7_DLIS_files.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Opening DLIS Files and Extracting Data\n",
    "\n",
    "[Digital Log Interchange Standard (DLIS) files](https://dlisio.readthedocs.io/en/latest/dlis/specification.html) are the industry standard for storing well log data, including raw and processed borehole image log data. They are a binary file format for data that stores various kinds of metadata about when, where and who collected the data. There are also lists of what data was collected and with what tools. They have a useful flexibility that can also make them a difficult file type to work with. This notebook is designed to help you to explore the contents of a DLIS file and extract the data you need. \n",
    "\n",
    "Typically, expensive specialist software is used to open and view a DLIS file. However, the methods in this notebook enable us to explore and extract the content of a DLIS file at no cost by using an open-source library called [DLISio](https://dlisio.readthedocs.io/en/latest/index.html). While the focus here is on borehole image data, the same methods apply to other types of well log data stored as DLIS.\n",
    "\n",
    "Helper functions and some methods used here come from [this example notebook](https://github.com/equinor/dlisio-notebooks/tree/master), as well as the [DLISio documentation](https://dlisio.readthedocs.io/en/latest/index.html). I'd like to thank Equinor and the DLISio developers for their work on the DLISio library and the example notebooks.\n",
    "\n",
    "If you have any questions about borehole image DLIS or this notebook, please email irene@cubicearth.nz.\n",
    "\n",
    "## DLIS File Jargon and Structure\n",
    "\n",
    "The structure of a DLIS can be thought of as a hierarchical data storage system that includes various related metadata objects.\n",
    "\n",
    "- A DLIS contains one or more ___logical files___ that are like high-level folders. Commonly, separate logging runs in one well are stored as separate logical files in the same DLIS. For borehole image data, sometimes processed acoustic and microresistivity logs are delivered as septate logical files in a single DLIS. \n",
    "\n",
    "- Each logical file has an ___origin___ object that contains general information like when, where, and by whom the data was collected (metadata). Most logical files have a single origin. However, processed borehole image data may have more than one origin that includes the same information. If a logical file has more than one unique origin, then care should be taken to ensure data is associated with the correct origin.\n",
    "\n",
    "- Each logical file has a set of ___parameters___. This parameter object is the metadata defined at the time of log acquisition. It includes constants relevant to the tool and logging conditions, such as logging datum, well construction, tool settings, etc.\n",
    "\n",
    "- A ___curve___ is a single, unique log (the data). For example: gamma, pad 1 azimuth, caliper 1, caliper 2, etc. A curve may have one dimension (a single value recorded per depth) or more than one dimension (multiple values recorded per depth).\n",
    "\n",
    "- Metadata about each curve is stored as a ___channel___ object. This channel object contains information including the mnemonic (short name), long name, units, dimension, and associated frame. In this notebook, we make a table of these metadata to help us identify what data we want and the information needed to extract it.\n",
    "\n",
    "- Curves and channels that share an index are collected together in a ___frame___ object (index and metadata). The index is typically depth, but can be time for some data types. Frame objects include additional information like the spacing between data and direction of data acquisition. A frame typically includes curves (data) acquired in the same logging run.\n",
    "\n",
    "- Each logical file has a ___tool___ object (metadata) that describes the logging tool(s) used to acquire the data. In this notebook, we use the tool object to extract the channels and parameters associated with that tool.\n",
    "\n",
    "- Each logical file has a ___remarks___ object that stores comments made at the time of acquisition. These may include useful information about the logging conditions or data quality. \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import logging\n",
    "\n",
    "import dlisio\n",
    "from dlisio import dlis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Example Data\n",
    "\n",
    "The data used in this notebook is from the [78B-32 well at the Utah Forge project](https://gdr.openei.org/submissions/1330).\n",
    " \n",
    " Download the file named 'FORGE Well 78B-32 FMI and UBI Processed Data.zip'. \n",
    " \n",
    " The DLIS used here is the processed FMI data from that zip. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = 'University_Utah_FORGE_78B-32_FMI_processed_images.dlis'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Logical File(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the DLIS file, with the first logical file stored in f \n",
    "# all other logical files stored in f_tail\n",
    "\n",
    "f, *f_tail = dlis.load(filename)\n",
    "\n",
    "# Check if there is one or more logical files in f_tail\n",
    "if len(f_tail): logging.warning('There are more logical files in tail')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above code fragment loads the first logical file and places any other logical files that are present in f_tail. Where the DLIS contains more than one logical file, you will need to use a for loop to load each logical file in turn ([c.f. example in API docs](https://dlisio.readthedocs.io/en/latest/dlis/api.html#load-a-dlis-file)).\n",
    "\n",
    "There is more than one kind of [DLIS encoding](https://dlisio.readthedocs.io/en/latest/common-api.html#dlisio.common.set_encodings), but the only way to work out which encoding has been used is to guess. This notebook leaves encoding as the default, but you can try other encodings if you have a problem loading the DLIS file."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Origin(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:f contains multiple origins\n"
     ]
    }
   ],
   "source": [
    "# Load the first origin record for the logical file stored in f\n",
    "# and place all other origin records in origin_tail.\n",
    "\n",
    "origin, *origin_tail = f.origins\n",
    "\n",
