC6ldEed2xwPXBUR9wP/RfY38klgb2D3oTaIbFiII6i/x8cbgeXAZyLiK2Tvwvx1rf1LGtbXsJ1Lne5r2M6lTvY1bOPKeQe9g6WU/gycB/zrKLa5Dng78G6yd1geIRv64U0ppQeqqm4d+ZiKeZ3Ngb+r8xiryBr3gWSP4HwHOCqldH+9cUrK2M6lzmc7lzqbbVzVIiWfSpAkSZIkqWjeQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQu0REPBwRfzVE+X4RcX9ELI+IX0fEdoPW/1VE3BoRz0XEwog4fJhjTImIsyOiLyIej4hPDFq/YUR8JyKeioilEXFt485Q0ljaeUTcUxl+JZ/WRMT/DHOMmu08IiZHxMV5HCki9m30OUrdYozt+ZyIWDWoTffU2P++EbG2qt6iiPj8CDFFRHwpIhbn05ciIqrWz42I3+X7/ftxnL7U1Yr+3h4Rfzfo35Hl+f/X39DYM9VQTNC7WERsCVwC/AvZmIjzgR9Vrd8J+CFwIrAJ8DrglmF2eTIwE9gOeAvwmYg4oGr93Pw4r84/P96gU5FUw0jtPKW0c0ppWkppGrAx8Cjw/4bZ5ckM386vA/4/4PEGnoYkRm7PuS9X2nQ+9Q+zyz9Vtf83AcdExCHD1J8DHEL2feC1ZOMj/1PV+juAfwZurf+sJNWjld/bU0rnV/87QtauH8S23RITiw5AhXo3cE9K6f8BRMTJwFMRsWNK6X7gc8D3Uko/y+svzqdaZgN/n1J6Gng6Ir4P/D3w84jYEXgXMCOl1JfXH+4fDUmNMVI7r/ZmYEvgx8Psr2Y7TymtAr6WH2e4pEDS2IymPY9KSumhiPgtsBNwaY1qs4GvpJQW5sf/CvB+4Lv5Pr6dlz8/nlgkDall39tr1D0vpZQaciYalnfQu9vOZL92A5BSeg74Q14OsBdARNwVEY9FxH9HxOZD7SgiNgOmV+8vn6/saw/gEeDz+SPud0XEexp6NpKGMlI7rzYb+HFeZz11tHNJzVVPe/7niFgSEbeM5v+zETET2Ae4od7jY/uXWqmV39ur625H9gP+eY04CY3MBL27TQOWDipbSvaYK8AM4H3Ae8gegdkA+OYw+6psX2tfu+RlWwMfAs6NiFePI35JIxupnQNZHxHAocA5I+yrsn3NfUlqmpHa8zfI/n/9YrLHYM+JiH2G2d/WEfFMRPQBvwduJHtNpd7jLwWmVb+HLqlpWvm9vdpRwG9SSg+NIWaNgQl6d3sW6B1U1gssy+dXAP+VUvp9SulZ4IvAQQAR8d2qjiNOyPfFoP0N3tdq4NSU0qqU0v8Cvwb2b/RJSVrHSO284t3AEuB/KwVjaOeSmmvY9pxSujWltDiltCaldCVwPlnbJiJ+VtWe/y7f9k8ppU1TSr3ApmT/rz43r39CVf3v1jh+L/Csj71KLdHK7+3VjiL/d0GtYYLe3e4h60ACgIjYCHh5Xg5wJ1D9P90X5lNKH6jqPOKL+fsrj1XvL5+v3tdg/g9dar6R2nnFeu+XjaGdS2quettzRQICIKV0YFV7Pn+9iiktJetg6q/z5S9W1f/AUMfH9i+1Uiu/t1eOsQ/Zk68XN/JENDwT9O4yKSKmVibgJ8AuEfGefPlfgTurOpr5L+DoiHhZ/vjr8cAVw+z/POBzEbFZ3inc+xl4XPZa4I/AZyNiYt7g3wJc1eiTlLrcaNs5ETGDrD3W8wv5cO28MmzL1Hxxch6Hj79KYzOq9hwRh0bEtIiYEBH7k42ocHk9B4qIacARDJ9wnwd8IiK2iYitgU+ybvufnMcVVbH7XVMamyK/t1dU+qbxSbkW8h/N7nIl2eMvlemjZO+pnAY8DexJ9j9nAFJKZ5M13hvJOnhbCXxkmP2fRNZZxSNkj8n+e0rp5/m+VgMHkz1qsxT4PnDUeHudlbSeUbXz3PuA61NKf6hj/zXbee53+XG3IfsBbgXZEC6SRm+07fmjwCLgGeDfgfenlK4ZZv9bVx57JWvTmwN/N0z97wH/A9wF3A38NC+r+EUe5xvJhlZdQda5lKTRK+x7O0D+I8Dh+Hh7y4WvDUmSJEmSVDzvoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJWCCLkmSJElSCUwsOoDhbLnllmn77bcvOoxC9Pf3A9DT01NwJMXxGoz+Gtxyyy1PpZRe1MyYGq3Idt4uf2PG2XjtEutQcdrO2+e/X4XxNl+7xTxSvJ3Uzsv+38b4xq/sMZY1vlrtvNQJ+vbbb8/8+fOLDqMQfX19APT29hYcSXG8BqO/BhHxSDPjaYYi23m7/I0ZZ+PVFeuFF0JPD0ycmH1WpjVr4OqrISXYcEOYMwemTh1YP2HC+vMTJmTTKIeEHypO23l7/a2B8bZCu8U8Uryd1M7L/t/G+Mav7DGWNb5a7bzUCbokqYP99rfwxz8Ova4yBGjlM2Jgvrp8qG0iBpLhylRZzj8nrliRLW+00UB5ZR+V6cgj6zuPf/u3+upVXH897LXX6LaRJEldwQRdktR6N98M++xT2OE3LOrAO+4Ir3xlUUeXJEklZ4IuSWq9N7wBTj0V7ryz9mPfQ5XXU1a5A7527bp3xCvLa9eyevVqSIlJPT1Driel7DH2Rrv/fthii9rrb74ZZs1q/HElSVJbaP8E/brrYN68+upWPyI53HuA9darNtJjmIPLt9oK9t675vEnPPtsNj9tWu04xvuldjR1CzhWLFuWLW+8cdOPtZ6UYNUqWLkymzbeGF71qqHrShq9CRPgxBNHv111wj3UdN11cPzxA8uDt8mXJ/T3Z8sTJqz/OP3g+VZ66qlijitJkkqhvRP0lOAv/qLoKJpiWtEBlMDGRQdQy7vfDf/wD/COdxQdibS+P/4RttuukEOXq+uV4RXej+trXgO77w6nnw4vaquOmiVJUhO1d4Iekd0t+eUv1y0f6q715z/f2tjUuS65JJvAx1FVPr29sPXW8Kc/FR2Jann0UZgxo+goJElSCbV3gg5ZJ0NvfOO6PQFXHluuTtBvvRX+539aH5861ytfCQWN3y3VtOmmsGhRIYdu+DAmjzwCy5YN/bh69Xzl0faPfawxx22m3XaDzTYrOgpJklRS7Z+gA3z84/D1rxcdhbrN735XdARSMZ55Bs48c72nlSY//3w2P3XqyPsYqa+Pf/mXbLzxMpgxI7vrLUmS1GSdkaDPmZM9clz9hW+4MXJrlY12m0Ydo7o8/6K6du1aACYM14lZxeAO6Crrh+tAbbSd4A3evp464zzGC9egMj7xWI/35JOjP349IuAzn4ETToBNNmnOMaQyOuaYgdc8qtSRlrfWO94BEydCT8/AlI+DvmrNGohg8uTJ6z51VT1Vyj71qeLOQZIkdZXOSNB32gl+/vOsV/Tly4evW/nSVStRHksyOdS2Q+1/FPsesmYD9z/0Qcd4bepNxEe5/xeWGrX/Zvjyl7Np9eosEZC6wfe+l73isWJFuZ9e+ulPs57iN9ooW676cXXt889ny694BcyePf5/PyVJkhqgczKK//kfyN9/7AR+VWyzazBp0sD8mWfCBz5QXCxSs225Jfzbv8Gll5Y7QQc47bQhi9e523/00euufOQReOlLmxaSJElSLZ2ToB93XPYu+nB3QQbfWR1cdzx3XkfadpTr1+tsqcH7b4f161yDRuz/scey4dGWL8/ueK9Zk02Nfrf0gx/Mporrr4e99mrsMaQyOOSQrHO2pUthwgSeW7ECenrYaOONBx4nr3xOmJA9ZVJ5ZeXee+G97y00/JqeecYEXZIkFaJzEnSAyZOLjqBxVq/OPjfYoNg4itSTj1Q81h6hb78dfv3rgeXPfKaYTqf23ntg/gc/gP/v/2t9DFKz7LPPC7Mbdcpj4h/5yMDnu99dbCySJKmrdFaCLlXbbbeiI1jXtGneSZfawf/+78BnK/u0kCRJXa+O7rGlkurvh09/OntVYeuts8dlB/fA3Cw33ABr1647DvNI07JlWYdUUie65BJWHXkkq448MutAbuutYautsvfVt9xyoKO2dvGrX8ETTxQdhSRJ6jLeQVd7ufHGoe9CP/YYXHBB6+JYvdpen6UlS+Dgg+HOO6Gvjw56yWjdf0+q76J/9KOwyy6tj0eSJHUFE3S1j113hTvuGN8+rr8eNtts/Q6sqjuyqhor+YXPiOwOoEm5NOC3v806ietE3//+0OWXXgp//nNLQ5EkSd3DBF3t4xWvGH+CXt1h22jNng3nnDO+40ud5J3vhMWLs9dNenroW7YMgN6NN15nzPEXPmuVbb11iwMfhwh43esGfrxbtgwWLKh/+x12gN13hyOOgL/5m+bFKUmS2pIJutrHxRcPzH//+3Dhhdl7oq1y7rlwySVZQlF5//yaa2CPPVoXg1Q2m28+MD8x/1/KaEdeWLYMHnhg4AmViKx9HXkk3H9/Y+JslD//eXx30B96KJsuusgO6CRJ0npM0NWe3v/+bHruOXjNa7LHzw87LEuc167N7mg14530/A7hC/bcc+h6u+wC116bPU4vaXjTpg096sJ9941tfw88kHVUV1YTJmSPykuSJA1igq72ttFG8OCDQ6/7+MeLu7t9993w8MMm6FIRNtssu7O/ZEnRkQxt7Vo48UT4678uOhJJklQyDrOmzrX77rByZevupC1atO6wamUbh13qFltumb0bP8ywh31Ll9K3dOn66770pebFNXEi/Pd/Z1NlrHVJkqQq3kFXZ5s8GX73u+yO1RVXZI/Er12bDZO2di186EOwYsX4j7PxxrDBBuPfj6TmqU7E16whFi6Ej3wk+/cgpWwYx7VrG3/cm2+GWbMav19JktRxTNDVHSZMgHe9a/3yo4+GNWuy6bbb4Mor4bTT6t/vJZfYE7NUpK98BT71qVFvNspu7MbniitM0CVJUl18xF3dLQImTcrufr/xjbD99qPb/tWvbkpYkur0l39ZdAQje+yxoiOQJEltwjvoUrUbbhhd/Y03bk4ckuoza9aYhivr6+sDoHfwkHBr18I3vwmPPALLl0NfX1b26KPw29+OLca77x7bdpIkqeuYoEvVTj4Zzjqr/vozZmSPx/f0NC0kSS00YULWwePHPtaY/Z12GpxwQmP2JUmSOp4JulRtxoyiI5Ba45OfhK9+taG7bOl73ePU1Fjf9KasPwufsJEkSaPkO+jSwoXZu+iVaTTOPNO752pPjz9edASd67rroLd33X9XXv7yoqOSJEltwDvo0lNPjX6bO+6AXXbJHoeV2tH552dTA9V8r3s4ixdnj4CvXbvuD2SDfzAbanm4z8EGrV+5ahVEMGXy5PW3qV5+5BH48Y/rP59aHnxwYL9/+hNMnz7+fUqSpI5jgi699rVj287kXBq/E06AuXNbftgpLT9ibvJkmDq1qKNLkqSSM0FXd0tpbB04PfNMw0OR1vOTn8C7392496WHe42j3tc7hqm3ccRAj+pD3ZUeat2qVfUdtxMsWwbTphUdhSRJKjETdHW3//xP+NKX6q//7W/DP/9z8+KRql12WWP3l9KYhiSr1yh7cOgMd90Fr3pVNl/9A0j152j7tpAkSV3LBF3da/VqmDOn/vp33DH2x+GlsTjnHDjnnOHf7U4pe3978FSrfO3age2q99GAsmXLlkFKbFzpvbxB+61ZNnjdvHnwqU/RUrvs0trjSZKkjmaCru60di389Kf117/3Xnj1q5sXjzRWEdlIAqMdTSCl7FWNiKw/heoex6sfR6+uP9R81XKaNClbrh5ebLj9QHYH+i//cnSxF+0lL4E99oAdd4Qvfzn7se/YY2HTTYuOTJIktTkTdHWnU0+Fk06qv/6f/2yCrs7ygQ80vHO2dhoHfVwefxwuvzybKj73uXXr3H037Lxza+OSJEltz26o1X1WrID/+q/RbfOe9zQnFqko//iPsMkm2XjdG2+cdV620UawwQZZL+NTCuvnvDNcf33REUiSpDbkHXR1n8cfh4cfHt02Tz2V3W0czTvrUpntvnvDRyNY9rvfEX/6E9M22igrqDzO/vWvwwUXNPRYhejpgYkTYeXK9dftsUf2Y0dPT/aKwCWXwO9/D6edBpVH/yVJkkZggq7uM306HHEEXHjh6LY7/ngTdGkYafp00vTpWaJa7VvfguXL4emns6T9T3+CP/yhmCDHo78/m4Zy003rl/3sZ/COd7TfO/aSJKkwJujqHqtWwemnw/nnZ3e2RuuGGxofk9QNNt8cLr103bI1a7rjzvK++2afv/kNvOlNhYYiSZLKzwRd3eO73x1dx3AVv/gFvO1tjY9H6mY9PfD972ePvlePE15rzPB66gxl7Vr45S/HFmOjbL45bLddsTFIkqS2YIKu7nHggfDRj9ZX9yMfyd6bldQcEVlHdf/4j43f99FHZ2PIt8oll8D222evz7zkJa07riRJ6jgm6Op8N9wAe+89um2+8Q34t3+DDTdsTkwanV//GhYurL/+4HG8ayxPWrEiW95ww5Hrw0BZreWRYhqprMbyxOXLs+VK52sN2OeY9nHmmdkTJTV0zTBrg7373QPzTz0FW2xRXCySJKmtmaCr81WSsNG6447RJ/ZqvGuvhbe+tSm73qApe208fyZqA7vuCgcfDJttVnQkkiSpjZmgq/O95S3Znc7+/qyjqkMPHXmb3XaD17ym6aGpDvvsA6eeCvffX1/9Ou6cV6xaswZSYnKls7KR7ryPVkq19zG4bJjl1atXZ3f8qztVG+c+m7GP1fn1nDRxYt3bNDyuefPW37bZDjwQrryy9ceVJEkdxwRdnW/RIpgxo/7606fDrbc2Lx6NTk8PnHhiU3b9fF8fAJMHDwvWavPnw223Zcn8ENOaFSsggkkbbbT+ehh6fnCnakPVHar+OLZdlT+KP2natNr7HuoThv8hZDTrikjQf/az7Fw22yz7t+anP4Vtt219HJIkqe2ZoKvz/e53o6v/3//dnDikoTzzDOy++7BV2uVR/I1GrtLZnn46my65pP4OKSVJkqqYoKvzvelNsMMO8NBD9dVfvLi58UjVNt00G2rsl7/M7gYPnoBVq1Zlj+JPnJgNG1a1bsj56rvKY1k/eF31+mHWrVmzBoCJPT21tx0plrGcxx13DHOBW+TTn4aPfSyLaZttio5GkiS1KRN0db5nnqk/OQc4/PDsc++94YwzYM89mxKW9IIjjsimGkrzKP4Iludx9rYyzlWrYMqU1h2vln//d5g2DXbaKfvcf3+YMKHoqCRJUpvx24M634tfnN3VWrsWvvOd+re7/vphkyZJw5g9u+Y79Q2dypCcV5x0Ehx2WNZp3Be+UHQ0kiSpDZmgq3u8733wz/9cX90ttoArrijHo7NSO5o6tegIinXyydkPCH/7t0VHIkmS2ogJurrDihVw/vn11U0JnnoK3vEOKPkjxVJpfe97Q79TX5Kpb+lS+pYuzZavu6551+GXv2zeviVJUscxQVd3ePDB+utecEHz4pBUPtttBxtu2Lj9/eM/wnPPZcm/nU5KkqRRMEFXd9h55/rrPvxw08KQVEIzZmQJ9cUXj28/hxwCa9bA97/f2IRfkiR1DXtxlwZ797uLjkBSEd7znnWHdhusrw9Wr87eLYeBzidTgo02yiZJkqRxMEFX57vrLvjyl+uvv+OO6y6/6U3wm980NiZJ7cc+KSRJUpOZoKvzvfa149v+gx9sTBySJEmSNAwTdHW+ffeFa64Zud5wj7ZKkiRJUpPZSZw6349/DLvuOnydf/mXloQiSZIkSbV4B13t44EHYO7cgeVKR021liEb3/i3vx1531/4ApxyyvjikyRJkqRxMEFXaU287DI2POqo1h3w+edh6tTWHU+SJEmSqviIu0orbbVVaw+4wQbwjW/4LrokSZKkQpigq7T699qLvqVLs4R5vNPy5fUd9KMfhQk2C0mSJEmtZyai7vDDHxYdgSRJkiQNywRd3eEv/mJ09SPg/vubE4skSZIkDcEEXZ3viSdGn6AD3H1342ORJEmSpBrsxV2d64Yb4JZb4Oab4cknR7/9YYfBPffAlCnwspcNPYxbF4iIh4FlQD+wJqU0KyI2B34EbA88DByeUno6IgL4OnAQsBz4+5TSrUXELUmSJLUbE3R1piVLYO+9x7+fnXce/z7qddNN0Nub/RCQ9yQ/4dlns3WbbAIvf3mRPxK8JaX0VNXy8cDVKaXTI+L4fPk44EBgZj7tCZyZf0qSJEkagQm6OtPmm8NFF8E112TL1YntxInZBLBiRdZr+9ln19/Te7Psscd6RdOqF774RfjsZ1sWzggOBvbN588FriFL0A8GzkspJeCGiNg0IqanlB6rtaP+/n76+vqaHO7QijruaBln47VLrO0SpyRJagwTdHWuww7Lpnp885vZ5803w2NVuWQlsa8eG71yhzslWLMGVq+GD38Ynqq+wdwEf/d3zd1/bQn4RUQk4HsppbnAVlVJ9+NAZdD6bYBHq7ZdmJetk6BHxBxgDsC2227bxNAlSZKk9mGCrvbzm9/Av/7r+PezdCncdtv499NEacIElj35JL1bbFFkGG9KKS2KiBcD8yJine7tU0opT97rlif5cwFmzZqVent7GxftGBR9/HoZZ+O1S6ztEqckSRofE3SV3623DtydPuMM+PnPi42nhZ696y6YNKnQGFJKi/LPJyPiJ8AewBOVR9cjYjpQ6YVvEVB9S3xGXiZJkiRpBCbo7Wb1ali1KntvuvKYdWWC1pWtXQuLFsG++zbtVLv+ftF++5GKvXNORGwETEgpLcvn9wdOAS4HZgOn55+X5ZtcDnwoIi4k6xxu6XDvn0uSJEkaYILebiZPLjqC8nnb27Lez9euhRNPhG23zX7AiBj9Z9mGUiu+g6itgJ9ko6cxEfhhSunnEXEzcFFEHAM8Ahye17+SbIi1BWTDrB3d+pAlSZKk9mSC3m5OPBG++tXsTvqaNUVHU6zNNoP/+z949auLjqRjpZQeBF43RPliYL8hyhNwbAtCkyRJkjrOhKID0Cidemo2HNjq1dmj5h/6UNERjd0DD2SP61d+bOjvz+6C54/T9y1dSt/Spes/Zl+ZliwxOZckSZLUMbyD3u5OPBFuuGHd5Hbt2nWn55+HZ57J6sBAeSUpLsrMmbXX7borU/bfP5ufMmXg0fMIOPRQ2GWX5scnSZIkSS1kgl5Wa9cy5bOfhXPOyXrxnjgRnn66cfvv7YXZs7NE/T//s3H7bZTbb2fK7bcPve7zn193XHJJkiRJ6gAm6GX0q1/Ru1/V673PP9/4Y/T1wSWXZIn/9OkDHaRVd5j2yCONP+4oPH/CCQBMnTJl3UfbDz200LgkSZIkqRlM0It2+eVw8MGtP+4WW8DLX75uWcS6d6Zf8pL1t6vnznWlzuD91bs+rzPpyisHfjCo9tOfjryP6vLB88PF0ape3IeKr/oVhTVrYM0apu6zD89/+cutiUmSJElSoUzQi/bKVxZz3MWLs6nEeooOoAQm//73rPzwh2HLLYsORZIkSVKTmaAXbccdh7wD3JePf93b27v+NmUbq3u0DjkE3ve+bJi06kfrqyfgueXLAdhoo43WPefqDuMGlw033yhjvTM/0tMH1WOyT5wIkyaxbNIkksm5JEmS1BVM0NvR/vvDL35RdBRjd+ml2TSCjZoeyCjcey9su23tHxRq/Mgw3h8IUv5DjSRJkqTOZ4Lejq66Krsbu3p1No74ypVDD69WPTVj/bHHwkMPFX01WmOnnQo57Ab778+KH/2okGNLkiRJai0T9HYVAZMnZ9O0acXE8OCDtdetXQtz58Kjj67bM/yECevOV39W33kGns97r586dWpWMNLd6OHW11qXUnYNq3uJr54qdUY7nXzy8LHWadIvfsGkzTbLFn7yk+z1AEmSJEkdyQRdzTFhAnzgA+Paxar88e6pQ72HX3YnnbR+2Ze+BMcfP/Z9/uAHJuiSJElSB5swchVJDXHccdm77EMNXzeMVUcdld2V//GPmxSYJEmSpDLwDrrUSq9+NTz2GPz5z7BiRZZ4T5y4bo/2a9dmj91PnPhCb/6TCw5bkiRJUvOZoEtFeNGLio5AkiRJUsn4iLskSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJWCCLkmSJElSCZigS5IkSZJUAibokiRJkiSVgAm6JEmSJEklYIIuSZIkSVIJmKBLkiRJklQCJuiSJEmSJJWACbokSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJTBigh4RZ0fEkxFxd1XZ5hExLyIeyD83y8sjIr4REQsi4s6IeH3VNrPz+g9ExOzmnI4kSZIkSe2pnjvo5wAHDCo7Hrg6pTQTuDpfBjgQmJlPc4AzIUvogZOAPYE9gJMqSb0kSZIkSYKJI1VIKV0bEdsPKj4Y2DefPxe4BjguLz8vpZSAGyJi04iYntedl1JaAhAR88iS/guGO3Z/fz99fX31nktH6dbzruY18BpIkiRJ3WSs76BvlVJ6LJ9/HNgqn98GeLSq3sK8rFb5eiJiTkTMj4j5ixcvHmN4kiRJkiS1lxHvoI8kpZQiIjUimHx/c4G5