    "if len(origin_tail): logging.warning('f contains multiple origins')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The warning above indicates that there is more than one origin record in the logical file.\n",
    "\n",
    "Below we print and compare the origin records. If they are the same, we can proceed. If they are different, we need to decide which origin record to use."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------\n",
      "Origin\n",
      "------\n",
      "name   : WELL-FORGE 78B-32\n",
      "origin : 113\n",
      "copy   : 0\n",
      "\n",
      "Logical file ID          : FORGE 78B-32\n",
      "File set name and number : FORGE / 1\n",
      "File number and type     : 0 / CUSTOMER\n",
      "\n",
      "Field                   : None\n",
      "Well (id/name)          :  / FORGE 78B-32\n",
      "Produced by (code/name) : 440 / Schlumberger\n",
      "Produced for            : University Of Utah\n",
      "Created                 : 2021-08-12 21:30:25\n",
      "\n",
      "Created by              : Techlog, (version: 2019.2.4 (rev: 2046510))\n",
      "Other programs/services : WELL-FORGE 78B-32\n",
      "\n",
      "\n",
      "------\n",
      "Origin\n",
      "------\n",
      "name   : DATASET-FMI_HD_2970-8529ft_processed\n",
      "origin : 114\n",
      "copy   : 0\n",
      "\n",
      "Logical file ID          : FORGE 78B-32\n",
      "File set name and number : FORGE / 1\n",
      "File number and type     : 0 / CUSTOMER\n",
      "\n",
      "Field                   : None\n",
      "Well (id/name)          :  / FORGE 78B-32\n",
      "Produced by (code/name) : 440 / Schlumberger\n",
      "Produced for            : University Of Utah\n",
      "Created                 : 2021-08-12 21:30:25\n",
      "\n",
      "Created by              : Techlog, (version: 2019.2.4 (rev: 2046510))\n",
      "Other programs/services : DATASET-FMI_HD_2970-8529ft_processed\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Print the description of all origin records\n",
    "for origin in f.origins:\n",
    "    print(origin.describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A helper function that extracts specified information from the logical file into a pandas dataframe\n",
    "\n",
    "def summarize(objs, **kwargs):\n",
    "    \"\"\"Create a pd.DataFrame that summarize the content of 'objs', One \n",
    "    object pr. row\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    \n",
    "    objs : list()\n",
    "        list of metadata objects\n",
    "        \n",
    "    **kwargs\n",
    "        Keyword arguments \n",
    "        Use kwargs to tell summarize() which fields (attributes) of the \n",
    "        objects you want to include in the DataFrame. The parameter name \n",
    "        must match an attribute on the object in 'objs', while the value \n",
    "        of the parameters is used as a column name. Any kwargs are excepted, \n",
    "        but if the object does not have the requested attribute, 'KeyError' \n",
    "        is used as the value.\n",
    "        \n",
    "    Returns\n",
    "    -------\n",
    "    \n",
    "    summary : pd.DataFrame\n",
    "    \"\"\"\n",
    "    summary = []\n",
    "    for attr, label in kwargs.items():\n",
    "        column = []\n",
    "        for obj in objs:\n",
    "            try:\n",
    "                value = getattr(obj, attr)\n",
    "            except AttributeError:\n",
    "                value = 'KeyError'\n",
    "    \n",
    "            column.append(value)\n",
    "        summary.append(column)\n",
    "\n",
    "    summary = pd.DataFrame(summary).T\n",
    "    summary.columns = kwargs.values()\n",
    "    return summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a table of all parameters in the logical file. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Long name</th>\n",
       "      <th>Value(s)</th>\n",
       "      <th>Units</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>STAT</td>\n",
       "      <td>State or Province</td>\n",
       "      <td>[Utah]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BS</td>\n",
       "      <td>Bit Size</td>\n",
       "      <td>[8.75]</td>\n",
       "      <td>in</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TLI</td>\n",
       "      <td>Top Log Interval</td>\n",
       "      <td>[-999.25]</td>\n",
       "      <td>ft</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CWEI</td>\n",
       "      <td>Casing Weight</td>\n",
       "      <td>[54.0]</td>\n",
       "      <td>lbm/ft</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RMFS</td>\n",
       "      <td>Resistivity of Mud Filtrate Sample</td>\n",
       "      <td>[0.15000000596046448]</td>\n",
       "      <td>ohm.m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>LATI</td>\n",
       "      <td>Latitude</td>\n",
       "      <td>[38.500171 degrees]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>LUL</td>\n",
       "      <td>Logging Unit Location</td>\n",
       "      <td>[F.Morgan]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>BLI</td>\n",
       "      <td>Bottom Log Interval</td>\n",
       "      <td>[-999.25]</td>\n",
       "      <td>ft</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BHT</td>\n",
       "      <td>Bottom Hole Temperature</td>\n",
       "      <td>[320.8699951171875]</td>\n",
       "      <td>degF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>EPD</td>\n",
       "      <td>Elevation of Permanent Datum (PDAT) above Mean...</td>\n",
       "      <td>[5536.0]</td>\n",
       "      <td>ft</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>MST</td>\n",
       "      <td>Mud Sample Temperature</td>\n",
       "      <td>[68.0]</td>\n",
       "      <td>degF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>DLAB</td>\n",
       "      <td>Date Logger At Bottom</td>\n",
       "      <td>[19-Jul-2021]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>APD</td>\n",
       "      <td>Elevation of Depth Reference (LMF) Above Perma...</td>\n",
       "      <td>[29.5]</td>\n",
       "      <td>ft</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>TLAB</td>\n",
       "      <td>Time Logger At Bottom</td>\n",
       "      <td>[07:53:00]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>LONG</td>\n",
       "      <td>Longitude</td>\n",
       "      <td>[-112.88221 degrees]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>DCS</td>\n",
       "      <td>Date Circulation Stopped</td>\n",
       "      <td>[19-Jul-2021]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>MCST</td>\n",
       "      <td>Mudcake Sample Temperature</td>\n",
       "      <td>[68.0]</td>\n",
       "      <td>degF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>RMCS</td>\n",
       "      <td>Resistivity of Mud Cake Sample</td>\n",
       "      <td>[-999.25]</td>\n",
       "      <td>ohm.m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>DFT</td>\n",
       "      <td>Drilling Fluid Type</td>\n",
       "      <td>[WATER]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>LUN</td>\n",
       "      <td>Logging Unit Number</td>\n",
       "      <td>[9108]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Name                                          Long name  \\\n",
       "0   STAT                                  State or Province   \n",
       "1     BS                                           Bit Size   \n",
       "2    TLI                                   Top Log Interval   \n",
       "3   CWEI                                      Casing Weight   \n",
       "4   RMFS                 Resistivity of Mud Filtrate Sample   \n",
       "5   LATI                                           Latitude   \n",
       "6    LUL                              Logging Unit Location   \n",
       "7    BLI                                Bottom Log Interval   \n",
       "8    BHT                            Bottom Hole Temperature   \n",
       "9    EPD  Elevation of Permanent Datum (PDAT) above Mean...   \n",
       "10   MST                             Mud Sample Temperature   \n",
       "11  DLAB                              Date Logger At Bottom   \n",
       "12   APD  Elevation of Depth Reference (LMF) Above Perma...   \n",
       "13  TLAB                              Time Logger At Bottom   \n",
       "14  LONG                                          Longitude   \n",
       "15   DCS                           Date Circulation Stopped   \n",
       "16  MCST                         Mudcake Sample Temperature   \n",
       "17  RMCS                     Resistivity of Mud Cake Sample   \n",
       "18   DFT                                Drilling Fluid Type   \n",
       "19   LUN                                Logging Unit Number   \n",
       "\n",
       "                 Value(s)   Units  \n",
       "0                  [Utah]          \n",
       "1                  [8.75]      in  \n",
       "2               [-999.25]      ft  \n",
       "3                  [54.0]  lbm/ft  \n",
       "4   [0.15000000596046448]   ohm.m  \n",
       "5     [38.500171 degrees]          \n",
       "6              [F.Morgan]          \n",
       "7               [-999.25]      ft  \n",
       "8     [320.8699951171875]    degF  \n",
       "9                [5536.0]      ft  \n",
       "10                 [68.0]    degF  \n",
       "11          [19-Jul-2021]          \n",
       "12                 [29.5]      ft  \n",
       "13             [07:53:00]          \n",
       "14   [-112.88221 degrees]          \n",
       "15          [19-Jul-2021]          \n",
       "16                 [68.0]    degF  \n",
       "17              [-999.25]   ohm.m  \n",
       "18                [WATER]          \n",
       "19                 [9108]          "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a pandas dataframe that contains parameter (constant) details\n",
    "parameter_table = summarize(f.parameters, name='Name', long_name='Long name', values='Value(s)')\n",
    "\n",
    "# Add units through the temporary units interface\n",
    "units_column = []\n",
    "for i, par in enumerate(f.parameters):\n",
    "    if i not in parameter_table.index: continue\n",
    "    try:\n",
    "        units_column.append(par.attic['VALUES'].units)\n",
    "    except KeyError:\n",
    "        units_column.append(None)\n",
    "parameter_table['Units'] = units_column\n",
    "\n",
    "# Sort the table alphabetically on parameter name\n",
    "parameter_table.sort_values('Name')\n",
    "\n",
    "# Display the first 20 rows of the parameter table\n",
    "display(parameter_table.head(20))\n",
    "# note that there are 108 parameters in this example\n",
    "\n",
    "# Export parameter table to CSV for ease of review\n",
    "#parameter_table.to_csv('parameter_table.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Select a set of key data from the parameter table. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Long name</th>\n",
       "      <th>Value(s)</th>\n",
       "      <th>Units</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>CN</td>\n",
       "      <td>Company Name</td>\n",
       "      <td>[University Of Utah]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>FN</td>\n",
       "      <td>Field Name</td>\n",
       "      <td>[None]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>LONG</td>\n",
       "      <td>Longitude</td>\n",
       "      <td>[-112.88221 degrees]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>LATI</td>\n",
       "      <td>Latitude</td>\n",
       "      <td>[38.500171 degrees]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>DLAB</td>\n",
       "      <td>Date Logger At Bottom</td>\n",
       "      <td>[19-Jul-2021]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>TLAB</td>\n",
       "      <td>Time Logger At Bottom</td>\n",
       "      <td>[07:53:00]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>CSIZ</td>\n",
       "      <td>Current Casing Size</td>\n",
       "      <td>[11.75]</td>\n",
       "      <td>in</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BS</td>\n",
       "      <td>Bit Size</td>\n",
       "      <td>[8.75]</td>\n",
       "      <td>in</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Name              Long name              Value(s) Units\n",
       "32    CN           Company Name  [University Of Utah]      \n",
       "25    FN             Field Name                [None]      \n",
       "14  LONG              Longitude  [-112.88221 degrees]      \n",
       "5   LATI               Latitude   [38.500171 degrees]      \n",
       "11  DLAB  Date Logger At Bottom         [19-Jul-2021]      \n",
       "13  TLAB  Time Logger At Bottom            [07:53:00]      \n",
       "21  CSIZ    Current Casing Size               [11.75]    in\n",
       "1     BS               Bit Size                [8.75]    in"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "key_parameters = ['CN', 'WN', 'FN',                                         # Well ID\n",
    "                   'NATI', 'CONT', 'FL', 'FL1', 'FL2', 'LONG', 'LATI',      # Well location\n",
    "                   'DLAB', 'TLAB',                                          # Time and date of well logging\n",