ALNmzUq9vb2N2nVb6vbzB68BeA0kSZKkbjDWO+hP5I+uk38+mZcvAratqjcjL6tVLkmSJEmSGHuCfjlQ6Yl9NnBZVflReW/uewFL80fhrwL2j4jN8s7h9s/LJEmSJEkSdTziHhEXkHXytmVELCTrjf104KKIOAZ4BDg8r34lcBCwAFgOHA2QUloSEV8Abs7rnVLpME6SJEmSJNXXi/uRNVbtN0TdBBxbYz9nA2ePKjpJkiRJkrrEWB9xlyRJkiRJDWSCLklSF4iIsyPiyYi4u6ps84iYFxEP5J+b5eUREd+IiAURcWdEvL5qm9l5/QciYvZQx5IkSWNjgi5JUnc4BzhgUNnxwNUppZnA1fkywIHAzHyaA5wJWUJP1hfNnsAewEmVpF6SJI3fuMdBlyRJ5ZdSujYith9UfDBZR7AA5wLXAMfl5eflfcvcEBGb5sOq7gvMq3T0GhHzyJL+C4Y7dn9/P319fY05EWjovlrBeJuv3WJut3gltY530CVJ6l5b5cOhAjwObJXPbwM8WlVvYV5Wq3w9ETEnIuZHxPzFixc3NmpJkjqUd9AlSRIppRQRqYH7mwvMBZg1a1bq7e1t1K5f0Ix9NpPxNl+7xdxu8UpqPu+gS5LUvZ7IH10n/3wyL18EbFtVb0ZeVqtckiQ1gAm6JEnd63Kg0hP7bOCyqvKj8t7c9wKW5o/CXwXsHxGb5Z3D7Z+XSZKkBvARd0mSukBEXEDWyduWEbGQrDf204GLIuIY4BHg8Lz6lcBBwAJgOXA0QEppSUR8Abg5r3dKpcM4SZI0fibokiR1gZTSkTVW7TdE3QQcW2M/ZwNnNzA0SZKU8xF3SZIkqQNExNkR8WRE3F1VtnlEzIuIB/LPzfLyiIhvRMSCiLgzIl5ftc3svP4DETF7qGNJag4TdEmSJKkznAMcMKjseODqlNJM4Op8GeBAYGY+zQHOhCyhJ3sFZk9gD+CkSlIvqfl8xF2SJEnqACmlayNi+0HFB5P1PwFwLnANcFxefl7+SssNEbFpPprDvsC8Sv8SETGPLOm/YLhj9/f309fXt175UGVlYnzjV/YYyx7fYN5BlyRJkjrXVvkoDACPA1vl89sAj1bVW5iX1SpfT0TMiYj5ETF/8eLFjY1a6lLeQZckSZK6QEopRURq4P7mAnMBZs2alXp7e2vWHW5dGRjf+JU9xrLHV+EddEmSJKlzPZE/uk7++WRevgjYtqrejLysVrmkFjBBlyRJkjrX5UClJ/bZwGVV5UflvbnvBSzNH4W/Ctg/IjbLO4fbPy+T1AI+4i5JkiR1gIi4gKyTty0jYiFZb+ynAxdFxDHAI8DhefUrgYOABcBy4GiAlNKSiPgCcHNe75RKh3GSms8EXZIkSeoAKaUja6zab4i6CTi2xn7OBs5uYGiS6uQj7pIkSZIklYAJuiRJkiRJJWCCLkmSJElSCZigS5IkSZJUAibokiRJkiSVgAm6JEmSJEklYIIuSZIkSVIJmKBLkiRJklQCJuiSJEmSJJWACbokSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJWCCLomIODsinoyIu6vKNo+IeRHxQP65WV4eEfGNiFgQEXdGxOurtpmd138gImYXcS6SJElSuzJBlwRwDnDAoLLjgatTSjOBq/NlgAOBmfk0BzgTsoQeOAnYE9gDOKmS1EuSJEka2cSiA5BUvJTStRGx/aDig4F98/lzgWuA4/Ly81JKCbghIjaNiOl53XkppSUAETGPLOm/YLhj9/f309fX15gTGaWijjtaxtl47RJru8QpSZIawzvokmrZKqX0WD7/OLBVPr8N8GhVvYV5Wa3y9UTEnIiYHxHzFy9e3NioJUmSpDblHXRJI0oppYhIDdzfXGAuwKxZs1Jvb2+jdj0mRR+/XsbZeO0Sa7vEKUmSxsc76JJqeSJ/dJ3888m8fBGwbVW9GXlZrXJJkiRJdTBBl1TL5UClJ/bZwGVV5UflvbnvBSzNH4W/Ctg/IjbLO4fbPy+TJEmSVAcfcZdERFxA1snblhGxkKw39tOBiyLiGOAR4PC8+pXAQcACYDlwNEBKaUlEfAG4Oa93SqXDOEmSJEkjM0GXRErpyBqr9huibgKOrbGfs4GzGxiaJEmS1DV8xF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRGTNAjYtuI+HVE3BsR90TER/PyzSNiXkQ8kH9ulpdHRHwjIhZExJ0R8fqqfc3O6z8QEbObd1qSJEmSJLWXeu6grwE+mVLaCdgLODYidgKOB65OKc0Ers6XAQ4EZubTHOBMyBJ64CRgT2AP4KRKUi9JkiRJUrebOFKFlNJjwGP5/LKIuA/YBjgY2Devdi5wDXBcXn5eSikBN0TEphExPa87L6W0BCAi5gEHABfUOnZ/fz99fX1jOrF2163nXc1r4DWQJEmSusmo3kGPiO2B3YAbga3y5B3gcWCrfH4b4NGqzRbmZbXKBx9jTkTMj4j5ixcvHk14kiRJkiS1rRHvoFdExDTgx8DHUkp9EfHCupRSiojUiIBSSnOBuQCzZs1Kvb29jdht2+r28wevAXgNJEmSpG5Q1x30iJhElpyfn1K6JC9+In90nfzzybx8EbBt1eYz8rJa5ZIkSZIkdb16enEP4CzgvpTSV6tWXQ5UemKfDVxWVX5U3pv7XsDS/FH4q4D9I2KzvHO4/fMySZIkSZK6Xj2PuO8DvA+4KyJuz8tOAE4HLoqIY4BHgMPzdVcCBwELgOXA0QAppSUR8QXg5rzeKZUO4yRJkiRJ6nb19OJ+HRA1Vu83RP0EHFtjX2cDZ48mQEmSJEmSusGoenGXJEmSJEnNYYIuiYg4OyKejIi7q8pOjohFEXF7Ph1Ute6zEbEgIn4XEW+vKj8gL1sQEce3+jwkSZKkdmaCLgngHOCAIcrPSCntmk9XAkTETsARwM75Nt+JiJ6I6AG+DRwI7AQcmdeVJEmSVIe6x0GX1LlSStdGxPZ1Vj8YuDCltBJ4KCIWAHvk6xaklB4EiIgL87r3NjpeSZIkqROZoEsazoci4ihgPvDJlNLTwDbADVV1FuZlAI8OKt9zpAP09/fT19fXoHBHp6jjjpZxNl67xNoucUqSpMbwEXdJtZwJvBzYFXgM+EqjdhwRcyJifkTMX7x4caN2K0mSJLU176BLGlJK6YnKfER8H7giX1wEbFtVdUZexjDlg/c9F5gLMGvWrNTb29ugqMem6OPXyzgbr11ibZc4JUnS+HgHXdKQImJ61eLfAJUe3i8HjoiIKRGxAzATuAm4GZgZETtExGSyjuQub2XMkiRJUjvzDrokIuICYF9gy4hYCJwE7BsRuwIJeBj4J4CU0j0RcRFZ529rgGNTSv35fj4EXAX0AGenlO5p7ZlIkiRJ7csEXRIppSOHKD5rmPqnAacNUX4lcGUDQ5MkSZK6ho+4S5IkSZJUAibokiRJkiSVgAm6JEmSJEklYIIuSZIkSVIJmKBLkiRJklQCJuiSJEmSJJWACbokSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkdbiI2DYifh0R90bEPRHx0bx884iYFxEP5J+b5eUREd+IiAURcWdEvL5qX7Pz+g9ExOyizkmSpE5kgi5JUudbA3wypbQTsBdwbETsBBwPXJ1SmglcnS8DHAjMzKc5wJmQJfTAScCewB7ASZWkXpIkjd/EogOQJEnNlVJ6DHgsn18WEfcB2wAHA/vm1c4FrgGOy8vPSykl4IaI2DQipud156WUlgBExDzgAOCC4Y7f399PX19fw86nkftqBeNtvnaLud3ildQ63kGXJKmLRMT2wG7AjcBWefIO8DiwVT6/DfBo1WYL87Ja5UMdZ05EzI+I+YsXL27cCUiS1MG8gy5JUpeIiGnAj4GPpZT6IuKFdSmlFBGpUcdKKc0F5gLMmjUr9fb2NmrXL2jGPpvJeJuv3WJut3glNZ930CVJ6gIRMYksOT8/pXRJXvxE/ug6+eeTefkiYNuqzWfkZbXKJUlSA5igS5LU4SK7VX4WcF9K6atVqy4HKj2xzwYuqyo/Ku/NfS9gaf4o/FXA/hGxWd453P55mSRJagAfcZckqfPtA7wPuCsibs/LTgBOBy6KiGOAR4DD83VXAgcBC4DlwNEAKaUlEfEF4Oa83imVDuMkSdL4maBLktThUkrXAVFj9X5D1E/AsTX2dTZwduOik9QIEbEtcB5ZZ48JmJtS+no+POKPgO2Bh4HDU0pP50/WfJ3sx7jlwN+nlG7N9zUb+Fy+61NTSue28lykbuYj7pIkSVL7WwN8MqW0E7AXcGxE7AQcD1ydUpoJXJ0vAxwIzMynOcCZAHlCfxKwJ7AHcFL+SoukFvAOuiRJktTm8n4iHsvnl0XEfWTDIB4M7JtXOxe4BjguLz8vf2LmhojYNO8scl9gXuX1lYiYBxwAXDDc8fv7+4cc373sY74b3/iVPcayxzeYd9AlSZKkDhIR2wO7ATcCW+XJO8DjZI/AQ5a8P1q12cK8rFb5UMeZExHzI2L+4sWLG3cCUhfzDrokSZLUISJiGtmQih9LKfVlr5pnUkopIlKjjpVSmgvMBZg1a1Yablz3so/5bnzjV/YYyx5fhXfQJUmSpA4QEZPIkvPzU0qX5MVP5I+uk38+mZcvArat2nxGXlarXFILmKBLkiRJbS7vlf0s4L6U0lerVl0OzM7nZwOXVZUfFZm9gKX5o/BXAftHxGZ553D752WSWsBH3CVJkqT2tw/wPuCuiLg9LzsBOB24KCKOAR4BDs/XXUk2xNoCsmHWjgZIKS2JiC8AN+f1Tql0GCep+UzQJUmSpDaXUroOiBqr9xuifgKOrbGvs4GzGxedpHr5iLskSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJWCCLkmSJElSCZigS5IkSZJUAibokiRJkiSVgAm6JEmSJEklYIIuSZIkSVIJmKBLkiRJklQCJuiSJEmSJJWACbokSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJWCCLkmSJElSCZigS5IkSZJUAibokiRJkiSVgAm6JEmSJEklYIIuSZIkSVIJmKBLkiRJklQCJuiSJEmSJJWACbokSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJWCCLkmSJElSCZigS5IkSZJUAibokiRJkiSVgAm6JEmSJEklYIIuSZIkSVIJmKBLkiRJklQCJuiSJEmSJJWACbokSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJWCCLkmSJElSCZigS5IkSZJUAibokiRJkiSVgAm6JEmSJEklYIIuSZIkSVIJmKBLkiRJklQCJuiSiIhtI+LXEXFvRNwTER/NyzePiHkR8UD+uVleHhHxjYhYEBF3RsTrq/Y1O6//QETMLuqcJEmSpHZjgi4JYA3wyZTSTsBewLERsRNwPHB1SmkmcHW+DHAgMDOf5gBnQpbQAycBewJ7ACdVknpJkiRJw5tYdACSipdSegx4LJ9fFhH3AdsABwP75tXOBa4BjsvLz0spJeCGiNg0IqbndeellJYARMQ84ADgglrH7u/vp6+vrwlnNbKijjtaxtl47RJru8QpSZIawzvoktYREdsDuwE3AlvlyTvA48BW+fw2wKNVmy3My2qVDz7GnIiYHxHzFy9e3NgTkCRJktqUd9AlvSAipgE/Bj6WUuqLiBfWpZRSRKRGHCelNBeYCzBr1qzU29vbiN2OWdHHr5dxNl67xNoucUqSpPHxDrokACJiEllyfn5K6ZK8+In80XXyzyfz8kXAtlWbz8jLapVLkiRJGoEJuiQiu1V+FnBfSumrVasuByo9sc8GLqsqPyrvzX0vYGn+KPxVwP4RsVneOdz+eZkkSZKkEfiIuySAfYD3AXdFxO152QnA6cBFEXEM8AhweL7uSuAgYAGwHDgaIKW0JCK+ANyc1zul0mGcJEmSpOGZoEsipXQdEDVW7zdE/QQcW2NfZwNnNy46SZIkqTv4iLskSZIkSSVggi5JkiRJUgmYoEuSJEmSVAIm6JIkSZIklYAJuiRJkiRJJWCCLkmSJElSCZigS5IkSZJUAibokiRJkiSVgAm6JEmSJEklYIIuSZIkSVIJmKBLkiRJklQCJuiSJEmSJJXAiAl6REyNiJsi4o6IuCciPp+X7xARN0bEgoj4UURMzsun5MsL8vXbV+3rs3n57yLi7U07K0mSJEmS2kw9d9BXAm9NKb0O2BU4ICL2Ar4EnJFSegXwNHBMXv8Y4Om8/Iy8HhGxE3AEsDNwAPCdiOhp4LlIkiRJktS2Jo5UIaWUgGfzxUn5lIC3Au/Ny88FTgbOBA7O5wEuBr4VEZGXX5hSWgk8FBELgD2A62sdu7+/n76+vtGdUYfo1vOu5jXwGkiSJEndpK530COiJyJuB54E5gF/AJ5JKa3JqywEtsnntwEeBcjXLwW2qC4fYpvqY82JiPkRMX/x4sWjPiFJkiRJktrRiHfQAVJK/cCuEbEp8BNgx2YFlFKaC8wFmDVrVurt7W3WodpCt58/eA3AayBJkiR1g1H14p5Segb4NbA3sGlEVBL8GcCifH4RsC1Avn4TYHF1+RDbSJIkSZLU1erpxf1F+Z1zImID4G3AfWSJ+qF5tdnAZfn85fky+fpf5e+xXw4ckffyvgMwE7ipQechSZIkSVJbq+cR9+nAuXmP6xOAi1JKV0TEvcCFEXEqcBtwVl7/LOAHeSdwS8h6bieldE9EXATcC6wBjs0fnZckSZIkqevV04v7ncBuQ5Q/SNYL++Dy54HDauzrNOC00YcpSZIkSVJnG9U76JIkSZIkqTlM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSukBETI2ImyLijoi4JyI+n5fvEBE3RsSCiPhRREzOy6fkywvy9dtX7euzefnvIuLtBZ2SJEkdxwRdkqTusBJ4a0rpdcCuwAERsRfwJeCMlNIrgKeBY/L6xwBP5+Vn5PWIiJ2AI4CdgQOA70RETytPRJKkTjWx6AAkSVLzpZQS8Gy+OCmfEvBW4L15+bnAycCZwMH5PMDFwLciIvLyC1NKK4GHImIBsAdwfa1j9/f309fX17BzaeS+WsF4m6/dYm63eCW1jnfQJUnqEhHRExG3A08C84A/AM+klNbkVRYC2+Tz2wCPAuTrlwJbVJcPsU31seZExPyImL948eImnI0kSZ3HO+iSJHWJlFI/sGtEbAr8BNixiceaC8wFmDVrVurt7W34MZqxz2Yy3uZrt5jbLV5JzecddEmSukxK6Rng18DewKYRUfnBfgawKJ9fBGwLkK/fBFhcXT7ENpIkaRxM0CVJ6gIR8aL8zjkRsQHwNuA+skT90LzabOCyfP7yfJl8/a/y99gvB47Ie3nfAZgJ3NSSk5BUkyM1SJ3BBF2SpO4wHfh1RNwJ3AzMSyldARwHfCLv7G0L4Ky8/lnAFnn5J4DjAVJK9wAXAfcCPweOzR+dl1QsR2qQOoDvoEuS1AVSSncCuw1R/iBZL+yDy58HDquxr9OA0xodo6SxK3KkBqg9WkPZe6w3vvEre4xlj28w76BLkiRJHaCVIzXkx3O0BqnBvIMuSZIkdYBWjtSQH6/u0RrK3mO98Y1f2WMse3wV3kGXJEmSOogjNUjtywRdkiRJanOO1CB1Bh9xlyRJktrfdODcvMf1CcBFKaUrIuJe4MKIOBW4jXVHavhB3gncErKe20kp3RMRlZEa1uBIDVJLmaBLIiK2Bc4DtiLr8XVuSunrEXEy8H7gz3nVE1JKV+bbfJZsiJZ+4CMppavy8gOArwM9wH+mlE5v5blIktSNHKlB6gwm6JIg+4X8kymlWyNiY+CWiJiXrzsjpfQf1ZUHjZG6NfDLiHhlvvrbZI/VLQRujojLU0r3tuQsJEmSpDZmgi6JlNJjwGP5/LKIuI8aQ6rkao2RCrAg/7WeiLgwr1szQa81bmortMu4mMbZeO0Sa7vEKUmSGsNO4iStIyK2J3tE7sa86EMRcWdEnB0Rm+VltcZIrWvsVMdNlSRJktbnHXRJL4iIacCPgY+llPoi4kzgC2TvpX8B+ArwD+M9zmjGTW2Foo9fL+NsvHaJtV3ilCRJ42OCLgmAiJhElpyfn1K6BCCl9ETV+u8DV+SLw42R6tipkiRJ0hj4iLskIiLIhlu5L6X01ary6VXV/ga4O5+vNUbqzcDMiNghIiaTdSR3eSvOQZIkSWp33kGXBLAP8D7groi4PS87ATgyInYle8T9YeCfYPgxUiPiQ8BVZMOsnZ1Suqd1pyFJkiS1LxN0SaSUrgNiiFVXDrPNkGOk5uOk19xOkiRJ0tB8xF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqgboT9IjoiYjbIuKKfHmHiLgxIhZExI8iYnJePiVfXpCv375qH5/Ny38XEW9v+NlIkiRJktSmRnMH/aPAfVXLXwLOSCm9AngaOCYvPwZ4Oi8/I69HROwEHAHsDBwAfCciesYXviRJkiRJnWFiPZUiYgbwDuA04BMREcBbgffmVc4FTgbOBA7O5wEuBr6V1z8YuDCltBJ4KCIWAHsA19c6bn9/P319faM8pc7QreddzWvgNZAkSZK6Sb130L8GfAZYmy9vATyTUlqTLy8EtsnntwEeBcjXL83rv1A+xDYviIg5ETE/IuYvXry4/jORJEmSJKmNjXgHPSLeCTyZUrolIvZtdkAppbnAXIBZs2al3t7eZh+y1Lr9/MFrAF4DSZIkqRvU84j7PsC7IuIgYCrQC3wd2DQiJuZ3yWcAi/L6i4BtgYURMRHYBFhcVV5RvY0kSZIkSV1txEfcU0qfTSnNSCltT9bJ269SSn8H/Bo4NK82G7gsn788XyZf/6uUUsrLj8h7ed8BmAnc1LAzkSRJkiSpjdXVSVwNxwEXRsSpwG3AWXn5WcAP8k7glpAl9aSU7omIi4B7gTXAsSml/nEcX5IkSZKkjjGqBD2ldA1wTT7/IFkv7IPrPA8cVmP708h6gpckSZIkSVVGMw66JEmSJElqEhN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEphYdABd55vfhI98pPb6T38aIpiycmW2PHXqwLqIdT8B1qyBf//3xsfZaHPmwDvfmcVePQHccgv09GTTmjXZtOGG8Pd/D5MnFxq2JEmSJLWKCXqrfe97w6//5jcBmAyQ0kB5ZX5w2Zo1DQ2vaebOzaZRmPzcc6z6+MebFJAkSZIklYsJeqvdfXdd1Zb19QHQ29s7cuXrr4cnn1y/vPpO+1BSyqZvfxt++cu64mqlqSefzNSTT84Wrr4aXvOadSsMPr9a51v9o8bgssHrhvpRZPDyS14y8rWVJEmSpFEyQe8Ee+9df92ZM2HBgubF0iz77Vd0BAM++Un4j/8oOgpJkiRJHcYEvdu85z3wpS8VHcXoTZ069Pvo1e+yV5cNNV/vuuHqTJgARx9dX8ySJEmSNAom6N3m9NOzqeKuu+DEE2HxYrj/flixAlauhLVrs/VTpmTLrXbjjfTtuCNQ52P+kiRJktTmTNC7yWtfmyXkozGa5HynnbK73BMmDEw9PevOV5YjsnmA3t6BdT098Dd/A3vsAfl7+JIkSZLUDUzQu8mqVc3d/6teBQcdtG5SXpmuvRZ++EM4+OAsIZ80qXbnbYsXD71OkiRJkjqYCXo3uf/+dZdTgv7+7HH2nXcef+dxP/lJNg3nBz+ob1+77w4vfen44pEkSZKkNjKh6ABUoAiYODF7LP2BBwaGXas1ffCDrYvtNa+hd5NN6N1kE/jc51p33C4VEVMj4qaIuCMi7omIz+flO0TEjRGxICJ+FBGT8/Ip+fKCfP32Vfv6bF7+u4h4e0GnJEmSJLUd76CrfmecAW98Y/ao/OrVA3ffV6+GG26Aiy5qznFPOw1OPbU5+1bFSuCtKaVnI2IScF1E/Az4BHBGSunCiPgucAxwZv75dErpFRFxBPAl4G8jYifgCGBnYGvglxHxypRSfxEnJUmSJLUTE/Rqd94Jr3td0VEA0NB+y3fYYWCIslp3x8eybnD55pvXt7/ly4eP953vhJ4eVuc/AEw67rhGXg0NIaWUgGfzxUn5lIC3Au/Ny88FTiZL0A/O5wEuBr4VEZGXX5hSWgk8FBELgD2A62sdu7+/n76COgQs6rijZZyN1y6xtkuckiSpMUzQqz3xRNERNMdDD41tu733hle/et3xwQdPtcqHW1fp0f2xx+Dcc9c95imnZI+0R7Ai/2I6yWHWWiIieoBbgFcA3wb+ADyTUlqTV1kIbJPPbwM8CpBSWhMRS4Et8vIbqnZbvU31seYAcwC23Xbbhp+LJEmS1I5M0Ku97W3ZHd4//Wng8e3Bd38Hl1WW166Fk04auZO0djJrFnzjG809xjnnNHf/qlv+GPquEbEp