    "                   'CSIZ', 'BS']                                            # Casing and well parameters\n",
    "\n",
    "# Create a table out of the parameters in desc_parameters\n",
    "summary_table = parameter_table.loc[parameter_table['Name'].isin(key_parameters)].copy()\n",
    "\n",
    "# Sort the table in the same order as desc_parameters\n",
    "categorical_sorter = pd.Categorical(key_parameters, key_parameters, ordered=True)\n",
    "summary_table['Name'] = summary_table['Name'].astype(categorical_sorter.dtype)\n",
    "summary_table.sort_values(by='Name', inplace=True)\n",
    "\n",
    "display(summary_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Remarks\n",
    "\n",
    "Sometimes there is useful information in the remarks that were made at the time of log acquisition. \n",
    "\n",
    "In this example, we are working with a processed dataset and there are no stored remarks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the remarks from the logical file and print them\n",
    "\n",
    "remarks = f.find('PARAMETER', '^R[0-9]{1,2}')\n",
    "remarks = sorted(remarks, key=lambda x: int(x.name[1:]) )\n",
    "\n",
    "for remark in remarks:\n",
    "    #if not remark.values: continue    # Uncomment to skip empty remarks\n",
    "    if remark.name == 'R8': continue   # Hide a remark containing a name; comment out the line to show the remark\n",
    "    print(f'{remark.name}: {\" \".join(remark.values)}')\n",
    "\n",
    "# If there are no remarks (as can be the case with processed data), then nothing will print."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Channels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frame FMI_HD_2970-8529FT_PROCESSED:\n",
      "Description      : \n",
      "Indexed by       : BOREHOLE-DEPTH\n",
      "Interval         : [2969.9999999999995, 8529.533333333331] ft\n",
      "Direction        : INCREASING\n",
      "Constant spacing : 0.00833333333333333 ft\n",
      "Index channel    : Channel(TDEP)\n",
      "No. of channels  : 14\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# all channels in one frame are referenced (indexed) against the same value (typically depth)\n",
    "\n",
    "for frame in f.frames:\n",
    "    index_channel = next(ch for ch in frame.channels if ch.name == frame.index)\n",
    "    print(f'Frame {frame.name}:')\n",
    "    print(f'Description      : {frame.description}')\n",
    "    print(f'Indexed by       : {frame.index_type}')\n",
    "    print(f'Interval         : [{frame.index_min}, {frame.index_max}] {index_channel.units}')\n",
    "    print(f'Direction        : {frame.direction}')\n",
    "    print(f'Constant spacing : {frame.spacing} {index_channel.units}')\n",
    "    print(f'Index channel    : {index_channel}')\n",
    "    print(f'No. of channels  : {len(frame.channels)}')\n",
    "    print()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Name</th>\n",
       "      <th>Long name</th>\n",
       "      <th>Units</th>\n",
       "      <th>Dimension</th>\n",
       "      <th>Frame</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TDEP</td>\n",
       "      <td>Tool Depth</td>\n",
       "      <td>ft</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ARRAY_WBI_IMGCAL</td>\n",
       "      <td></td>\n",
       "      <td>mS/m</td>\n",
       "      <td>[360]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ASSOC_CAL</td>\n",
       "      <td></td>\n",
       "      <td>in</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>C1_S</td>\n",
       "      <td>Caliper 1</td>\n",
       "      <td>in</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C2_S</td>\n",
       "      <td>Caliper 2</td>\n",
       "      <td>in</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>DEVIM_S</td>\n",
       "      <td>Memorized Deviation</td>\n",
       "      <td>deg</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>FMI_DYN</td>\n",
       "      <td>Button Resistivity profile corrected for gain ...</td>\n",
       "      <td></td>\n",
       "      <td>[360]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FMI_STAT</td>\n",
       "      <td>Button Resistivity profile corrected for gain ...</td>\n",
       "      <td></td>\n",
       "      <td>[360]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>GR_EDTC</td>\n",
       "      <td>Gamma Ray</td>\n",
       "      <td>gAPI</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>GR_EDTC_S</td>\n",
       "      <td>Gamma Ray</td>\n",
       "      <td>gAPI</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>HAZIM_S</td>\n",
       "      <td>Memorized Hole Azimuth</td>\n",
       "      <td>deg</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>P1NO_FBST_S</td>\n",
       "      <td>Pad 1 Azimuth in Plane Orthogonal to Tool Axis...</td>\n",
       "      <td>deg</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>RB_FBST_S</td>\n",
       "      <td>Memorized Relative Bearing</td>\n",
       "      <td>deg</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>STICKING_DETECTOR_S</td>\n",
       "      <td></td>\n",
       "      <td>unitless</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Name                                          Long name  \\\n",
       "0                  TDEP                                         Tool Depth   \n",
       "1      ARRAY_WBI_IMGCAL                                                      \n",
       "2             ASSOC_CAL                                                      \n",
       "3                  C1_S                                          Caliper 1   \n",
       "4                  C2_S                                          Caliper 2   \n",
       "5               DEVIM_S                                Memorized Deviation   \n",
       "6               FMI_DYN  Button Resistivity profile corrected for gain ...   \n",
       "7              FMI_STAT  Button Resistivity profile corrected for gain ...   \n",
       "8               GR_EDTC                                          Gamma Ray   \n",
       "9             GR_EDTC_S                                          Gamma Ray   \n",
       "10              HAZIM_S                             Memorized Hole Azimuth   \n",
       "11          P1NO_FBST_S  Pad 1 Azimuth in Plane Orthogonal to Tool Axis...   \n",
       "12            RB_FBST_S                         Memorized Relative Bearing   \n",
       "13  STICKING_DETECTOR_S                                                      \n",
       "\n",
       "       Units Dimension                                Frame  \n",
       "0         ft       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "1       mS/m     [360]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "2         in       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "3         in       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "4         in       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "5        deg       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "6                [360]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "7                [360]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "8       gAPI       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "9       gAPI       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "10       deg       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "11       deg       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "12       deg       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "13  unitless       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "channel_table = summarize(\n",
    "    f.channels, \n",
    "    name='Name', \n",
    "    long_name='Long name', \n",
    "    units='Units',\n",
    "    dimension='Dimension', \n",
    "    frame='Frame')\n",
    "\n",
    "channel_table.sort_values('Name')\n",
    "\n",
    "display(channel_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Tool(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Name</th>\n",
       "      <th>Generic name</th>\n",
       "      <th>Trademark name</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EDTCB</td>\n",
       "      <td></td>\n",
       "      <td>EDTC-B</td>\n",
       "      <td>Enhanced Digital Telemetry Cartridge - Version B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FBST-E</td>\n",
       "      <td></td>\n",
       "      <td>FBST-E</td>\n",
       "      <td>Full-Bore Scanner Tool E</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name Generic name Trademark name  \\\n",
       "0   EDTCB                      EDTC-B   \n",
       "1  FBST-E                      FBST-E   \n",
       "\n",
       "                                        Description  \n",
       "0  Enhanced Digital Telemetry Cartridge - Version B  \n",
       "1                          Full-Bore Scanner Tool E  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a pandas dataframe that contains tool type information\n",
    "tool_table = summarize(\n",
    "    f.tools, \n",
    "    name='Name', \n",
    "    generic_name='Generic name',\n",
    "    trademark_name='Trademark name', \n",
    "    description='Description')\n",
    "\n",
    "# Sort the table aphapetically by the tool name\n",
    "tool_table.sort_values('Name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "----\n",
       "Tool\n",
       "----\n",
       "name   : FBST-E\n",
       "origin : 114\n",
       "copy   : 1\n",
       "\n",
       "Description    : Full-Bore Scanner Tool E\n",
       "Trademark name : FBST-E\n",
       "\n",
       "Channels   : RB_FBST_S   HAZIM_S     DEVIM_S     C1_S        C2_S\n",
       "             P1NO_FBST_S\n",
       "Parameters : EMEXREG        GARM_B         FBEF           AOFFX\n",
       "             CORRELAT_CUT   FIEQ           STEP           FDBD           FDBP\n",
       "             RBSI           FBST_SIGPROC   EMXCORR        MIN_APP_DIP\n",
       "             SWING_ARM_CORR MDIP_REJECT    SOFF           FDFL           GARM_D\n",
       "             GARM_A         AFMO           FOFFX          XVOL           FOFFY\n",
       "             MPSC           ENABLED        LOG_SPEED_RNG  EMXCORRDIP\n",
       "             SEARCH_ANGLE   PADT           GAIN_FBST      FOFFZ\n",
       "             C1_SHIFT       RBS            FOCUS_DIP_AZI  C2_SHIFT\n",
       "             FOCUS_DIP_RT   MAX_TOOL_SPEED GARM_C         EMXGMOD        FIGA\n",
       "             ICMO           AOFFZ          AOFFY          MEAS_PNTR      FLM\n",
       "             APM            FIOF           CORINT         AMIP\n",
       "             FOCUS_DIP_MAG\n"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract metadata associated with a specific tool\n",
    "selected_tool = f.object(\n",
    "    'TOOL',         # object type\n",
    "    'FBST-E'        # object name from table above\n",
    "    )\n",
    "\n",
    "selected_tool.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Name</th>\n",
       "      <th>Long name</th>\n",
       "      <th>Value(s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>AFMO</td>\n",
       "      <td>Accelerometer Filtering Mode</td>\n",
       "      <td>[HAMMING]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>AMIP</td>\n",
       "      <td>Adaptive Mode Initial Phase</td>\n",
       "      <td>[0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AOFFX</td>\n",
       "      <td>X Accelerometer Offset</td>\n",
       "      <td>[0.05905511975288391]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>AOFFY</td>\n",
       "      <td>Y Accelerometer Offset</td>\n",
       "      <td>[-0.07217848300933838]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>AOFFZ</td>\n",
       "      <td>Z Accelerometer Offset</td>\n",
       "      <td>[0.019685039296746254]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>APM</td>\n",
       "      <td>Acquisition Phase Mode</td>\n",
       "      <td>[WBM - ADAPTIVE PHASE CONTROL]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>C1_SHIFT</td>\n",
       "      <td>C1 Caliper Supplementary Offset</td>\n",
       "      <td>[0.17299999296665192]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>C2_SHIFT</td>\n",
       "      <td>C2 Caliper Supplementary Offset</td>\n",
       "      <td>[-0.20100000500679016]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>CORINT</td>\n",
       "      <td>Correlation interval</td>\n",
       "      <td>[4.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CORRELAT_CUT</td>\n",
       "      <td>Correlation Cutoff for Dip Computation (betwee...</td>\n",
       "      <td>[0.3]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EMEXREG</td>\n",
       "      <td>EMEX Regulation Level</td>\n",
       "      <td>[9.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>EMXCORR</td>\n",
       "      <td>EMEX Correction</td>\n",
       "      <td>[ON]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>EMXCORRDIP</td>\n",
       "      <td>Correct Dip Buttons Values by EMEX</td>\n",
       "      <td>[OFF]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>EMXGMOD</td>\n",