8BNgxyYeay4wF2DWrFmp6LHuiz5+vYyz8dol1naJU5IkjY8J+lC23job//v88+Hxx+HEE4uOqBhf+lLREagAKaVnIuLXwN7AphExMb+LPgNYlFdbBGwLLIyIicAmwOKq8orqbSRJkiQNo/sS9GuvhZtvHrnepz7V/FjKYost4MtfzuYr74/PmgUbbFBcTGqpiHgRsDpPzjcA3kbW8duvgUOBC4HZwGX5Jpfny9fn63+VUkoRcTnww4j4KlkncTOBm1p6MpIkSVKb6q4E/amn4C//sugoyuG1r4XeXpg0Cc47D2bMKDoiFWs6cG7+HvoE4KKU0hURcS9wYUScCtwGnJXXPwv4Qd4J3BKynttJKd0TERcB9wJrgGPtwV2SJEmqT3cl6Ftumb0j/pvfrL+ucuc4Yuj5p56CW27JlisdoKWUjR++Zs36+yu7N78ZvvnNoqNQSaSU7gR2G6L8QbJe2AeXPw8cVmNfpwGnNTpGSZIkqdN1V4IOcMgh2dQIF18Mhw2Zo5Tft76VTQC77AJ33VVsPJIkSZLU5SYUHUBbe9vb4F3vgpe9rOhIxqenp+gIJEmSJKnrdd8d9EbaZBP42tfaO0G/+27Yeeeio5AkSZKkrmeCPl733FN0BKPzkpfAY48VHYUkSZIkaRAT9PF65zuLjqC2adOyIdR23hn++Z9hwgTYe++io5IkSZIkDcEEfbyefhqeeCKbX7wYdtqp2HiqPftsNj3yCFx55ei23Xln+NWv4MUvbk5skiRJkqR1dF+CnhKccALMnZsNl1YZMm2o+eppqDp//GPr42+Ve+6BW2+FAw4oOhJJkiRJ6grdl6CvXg2nn150FOX0m9+s+wi8vbtLkiRJUst0X4I+eTKsWJE9+p1SVpZS7fm1awfmlyyBXXdtecgts/HGJuWSJEmSVJDOT9AXLx76/evKo+rVVq+G/v5s3aWXwhVXND28Qu26K7z5zfCVr8DEzv9TkCRJkqQy6/ysbK+9YMGCoqMop6VL4etfLzoKSZIkSRLdkKBfeun675xXHmGvXl6zBi66qGVhlcLUqUVHIEmSJEnKdX6CvvPO8IMf1Ff3Rz9ad3nDDbP31cvkwgvhb/+26CgkSZIkSQ3W+Qn6eDz3XNYx3PLl2TvaPT3rD7UGAx3LpQRbbgkTJoz70H19fQD09vaOe1+SJEmSpPIzQR9OBGyxRTZJkiRJktRE47/VK0mSJEmSxs0EXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSukRE9ETEbRFxRb68Q0TcGBELIuJHETE5L5+SLy/I129ftY/P5uW/i4i3F3QqkiR1JBN0SZK6x0eB+6qWvwSckVJ6BfA0cExefgzwdF5+Rl6PiNgJOALYGTgA+E5E9LQodkmSOt7EogOQJEnNFxEzgHcApwGfiIgA3gq8N69yLnAycCZwcD4PcDHwrbz+wcCFKaWVwEMRsQDYA7h+uGP39/fT19fXsHNp5L5awXibr91ibrd4JbWOd9AlSeoOXwM+A6zNl7cAnkkprcmXFwLb5PPbAI8C5OuX5vVfKB9im3VExJyImB8R8xcvXtzA05AkqXN5B12SpA4XEe8Enkwp3RIR+7bimCmlucBcgFmzZqXe3t6GH6MZ+2wm422+dou5GfHmr53MBxallN4ZETsAF5L9yHYL8L6U0qqImAKcB7wBWAz8bUrp4XwfnyV71aUf+EhK6aqGByppSN5BlySp8+0DvCsiHib7ov5W4OvAphFR+bF+BrAon18EbAuQr9+E7Av8C+VDbCOpHOxrQmpjJuiSJHW4lNJnU0ozUkrbk33x/lVK6e+AXwOH5tVmA5fl85fny+Trf5VSSnn5EXkv7zsAM4GbWnQakkZQ1dfEf+bLlb4mLs6rnAscks8fnC+Tr99vcF8TKaWHgEpfE5JawEfcJUnqXscBF0bEqcBtwFl5+VnAD/JO4JaQJfWklO6JiIuAe4E1wLEppf7Why2phq+R9TWxcb5cd18TEVHd18QNVfus2ddEtVqdQZa9QzzjG7+yx1j2+AYzQZckqYuklK4BrsnnH2SIO2MppeeBw2psfxpZT/CSSqSIviYiYg4wB2DbbbcdobakepigS5IkSe2v0tfEQcBUoJeqvibyu+hD9TWxcKx9TYymM8iyd+BnfONX9hjLHl+F76BLkiRJbc6+JqTO4B10SZIkqXPZ14TURkzQJUmSpA5iXxNS+/IRd0mSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF2SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgETdEmSJEmSSsAEXZIkSZKkEjBBlyRJkiSpBEzQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrABF0SETE1Im6KiDsi4p6I+Hxefk5EPBQRt+fTrnl5RMQ3ImJBRNwZEa+v2tfsiHggn2YXdEqSJElS25lYdACSSmEl8NaU0rMRMQm4LiJ+lq/7dErp4kH1DwRm5tOewJnAnhGxOXASMAtIwC0RcXlK6emWnIUkSZLUxupK0CPiYWAZ0A+sSSnNyr+I/wjYHngYODyl9HREBPB14CBgOfD3KaVb8/3MBj6X7/bUlNK5jTsVSWOVUkrAs/nipHxKw2xyMHBevt0NEbFpREwH9gXmpZSWAETEPOAA4IJaO+rv76evr2/8JzEGRR13tIyz8dol1naJU5IkNcZoHnF/S0pp15TSrHz5eODqlNJM4Op8Gda9szaH7M4aVXfW9gT2AE6KiM3GfwqSGiEieiLiduBJsiT7xnzVaflj7GdExJS8bBvg0arNF+ZltcoHH2tORMyPiPmLFy9u9KlIkiRJbWk8j7gfTHa3DOBc4BrgODrkzlrRuvW8q3kNWnsNUkr9wK4RsSnwk4jYBfgs8DgwGZhL1sZPacCx5ub7Y9asWam3t3e8uxyXoo9fL+NsvHaJtV3ilCRJ41PvHfQE/CIibomIOXnZVimlx/L5x4Gt8nnvrEltLKX0DPBr4ICU0mMpsxL4L7KnXwAWAdtWbTYjL6tVLkmSJGkE9d5Bf1NKaVFEvBiYFxH3V69MKaWIGO591bqV7c5a0br9/MFrAM2/BhHxImB1SumZiNgAeBvwpYiYnlJ6LO9b4hDg7nyTy4EPRcSFZK+tLM3rXQV8ser1lf3J7sJLkiSpWyxaBJ//fDZ/4YWwbFlzjvOSl8CGG65f/qIXwU9+AtOnN+e4TVRXgp5SWpR/PhkRPyG7i/ZE1Zf36WTvrcLwd9b2HVR+zbiil9Qo04FzI6KH7Mmai1JKV0TEr/LkPYDbgQ/k9a8k6whyAVlnkEcDpJSWRMQXgJvzeqdUXmuRJElSG1q+HL74RVixYsjVU1atymb+/Gf43/+FlOCJJ1oT2+OPD13+4INw2WXwgQ8Mvb7ERkzQI2IjYEJKaVk+vz/ZO6iXA7OB0/PPy/JNvLMmtZmU0p3AbkOUv7VG/QQcW2Pd2cDZDQ1QkiRJxTjsMLjyypqrp9Rc0wLz5sEOO6xfPnEibLdd6+NpgHruoG9F1mFUpf4PU0o/j4ibgYsi4hjgEeDwvL531iRJkiSp3f32t8Mm54VbswZe/vKio2ioERP0lNKDwOuGKF8M7DdEuXfWJEmSJKkdLVkCRx2VPaY+f37R0cDvfw8zZxYdRcuMZ5g1SZIkSVK9UhqY1q4def6ZZ7LP1asHyuvZbqT5Rx+Fd7yj6KtRn1e+sr56V1zRPuc0DBN0SZIkSfrRj+CII4qOYh2OZTQKTz45cp02YIIuSZIkSQsWFB1B90gNGaG7I5mgS5IkSdKJJ2bTcO69Fy64YCDBfPhhuOkm6OmBN78Z/uEfIGLdCYZfHqbOs889BxFM23jjUW3Xkjp5Wd+yZRBBb2/vQJ3K5x//mF2zRYugtxcmT4bXv76+/x5dygRdkiRJkuqx8861191/P8yd29DDTWvo3pqjIY/h//a3sMce6/8g0IVM0CVJkiSpHvffn72rXkkgly6FhQuz4b523BH23DPriK0yVXfONtTyCHVWLF9OpMTUyZPXr1PPZ63916rzy1/CAw+0/rq+8Y3rl+2yC9x1V+tjKZgJuiRJkqTO19cHm2yyTlHZO2HboOgAivSZzxQdQSFM0CVJkiR1vg02gAMPhJ/9rOhIupsdxA3LBF2SJElS55s0Ca68cp2ivr4+gIEOzkqmIfEtXAi77bb+o/XLljUoykH6+tZ9l3zSpKwTvQkTmnO8DmOCLkmSJEmdasMN4bDDsgS5MkXA73+/3g8W4/LiF8PnPgeVHuc1JibokiRJktSpNt8cvvOd8e3jwQfh7ruzu+FTp2afEydCTw/Prlix7lBwt922fid41ctDlQ1VZ+1aWLUKjjhi/NegjZigS5IkSVI3+/zn4eSTx7RpU4eCmzQJDjooG0O9S5igS5IkSVI3++Mfm7fvU07Jhp+rfrx+8OP21cvVZVtu2VXJOZigS5IkSVJ3O+usbBqDsne0125M0CVJkiRJQ0sJLroI/vzn7PPeewfKU2LjtWvXrV/dg/uECTBnDhxzzPrl1cuQ9f5e2b63F6ZPb905logJuiRJkiRpaOefD+97X83VMdL2X/xiNo3WTTfB7ruPfrs2Z4IuSZIkSRra3/5t1ov7k09md81h4K73hAmsXL0agCmTJ2dl+Z31F6YddoAttoD+/tpTXx+cdtrAMffdF3bZpXXnWCIm6JIkSZKkoU2aBP/6rzVXr8wfTZ9S/Q76889nifnjj4/tmNdck43fPpSjjoL99htY3nFH2GOPsR2nhEzQJUmSJEmN89BDY0/OR3LeedlU7SUvyX4QGCwlNuzvz+YnThx4AqDa/vvDSSdl78WXgAm6JEmSJGnMppx2Gnz5y8UF8PjjNX8QGDHhveEGeP/7YcaMhoc1FibokiRJkqQxW7P//kwpIkHffHOYNg16erJp6lT4zGeysry3+OXPPw8RbLjhhuuOs17pTX6bbbLx1letGrqX+RYzQZckSZIkjVn/7rsP/fj4UJ57Dv7hH+Cee7JpPJYsyaZqRx21zmKNN9nr89OfwkEHjWcPo2aCLkmSJElqjd/8JhtPvexe+Up4/etbflgTdEmSJElSc9x2G/zVX2V32Neurf9Oe7O86EXZkHElZYIuSZIkSWqOLbaAI49c993uwe+Br14NZ5+dfVaklA3XVsuee8LMmfDd78JGG9Ws1pcPA9dbPQxciZmgS5IkqTn+4z9g8mTYYIOBL+KDv