       "      <td>EMEX and Gain Modes</td>\n",
       "      <td>[EMEXMANU_GAINMANU]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ENABLED</td>\n",
       "      <td>Equipment or Computation Acquisition Status</td>\n",
       "      <td>[Yes]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FBEF</td>\n",
       "      <td>EMEX Filtering Activation</td>\n",
       "      <td>[OFF]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>FBST_SIGPROC</td>\n",
       "      <td>Signal Processing Mode</td>\n",
       "      <td>[IN-PHASE]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FDBD</td>\n",
       "      <td>Dead Buttons Detection</td>\n",
       "      <td>[OFF]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>FDBP</td>\n",
       "      <td>Dead Buttons Patching</td>\n",
       "      <td>[OFF]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>FDFL</td>\n",
       "      <td>DSP Filter Length</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>FIEQ</td>\n",
       "      <td>Image Equalization</td>\n",
       "      <td>[ON]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>FIGA</td>\n",
       "      <td>Image Gain</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>FIOF</td>\n",
       "      <td>Image Offset</td>\n",
       "      <td>[0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>FLM</td>\n",
       "      <td>Logging Mode</td>\n",
       "      <td>[8-PAD (FULL IMAGE ACQUISITION)]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>FOCUS_DIP_AZI</td>\n",
       "      <td>Focus Dip Azimuth</td>\n",
       "      <td>[0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>FOCUS_DIP_MAG</td>\n",
       "      <td>Focus Dip Magnitude</td>\n",
       "      <td>[0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>FOCUS_DIP_RT</td>\n",
       "      <td>Real Time Focusing Dip Type</td>\n",
       "      <td>[Normal to Tool Axis]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>FOFFX</td>\n",
       "      <td>X Magnetometer Offset</td>\n",
       "      <td>[-0.001500000013038516]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>FOFFY</td>\n",
       "      <td>Y Magnetometer Offset</td>\n",
       "      <td>[-0.0044999998062849045]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>FOFFZ</td>\n",
       "      <td>Z Magnetometer Offset</td>\n",
       "      <td>[0.008500000461935997]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>GAIN_FBST</td>\n",
       "      <td>Electronic Gain Value in Manual Mode</td>\n",
       "      <td>[0 DB]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>GARM_A</td>\n",
       "      <td>Electronic Gain Value for Arm A</td>\n",
       "      <td>[0 DB]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GARM_B</td>\n",
       "      <td>Electronic Gain Value for Arm B</td>\n",
       "      <td>[0 DB]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>GARM_C</td>\n",
       "      <td>Electronic Gain Value for Arm C</td>\n",
       "      <td>[0 DB]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>GARM_D</td>\n",
       "      <td>Electronic Gain Value for Arm D</td>\n",
       "      <td>[0 DB]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>ICMO</td>\n",
       "      <td>Inclinometry Computation Mode</td>\n",
       "      <td>[Open Hole]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>LOG_SPEED_RNG</td>\n",
       "      <td>Logging Speed Range</td>\n",
       "      <td>[Normal (600 ft/h - 3600 ft/h)]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>MAX_TOOL_SPEED</td>\n",
       "      <td>Maximum service speed allowed for, or attained...</td>\n",
       "      <td>[1800.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>MDIP_REJECT</td>\n",
       "      <td>Real Time Mirror Dip Rejection</td>\n",
       "      <td>[Disable]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>MEAS_PNTR</td>\n",
       "      <td>Measurement Penetration</td>\n",
       "      <td>[0.39399999380111694]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>MIN_APP_DIP</td>\n",
       "      <td>Minimum Apparent Dip</td>\n",
       "      <td>[0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>MPSC</td>\n",
       "      <td>Manual Phase Shift Compensation</td>\n",
       "      <td>[0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>PADT</td>\n",
       "      <td>Presentation Allow Disallow Threshold</td>\n",
       "      <td>[0.5]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>RBS</td>\n",
       "      <td>Resistivity Button Selection</td>\n",
       "      <td>[AUTO]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>RBSI</td>\n",
       "      <td>Auto RBS Change Interval</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>SEARCH_ANGLE</td>\n",
       "      <td>Angular range to search around focus dip</td>\n",
       "      <td>[60.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>SOFF</td>\n",
       "      <td>Standoff</td>\n",
       "      <td>[-1.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>STEP</td>\n",
       "      <td>Step Length between Correlations</td>\n",
       "      <td>[2.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SWING_ARM_CORR</td>\n",
       "      <td>Swing Arm Correction Switch</td>\n",
       "      <td>[No]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>XVOL</td>\n",
       "      <td>EMEX Voltage</td>\n",
       "      <td>[0.0]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Name                                          Long name  \\\n",
       "19            AFMO                       Accelerometer Filtering Mode   \n",
       "48            AMIP                        Adaptive Mode Initial Phase   \n",
       "3            AOFFX                             X Accelerometer Offset   \n",
       "42           AOFFY                             Y Accelerometer Offset   \n",
       "41           AOFFZ                             Z Accelerometer Offset   \n",
       "45             APM                             Acquisition Phase Mode   \n",
       "31        C1_SHIFT                    C1 Caliper Supplementary Offset   \n",
       "34        C2_SHIFT                    C2 Caliper Supplementary Offset   \n",
       "47          CORINT                               Correlation interval   \n",
       "4     CORRELAT_CUT  Correlation Cutoff for Dip Computation (betwee...   \n",
       "0          EMEXREG                              EMEX Regulation Level   \n",
       "11         EMXCORR                                    EMEX Correction   \n",
       "26      EMXCORRDIP                 Correct Dip Buttons Values by EMEX   \n",
       "38         EMXGMOD                                EMEX and Gain Modes   \n",
       "24         ENABLED        Equipment or Computation Acquisition Status   \n",
       "2             FBEF                          EMEX Filtering Activation   \n",
       "10    FBST_SIGPROC                             Signal Processing Mode   \n",
       "7             FDBD                             Dead Buttons Detection   \n",
       "8             FDBP                              Dead Buttons Patching   \n",
       "16            FDFL                                  DSP Filter Length   \n",
       "5             FIEQ                                 Image Equalization   \n",
       "39            FIGA                                         Image Gain   \n",
       "46            FIOF                                       Image Offset   \n",
       "44             FLM                                       Logging Mode   \n",
       "33   FOCUS_DIP_AZI                                  Focus Dip Azimuth   \n",
       "49   FOCUS_DIP_MAG                                Focus Dip Magnitude   \n",
       "35    FOCUS_DIP_RT                        Real Time Focusing Dip Type   \n",
       "20           FOFFX                              X Magnetometer Offset   \n",
       "22           FOFFY                              Y Magnetometer Offset   \n",
       "30           FOFFZ                              Z Magnetometer Offset   \n",
       "29       GAIN_FBST               Electronic Gain Value in Manual Mode   \n",
       "18          GARM_A                    Electronic Gain Value for Arm A   \n",
       "1           GARM_B                    Electronic Gain Value for Arm B   \n",
       "37          GARM_C                    Electronic Gain Value for Arm C   \n",
       "17          GARM_D                    Electronic Gain Value for Arm D   \n",
       "40            ICMO                      Inclinometry Computation Mode   \n",
       "25   LOG_SPEED_RNG                                Logging Speed Range   \n",
       "36  MAX_TOOL_SPEED  Maximum service speed allowed for, or attained...   \n",
       "14     MDIP_REJECT                     Real Time Mirror Dip Rejection   \n",
       "43       MEAS_PNTR                            Measurement Penetration   \n",
       "12     MIN_APP_DIP                               Minimum Apparent Dip   \n",
       "23            MPSC                    Manual Phase Shift Compensation   \n",
       "28            PADT              Presentation Allow Disallow Threshold   \n",
       "32             RBS                       Resistivity Button Selection   \n",
       "9             RBSI                           Auto RBS Change Interval   \n",
       "27    SEARCH_ANGLE           Angular range to search around focus dip   \n",
       "15            SOFF                                           Standoff   \n",
       "6             STEP                   Step Length between Correlations   \n",
       "13  SWING_ARM_CORR                        Swing Arm Correction Switch   \n",
       "21            XVOL                                       EMEX Voltage   \n",
       "\n",
       "                            Value(s)  \n",
       "19                         [HAMMING]  \n",
       "48                             [0.0]  \n",
       "3              [0.05905511975288391]  \n",
       "42            [-0.07217848300933838]  \n",
       "41            [0.019685039296746254]  \n",
       "45    [WBM - ADAPTIVE PHASE CONTROL]  \n",
       "31             [0.17299999296665192]  \n",
       "34            [-0.20100000500679016]  \n",
       "47                             [4.0]  \n",
       "4                              [0.3]  \n",
       "0                              [9.0]  \n",
       "11                              [ON]  \n",
       "26                             [OFF]  \n",
       "38               [EMEXMANU_GAINMANU]  \n",
       "24                             [Yes]  \n",
       "2                              [OFF]  \n",
       "10                        [IN-PHASE]  \n",
       "7                              [OFF]  \n",
       "8                              [OFF]  \n",
       "16                               [1]  \n",
       "5                               [ON]  \n",
       "39                               [1]  \n",
       "46                               [0]  \n",
       "44  [8-PAD (FULL IMAGE ACQUISITION)]  \n",
       "33                             [0.0]  \n",
       "49                             [0.0]  \n",
       "35             [Normal to Tool Axis]  \n",
       "20           [-0.001500000013038516]  \n",
       "22          [-0.0044999998062849045]  \n",
       "30            [0.008500000461935997]  \n",
       "29                            [0 DB]  \n",
       "18                            [0 DB]  \n",
       "1                             [0 DB]  \n",
       "37                            [0 DB]  \n",
       "17                            [0 DB]  \n",
       "40                       [Open Hole]  \n",
       "25   [Normal (600 ft/h - 3600 ft/h)]  \n",
       "36                          [1800.0]  \n",
       "14                         [Disable]  \n",
       "43             [0.39399999380111694]  \n",
       "12                             [0.0]  \n",
       "23                             [0.0]  \n",
       "28                             [0.5]  \n",
       "32                            [AUTO]  \n",
       "9                               [10]  \n",
       "27                            [60.0]  \n",
       "15                            [-1.0]  \n",
       "6                              [2.0]  \n",
       "13                              [No]  \n",
       "21                             [0.0]  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_tool_param_table = summarize(\n",
    "    selected_tool.parameters, \n",
    "    name='Name', \n",
    "    long_name='Long name', \n",
    "    values='Value(s)')\n",
    "\n",
    "selected_tool_param_table.sort_values('Name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Name</th>\n",
       "      <th>Long name</th>\n",
       "      <th>Units</th>\n",
       "      <th>Dimension</th>\n",
       "      <th>Frame</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>C1_S</td>\n",
       "      <td>Caliper 1</td>\n",
       "      <td>in</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C2_S</td>\n",
       "      <td>Caliper 2</td>\n",
       "      <td>in</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DEVIM_S</td>\n",
       "      <td>Memorized Deviation</td>\n",