6DXUzbC+p7ly7PljTfOypYuhT/8AVasyIZfOuKIbCxnSa330pfCt741cr0zzmh+LG3ABF2SJKnbPPAAHHBA1mvxxIkDPSD39LARZEluT8/AHa5aU6VurXX/938tOZ3a985ygzqNGrfTT4dDD81+EHjxixu7b0ldzQRdkiSpGyxbNvDe5WmnwYMPDlmtp4Uhta3jj8+miltvhd12Ky4eqV1cdx38xV/UXr/LLtl76v392bR2LVx7bTYUWpcwQZckSeoUDz44MORQSgOdMaUEe+1VXFydbrPNio5Aag8jjSs+c2b29M6ECQOfkye3JraSMEGXJEnqBDfeaBLeSg8/DNttV3QUUjmkBF/5Ctx000DZ4GS8snzEEcOvH7z88Y+vvz4leMUrYPr0gd7hKz3ED5qfvHw5U047Df7lX+BznxvfebaACbokSVIneN3r4B//MXvcevC74FB7HrIvszff3Jo429m8ebByZdbplcm59IIJv/89fOpTRYcxpKmVGRN0SZIktczUqfD9749t2/7+bJiilSsbG1Mned/7srGcJa1n7atelT3FM7hvi8FjnjdqOQJe9SqYMSN7DP7GG+GQQ0YO9LjjYPPNs8fnDz44e6S+ZEzQJUmSul1PzwvjDdc9ZvC118LHPjbQkVN//7rrq99/H035WLZ/+OHhY22EH/wgm8Zi773ht79tbDxS2eyxRzYV4Ze/rK/el788MP/pT6//70sJmKBLkiRp9N785uxx+qI9/jj9++1Hz733Fh1JbSP92CFpfA45BJ54YqBzzNtvh8cfh+eeG367kTqtg2yYxrlzYcqURkQ6IhN0SZIkjc3SpfDhD0Nf38A77xMmrPsO/IQJA2WVz9tvhzvvbFgYhQ4Nt/322dBRXTQMlFQajz+ePZ3ynvc07xjnnQezZmX/1rWACbokSZLG5rvfHftj32X2wQ/CKafAllsWHYmkWn78Yzj00NYca/ArPE1kgi5JkqTscfU3vIGuehj7e9+DOXOKjkLqXqtXw847wwMPFB1JbeefD+99b8sOZ4IuSZLUqfr64L77skfLn34a3v722nUnT25dXM10xx1DP1o/YUK2PiWYODHr9X769GJjlbrd2rXlSM432WRgDHUYeJf9iivgLW9paSgm6JIkSZ1qyy2zO1T1WLWqubG0wgknwGtfW3QUUjn94Q9w4YXZfKVztJTgi1+E5cvHvNuOeOrmbW/LPj/2Mdhnn0JDMUGXJEnqVJddBiedlN0VSmmg47aU4JZb1q8/dSopH3YoKneQYP27SpX5svniF7OpXpttlj3av+mmA9dogw1gww2bFqJUmFe/uv4f7LrNxRcPfBb8b5sJuiRJUqc68MBsGuyPf4Tttlu//PnnqWPQoc7x9NOwww7rly9caK/s7eqKK+CGGwaWq39UqixXmbJqVfajVWUIrcHDblUvV+aHq1NZrqdOdSzV+95iixdinVS5sz116sC53HxzZ3bO2GhbbQXf/CbL82u4YT0/vP3FXzQ5qJGZoEuSJHWbl74U/t//y77oVzzzTDbWb6eofge9kvwMHgJuqKHhDj4YXvziYmPvRG9+M/zmN0VHsZ7WjGw9dhsUHcBIPvxhVq5eDRFMmTJl3fZ27bUwf35r43nJSwbmf/5zeN3rWNPXly33tsfD+CbokiRJ3ejQQ9cfouh736Mv/zLbO5Yvs298I1x/fQOCa4C1a7PpxBPXvTu5wQbw8Y9ndyTVOu98ZykT9I72spfBlVdCT8/AD1YTJmTL1WWDf6Sq9eNVjbKVy5YBMKVNEuCyM0GXJEnSyJ57Do48Ev7v/9YtX7KkmHjqddpp65ctXw5f+ELrY+lmn/lMNlWsXZu9/79mTTbGdH//uvOVH1hSgj/9CT7wgdEf85BD4NJLG3UG7efBB2HHHZt+mF4g1Zvc15n01yxbujSbRhnfqLzqVfC732XzPT3ZMHBveEN2/K22yn6IfOc7R7vXupmgS5IktbtvfhM+8pGG7Kor7oH9+Mfw059m85X3equnisHlZ5wBBxxQTMydZsIEmDWr/vr/9E9jO05KWeJf479z39KlkBK9G2889N/BUNuNZ/1PfgL33jv03xnAi14Ef/mXL5Qtf+45WLuWDTfYYN39VH68GKlsNHXHuM+Vzz8PKTFl0qTmx3TuuWP7OxiNSnIO2Y9Fd96ZTfWaNg3ypwrGwgRdkiSp3T38cNERtJf77hvbdh/4gNe63UTApEm1169Zk31uvHFr4vnUp0ZVvR3en16Zx9iSR9z/8z+zntb7+wfKBnfAN8iKxx5j6qmnEs8809zYKg4/fFybm6BLkiS1u698JZtG6/nn4Yc/HBiCDVjx/PMAbFDp8fjooxsVZXt66Uuz93gjsnd6JRVn4kQ44ohRbbK6r4/V73//2PrVKIAJuiRJUrf68IezO1JVSt9rdKv98Y+wyy6N298jj2TjrkvSEEzQJUmSmiEl+NrX2PBHPxq4Q115n3L+/Gz87Y02GugM67HHss+enoFOsirvYA6e1J622QY22aToKCSVmAm6JEkq1g03wN571129PR5SHFDzy9ZDD7UyDA1W3VN05T3kWs47D175yqz+S16SPfY+HpX3iiVpEBN0SZJUrAceKDoCdaPqXqJHctRRYzvGn/8MW245tm0ldSUTdEmSVKz3vS+b6tSX331slw5/Co938HBOteZvvhkefJAVy5cDsEFlWKeRth3NMYbbpqqjuiGHqYpYvzy3YsUKJp9zDj333EOprFpVdASS2owJuiRJUierHoJouOGI9t4b9t6b1fkPChu0yQ8gUNVL83XXwbPPDqx4/nn4xCdgyZJs+Y1vzN777+/PHmuvfN5449gPfvDBcOml44pfkipM0CVJktT+IuAd71i/fPbs+rYdrbe+NesBf7zvo0tSFRN0SZIkdbc//hHuuAM22ACmToUpU7LyoXrQX74crr0WTjgBpk0rNm5JHccEXZIkSd1t222zqV4HHNC8WCR1tQlFByBJkiRJkkzQJUmSJEkqBRN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSqBSCkVHUNNEfFn4JGi4yjQlsBTRQdRMK/B6K7BdimlFzUzmEYrQTtvl78x42y8dol1cJy280y7/PerMN7ma7eYh4u309p52f/bGN/4lT3GMsY3ZDsvdYLe7SJifkppVtFxFMlr4DVotna5vsbZeO0Sa7vE2Wrtdl2Mt/naLeZ2i3c8yn6uxjd+ZY+x7PFV8xF3SZIkSZJKwARdkiRJkqQSMEEvt7lFB1ACXgOvQbO1y/U1zsZrl1jbJc5Wa7frYrzN124xt1u841H2czW+8St7jGWP7wW+gy5JkiRJUgl4B12SJEmSpBIwQZckSZIkqQRM0CVJkiRJKgET9BKJiK0i4vX5tFXR8ahYEbF5RGxedBydxnbWXBHxrqJjaHcRMbFqflpEzPLfgoztt3Vsy43XrW27Hc7Rv3eVycSRq6jZImJX4LvAJsCivHhGRDwD/HNK6daCQitcRGyeUlpSdBytEhEvBb4M7Ac8kxVFL/Ar4PiU0sPFRdfebGeNFxHvHlwEfLvyJTSldEnro6pPRLwCeB1wX0rp3qLjqYiIvwe+EhGLgY8C3wYeAl4ZEZ9JKV1QZHxFsf02Vzu3ZShve67WLW07IvYB/hNYC/wDcCrwsoiYDByeUrq+yPigPf/ey/59uGxtMCI2TSk9U3QcY2Uv7iUQEbcD/5RSunFQ+V7A91JKrysksBaLiM+llE7N53cCLgUmkf3D+beDr08niojrga8BF6eU+vOyHuAw4GMppb0KDK+ttVM7i4jXAN8HtgF+BhyXUno6X3dTSmmPIuOriIjVwFXAk2TtFOBQ4GIgpZT+oajYBouIXwOHpZSeioj3Af8CXAvsCcxNKX2z0ABzEXEX8BZgY+AOYLeU0h/yu8XzUkqvLTTAgrRT+4X2acMV7dSWoX3ac7VuadsRcRNwDDAN+B/gkJTSdRHxeuCbKaV9Cg2Q8v+9t8P34bK3wYhYA1wDXAD8uO2S9ZSSU8ET8MAw6xYUHV8Lr8OtVfM/BQ7M5/cAflt0fCX4W6i5zmnc17ZU7Qy4DjgA2BT4FHAP8PJ83W1Fx1cV5+7A1cAHq8oeKjquGrHeXTV/M7BFPr8hcGfR8VXFdnvV/J8GrStNnAVcl7Zpv3lMbdGGq+Jtm7acx9YW7XlQzLdXzXds267++ya7m1q97tZWxTFCjKX+e2+H78Nlb4PAXcA7gfOBxcBlwBHABkXHVs/kI+7l8LOI+ClwHvBoXrYtcBTw88KiKtbWKaWfAaSUboqIDYoOqEVuiYjvAOey7t/CbOC2wqLqDO3UzjZOKVVi+o+IuAX4ef4rdWkee0op3RwRbwM+nP+afhwlim+Q1RGxTUppEfAs8FxevhLoKS6s9fwxIv6N7C7b/RHxFeAS4K+AxwqNrFjt1H6hTdpwRZu1ZWif9lytW9p2df9Wnx20bnIrA6mlzf7ey/p9uOxtcHVK6Qrgivya/TVZgv7tiLgqpfTeYsMbno+4l0REHAgcTPY4HGTv2F2eUrqyuKhaK3+X8FqyR3j2ArZLKS3P192dUtqlwPBaIn9H6xjW/VtYSPaY2FkppZVFxdYJ2qWdRcQdwJtTSkuryl4L/BjYPKW0RWHB1RARW5O9njErpfSygsNZT0TsS/bO54+BzYHXkz3i+CbgqpTSfxQWXJW8z4ljyb4sfgt4O3A08Ahwakqpk77Ij0q7tF9ozzZcUfa2DO3Tnqt1S9vOO1v7ZeX7W1X5y4H3pJS+XExkQyvj33s7fB8uexuMiNtSSrsNUb4J2WsX5xYQVt1M0FUaEfGXg4puSSk9m7+fdWhK6dtFxCW1WkS8F3gwpXTDoPKXAv+SUnp/MZG1t/x/zO8FXknWSepC4LKU0v2FBqaOYxtuPtuzOlW7fB8ucxuMiE8V/SPBeJigl1xEzEkpzS06DhUvIt6ZP66jBrOdNZ7XtPG8pkPzujSX17f5uuUat8N5tkOM6nyOg15+MXKVzhcRc4qOoQR2LzqADtY27ayN2oLXtPHa5pq2WFtdlzb6e6vw+jZfW13jcWiH8yx1jO3w9132GMseH5igl0ZE7BgR+0XEtEGrHikkoPIp9T+YjRQRe0TE7vn8ThHxiYg4KKV0UtGxtbsOaWelagte08brkGvacB10XUr191bh9W2+DrrGw2qH82yHGGso7d93lbLHWPb4TNDLICI+Qtb9/4eBuyPi4KrVXywmqmK08T+YDRERJwHfAM7Me3v9FrARcHxEnFhocG2u3dpZO7QFr2njtds1bZV2vC7t8PdW4fVtvna8xmPRDufZJjGW/u+77DGWPb5hFT3Om9MLY/VNy+e3B+YDH82Xbys6vhZeh48AvwMuBR4GDq5aV4qxM1v0t9BDNo5kH9Cbl29ACcaVbOepndpZu7QFr2l3X1Ovy7DxtsXfm9fXa9yN51n2GNvh77vsMZY9vpEmx0EvhwkppWcBUkoP50MXXBwR29EGj2E00PuBN6Ssp8rtya7B9imlr9M912FNSqkfWB4Rf0gp9QGklFZExNqCY2t37dTO2qUteE0br52uaSu123Vpl7+3Cq9v87XbNR6rdjjPssfYDn/fZY+x7PENy0fcy+GJiNi1spD/o/FOYEvgNUUFVYB1/sEE9gUOjIiv0gaNqUFWRcSG+fwbKoWRDWVhgj4+7dTO2qUteE0br52uaSu123Vpl7+3Cq9v87XbNR6rdjjPssfYDn/fZY+x7PENywS9HI4CHq8uSCmtSSkdBby5mJAKUfZ/MFvhzSml5QAppeqEfBIwu5iQOkY7tbN2aQte08Zrp2vaSu12Xdrl763C69t87XaNx6odzrPsMbbD33fZYyx7fMNyHHSVRkTMIHvE+/Eh1u2TUvq/AsKSWs620HheU7WSf2/N5fVVJ2uHv++yx1j2+EZigi5JkiRJUgn4iLskSZIkSSVggi5JkiRJUgmYoOsFEbFVRPwwIh6MiFsi4vqI+Juq9bdExJSImBYR34uIP+Rl10TEnhExNSJuiog7IuKeiPh8kecjaX22c6nz2c6lzmYb72yOgy4AIiKAS4FzU0rvzcu2A96Vz+8ALEoprYyIc4GHgJkppbX5up2AlcBb8zEHJwHXRcTPUko3FHBKkgaxnUudz3YudTbbeOczQVfFW4FVKaXvVgpSSo8A38wXDwB+HhEvB/YE/q4yDFhK6SGyxg/wbP45KZ/shVAqD9u51Pls51Jns413OB9xV8XOwK3DrD8A+Hle7/aUUv9QlSKiJyJuB54E5qWUbmx0oJLGzHYudT7budTZbOMdzgRdQ4qIb+fvpdwcEZOBGSmlB0faLqXUn1LaFZgB7BERuzQ7VkljYzuXOp/tXOpstvHOY4KuinuA11cWUkrHAvsBLwL+Ariuqt7rIqJnuJ2llJ4Bfk32K56kcrCdS53Pdi51Ntt4hzNBV8WvgKkR8cGqsg3zzwOAnwGklP4AzAc+n3dSQURsHxHviIgXRcSmedkGwNuA+1sUv6SR2c6lzmc7lzqbbbzDRUr2B6BMREwHziDrUOLPwHPAd4FPAW9OKa3I6/UCXyHrpGIF8BTwabIeIc8Fesh+/LkopXRKi09D0jBs51Lns51Lnc023tlM0DWsiJgBfD+ldGDRsUhqDtu51Pls51Jns413DhN0SZIkSZJKwHfQJUmSJEkqARN0SZIkSZJKwARdkiRJkqQSMEGXJEmSJKkETNAlSZIkSSoBE3RJkiRJkkrg/wdi3+8djEe3wAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1008x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(figsize=(14, 10), ncols=len(wells))\n",
    "\n",
    "curve_name = 'RHOB'\n",
    "\n",
    "for i, (ax, well) in enumerate(zip(axs, wells)):\n",
    "    gr = well.get_curve(curve_name)\n",
    "    if gr is not None:\n",
    "        ax = gr.plot(ax=ax, c='red')\n",
    "    ax.set_title(f\"{curve_name} for\\n{well.header.name}\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Well Log Data Quality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "import welly.quality as wq\n",
    "from IPython.display import HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "tests = {'Each': [wq.no_flat,\n",
    "                 wq.no_gaps,\n",
    "                 wq.not_empty],\n",
    "        'GR': [\n",
    "                wq.all_positive,\n",
    "                wq.all_between(0, 250),\n",
    "                wq.check_units(['API', 'GAPI']),\n",
    "        ],\n",
    "        'RHOB': [\n",
    "                wq.all_positive,\n",
    "                wq.all_between(1.5, 3),\n",
    "                wq.check_units(['G/CC', 'g/cm3']),\n",
    "        ]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table><tr><th>Idx</th><th>UWI</th><th>Data</th><th>Passing</th><th>GR</th><th>RHOB</th></tr><tr><td></td><td></td><td></td><td>%</td><td>4/4&nbsp;wells</td><td>4/4&nbsp;wells</td></tr><td>0</td><td><span style=\"font-weight:bold;\">L06-06</span></td><td>2/5&nbsp;curves</td><td>58</td><td style=\"background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;\">GR<div title=\"4/6\" style=\"font-size:80%; float:right; cursor: default; padding:4px 0px 4px 6px; color:#FFCC33;\">&#x2b24;</div><br /><span style=\"font-size:70%; color:#33AA33\">43.65 GAPI</span></td><td style=\"background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;\">RHOB<div title=\"3/6\" style=\"font-size:80%; float:right; cursor: default; padding:4px 0px 4px 6px; color:#FFCC33;\">&#x2b24;</div><br /><span style=\"font-size:70%; color:#33AA33\">2.52 G/C3</span></td></tr><td>1</td><td><span style=\"font-weight:bold;\">L07-01</span></td><td>2/4&nbsp;curves</td><td>83</td><td style=\"background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;\">GR<div title=\"5/6\" style=\"font-size:80%; float:right; cursor: default; padding:4px 0px 4px 6px; color:#FFCC33;\">&#x2b24;</div><br /><span style=\"font-size:70%; color:#33AA33\">46.86 GAPI</span></td><td style=\"background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;\">RHOB<div title=\"5/6\" style=\"font-size:80%; float:right; cursor: default; padding:4px 0px 4px 6px; color:#FFCC33;\">&#x2b24;</div><br /><span style=\"font-size:70%; color:#33AA33\">2.61 G/C3</span></td></tr><td>2</td><td><span style=\"font-weight:bold;\">L05-B-01</span></td><td>2/5&nbsp;curves</td><td>92</td><td style=\"background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;\">GR<div title=\"6/6\" style=\"font-size:80%; float:right; cursor: default; padding:4px 0px 4px 6px; color:#33EE33;\">&#x2b24;</div><br /><span style=\"font-size:70%; color:#33AA33\">36.02 GAPI</span></td><td style=\"background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;\">RHOB<div title=\"5/6\" style=\"font-size:80%; float:right; cursor: default; padding:4px 0px 4px 6px; color:#FFCC33;\">&#x2b24;</div><br /><span style=\"font-size:70%; color:#33AA33\">2.56 G/C3</span></td></tr><td>3</td><td><span style=\"font-weight:bold;\">L06-07</span></td><td>2/5&nbsp;curves</td><td>83</td><td style=\"background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;\">GR<div title=\"6/6\" style=\"font-size:80%; float:right; cursor: default; padding:4px 0px 4px 6px; color:#33EE33;\">&#x2b24;</div><br /><span style=\"font-size:70%; color:#33AA33\">28.73 GAPI</span></td><td style=\"background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;\">RHOB<div title=\"4/6\" style=\"font-size:80%; float:right; cursor: default; padding:4px 0px 4px 6px; color:#FFCC33;\">&#x2b24;</div><br /><span style=\"font-size:70%; color:#33AA33\">2.62 G/C3</span></td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_qc_table = wells.curve_table_html(keys=['GR', 'RHOB'], tests=tests)\n",