       "      <td>deg</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HAZIM_S</td>\n",
       "      <td>Memorized Hole Azimuth</td>\n",
       "      <td>deg</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>P1NO_FBST_S</td>\n",
       "      <td>Pad 1 Azimuth in Plane Orthogonal to Tool Axis...</td>\n",
       "      <td>deg</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RB_FBST_S</td>\n",
       "      <td>Memorized Relative Bearing</td>\n",
       "      <td>deg</td>\n",
       "      <td>[1]</td>\n",
       "      <td>Frame(FMI_HD_2970-8529FT_PROCESSED)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name                                          Long name Units  \\\n",
       "3         C1_S                                          Caliper 1    in   \n",
       "4         C2_S                                          Caliper 2    in   \n",
       "2      DEVIM_S                                Memorized Deviation   deg   \n",
       "1      HAZIM_S                             Memorized Hole Azimuth   deg   \n",
       "5  P1NO_FBST_S  Pad 1 Azimuth in Plane Orthogonal to Tool Axis...   deg   \n",
       "0    RB_FBST_S                         Memorized Relative Bearing   deg   \n",
       "\n",
       "  Dimension                                Frame  \n",
       "3       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "4       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "2       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "1       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "5       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  \n",
       "0       [1]  Frame(FMI_HD_2970-8529FT_PROCESSED)  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_tool_channel_table = summarize(\n",
    "    selected_tool.channels, \n",
    "    name='Name', \n",
    "    long_name='Long name', \n",
    "    units='Units',\n",
    "    dimension='Dimension', \n",
    "    frame='Frame')\n",
    "\n",
    "selected_tool_channel_table.sort_values('Name')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. Extract Data\n",
    "\n",
    "To extract data, we need to evaluate the channel table above to determine:\n",
    "\n",
    "1. The name of the frame that contains the data we are interested in. In this case, all data are located in the \"FMI_HD_2970-8529FT_PROCESSED\" frame.\n",
    "\n",
    "2. The name (mnemonic) of the curve/channel we are interested in. In this case, we are interested in \"FMI_DYN\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-----\n",
       "Frame\n",
       "-----\n",
       "name   : FMI_HD_2970-8529FT_PROCESSED\n",
       "origin : 114\n",
       "copy   : 0\n",
       "\n",
       "Channel indexing\n",
       "--\n",
       "Indexed by       : BOREHOLE-DEPTH\n",
       "Index units      : ft\n",
       "Index min        : 2969.9999999999995 [ft]\n",
       "Index max        : 8529.533333333331 [ft]\n",
       "Direction        : INCREASING\n",
       "Constant spacing : 0.00833333333333333 [ft]\n",
       "Index channel    : Channel(TDEP)\n",
       "\n",
       "Channels\n",
       "--\n",
       "TDEP                ARRAY_WBI_IMGCAL    ASSOC_CAL           C1_S\n",
       "C2_S                DEVIM_S             FMI_DYN             FMI_STAT\n",
       "GR_EDTC             GR_EDTC_S           HAZIM_S             P1NO_FBST_S\n",
       "RB_FBST_S           STICKING_DETECTOR_S"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define the frame\n",
    "\n",
    "frame = f.object('FRAME', 'FMI_HD_2970-8529FT_PROCESSED')\n",
    "\n",
    "frame.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get all curves from the frame\n",
    "curves = frame.curves()\n",
    "\n",
    "# Get the desired curve from the curves\n",
    "FMI_DYN = curves['FMI_DYN']\n",
    "\n",
    "# Because we are working with a micro-resistivity image log, \n",
    "# there are nan values in the gaps between the pads. We need to \n",
    "# replace the log nan values (-9999.0) with np.nan to make a nice plot.\n",
    "FMI_DYN[FMI_DYN == -9999.] = np.nan\n",
    "\n",
    "# Get the index channel (depth) from the frame\n",
    "DEPT = curves[frame.index]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9. Plot 50 ft of FMI Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A helper function for plotting image logs using matplotlib imshow \n",
    "def paint_channel(ax, curve, y_axis, x_axis, **kwargs):\n",
    "    \"\"\"Plot an image channel into an axes using an index channel for the y-axis\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    \n",
    "        ax : matplotlib.axes\n",
    "        \n",
    "        curve : numpy array\n",
    "            The curve to be plotted\n",
    "        \n",
    "        index : numpy array \n",
    "            The depth index as a Channel object (slower) or a numpy array (faster)\n",
    "        \n",
    "        **kwargs : dict \n",
    "            Keyword arguments to be passed on to ax.imshow()\n",
    "    \"\"\"\n",
    "    # Determine the extent of the image so that the pixel centres correspond with the correct axis values\n",
    "    dx = np.mean(x_axis[1:] - x_axis[:-1])\n",
    "    dy = np.mean(y_axis[1:] - y_axis[:-1])\n",
    "    extent = (x_axis[0] - dx/2, x_axis[-1] + dx/2, y_axis[0] - dy/2, y_axis[-1] + dy/2)\n",
    "    \n",
    "    # Determine the correct orientation of the image\n",
    "    if y_axis[1] < y_axis[0]:   # Frame recorded from the bottom to the top of the well\n",
    "        origin = 'lower'\n",
    "    else:                       # Frame recorded from the top to the bottom of the well\n",
    "        origin = 'upper'\n",
    "    \n",
    "    return ax.imshow(curve, aspect='auto', origin=origin, extent=extent, **kwargs)\n",
    "\n",
    "\n",
    "# Plot the image log\n",
    "fig, ax = plt.subplots(1,1, figsize=(4,8), sharey=True, constrained_layout=True)\n",
    "\n",
    "ang = np.arange(360)\n",
    "\n",
    "im = paint_channel(ax, FMI_DYN, DEPT, ang, cmap='YlOrBr', vmin=-10, vmax=300) \n",
    "\n",
    "cbar = fig.colorbar(im, ax=ax, location='top')\n",
    "cbar.set_label('FMI resistivity - dynamic normalization')\n",
    "\n",
    "ax.set_xticks([0, 90, 180, 270, 360])\n",
    "ax.set_xticklabels(['N', 'E', 'S', 'W', 'N'])\n",
    "\n",
    "ax.grid(True)\n",
    "\n",
    "#ax.set_xlabel('Azimuthal angle from north [°]')\n",
    "ax.set_ylabel('Depth [ft]')\n",
    "\n",
    "ax.set_ylim(4600, 4550)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "sandpit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}