    "HTML(data_qc_table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "qc_dict = {}\n",
    "for well in wells:\n",
    "    qc_dict[well.header.name] = well.qc_table_html(tests)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table><tr><th>Curve</th><th>Passed</th><th>Score</th><th>check_units</th><th>no_gaps</th><th>no_flat</th><th>all_between</th><th>all_positive</th><th>not_empty</th></tr><tr><th>GR</th><td>4 / 6</td><td>0.667</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DT</th><td>2 / 3</td><td>0.667</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RHOB</th><td>3 / 6</td><td>0.500</td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DRHO</th><td>2 / 3</td><td>0.667</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>NPHI</th><td>2 / 3</td><td>0.667</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTML(qc_dict['L06-06'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table><tr><th>Curve</th><th>Passed</th><th>Score</th><th>check_units</th><th>no_gaps</th><th>no_flat</th><th>all_between</th><th>all_positive</th><th>not_empty</th></tr><tr><th>GR</th><td>5 / 6</td><td>0.833</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DT</th><td>2 / 3</td><td>0.667</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RHOB</th><td>5 / 6</td><td>0.833</td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>NPHI</th><td>3 / 3</td><td>1.000</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTML(qc_dict['L07-01'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Well Data to Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = wells.df()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "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></th>\n",
       "      <th>GR</th>\n",
       "      <th>DT</th>\n",
       "      <th>RHOB</th>\n",
       "      <th>DRHO</th>\n",
       "      <th>NPHI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UWI</th>\n",
       "      <th>Depth</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">L06-06</th>\n",
       "      <th>25.2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">L06-07</th>\n",
       "      <th>4855.7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4855.8</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4855.9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4856.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4856.1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>190880 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               GR  DT  RHOB  DRHO  NPHI\n",
       "UWI    Depth                           \n",
       "L06-06 25.2   NaN NaN   NaN   NaN   NaN\n",
       "       25.3   NaN NaN   NaN   NaN   NaN\n",
       "       25.4   NaN NaN   NaN   NaN   NaN\n",
       "       25.5   NaN NaN   NaN   NaN   NaN\n",
       "       25.6   NaN NaN   NaN   NaN   NaN\n",
       "...            ..  ..   ...   ...   ...\n",
       "L06-07 4855.7 NaN NaN   NaN   NaN   NaN\n",
       "       4855.8 NaN NaN   NaN   NaN   NaN\n",
       "       4855.9 NaN NaN   NaN   NaN   NaN\n",
       "       4856.0 NaN NaN   NaN   NaN   NaN\n",
       "       4856.1 NaN NaN   NaN   NaN   NaN\n",
       "\n",
       "[190880 rows x 5 columns]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "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>GR</th>\n",
       "      <th>DT</th>\n",
       "      <th>RHOB</th>\n",
       "      <th>DRHO</th>\n",
       "      <th>NPHI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Depth</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25.2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5594.6</th>\n",
       "      <td>136.702515</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5594.7</th>\n",
       "      <td>137.528931</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5594.8</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5594.9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5595.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>55699 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                GR  DT  RHOB  DRHO  NPHI\n",
       "Depth                                   \n",
       "25.2           NaN NaN   NaN   NaN   NaN\n",
       "25.3           NaN NaN   NaN   NaN   NaN\n",
       "25.4           NaN NaN   NaN   NaN   NaN\n",
       "25.5           NaN NaN   NaN   NaN   NaN\n",
       "25.6           NaN NaN   NaN   NaN   NaN\n",
       "...            ...  ..   ...   ...   ...\n",
       "5594.6  136.702515 NaN   NaN   NaN   NaN\n",
       "5594.7  137.528931 NaN   NaN   NaN   NaN\n",
       "5594.8         NaN NaN   NaN   NaN   NaN\n",
       "5594.9         NaN NaN   NaN   NaN   NaN\n",
       "5595.0         NaN NaN   NaN   NaN   NaN\n",
       "\n",
       "[55699 rows x 5 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['L06-06']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}