{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["# Quick start\n", "\n", "Welcome to the **Quick start** guide! This should help you get started using `welly`.\n", "\n", "First some preliminaries..."]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [{"data": {"text/plain": ["'0.4.10.dev49+g6b014a6.d20220213'"]}, "execution_count": 1, "metadata": {}, "output_type": "execute_result"}], "source": ["import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "import welly\n", "welly.__version__"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Create a project from LAS\n", "\n", "Use the `read_las()` function to load a well by passing a single filename, a POSIX-style path with wildcards (e.g. `'file_*.las'`) or URL as a `str`.\n", "\n", "This creates a project containing one (or more, depending on the wildcard) wells."]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["0it [00:00, ?it/s]Only engine='normal' can read wrapped files\n", "1it [00:01,  1.84s/it]\n"]}, {"data": {"text/html": ["<table><tr><th>Index</th><th>UWI</th><th>Data</th><th>Curves</th></tr><tr><td>0</td><td><strong>Long = 63* 45'24.460  W</strong></td><td>24&nbsp;curves</td><td>CALI, HCAL, PEF, DT, DTS, DPHI_SAN, DPHI_LIM, DPHI_DOL, NPHI_SAN, NPHI_LIM, NPHI_DOL, RLA5, RLA3, RLA4, RLA1, RLA2, RXOZ, RXO_HRLT, RT_HRLT, RM_HRLT, DRHO, RHOB, GR, SP</td></tr></table>"], "text/plain": ["Project(1 wells: Long = 63* 45'24.460  W)"]}, "execution_count": 2, "metadata": {}, "output_type": "execute_result"}], "source": ["project = welly.read_las('https://geocomp.s3.amazonaws.com/data/P-129.LAS')\n", "\n", "project"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Clearly there are some issues with this well. Have a look at the [Well object docs](Wells.ipynb) to see how to fix them.\n", "\n", "You can index into a project to get at a single well."]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"text/html": ["<table><tr><th style=\"text-align:center;\" colspan=\"2\">Kennetcook #2<br><small>Long = 63* 45'24.460  W</small></th></tr><tr><td><strong>crs</strong></td><td>CRS({})</td></tr><tr><td><strong>location</strong></td><td>Lat = 45* 12' 34.237\" N</td></tr><tr><td><strong>country</strong></td><td>CA</td></tr><tr><td><strong>province</strong></td><td>Nova Scotia</td></tr><tr><td><strong>latitude</strong></td><td></td></tr><tr><td><strong>longitude</strong></td><td></td></tr><tr><td><strong>datum</strong></td><td></td></tr><tr><td><strong>section</strong></td><td>45.20 Deg N</td></tr><tr><td><strong>range</strong></td><td>PD 176</td></tr><tr><td><strong>township</strong></td><td>63.75 Deg W</td></tr><tr><td><strong>ekb</strong></td><td>94.8</td></tr><tr><td><strong>egl</strong></td><td>90.3</td></tr><tr><td><strong>gl</strong></td><td>90.3</td></tr><tr><td><strong>tdd</strong></td><td>1935.0</td></tr><tr><td><strong>tdl</strong></td><td>1935.0</td></tr><tr><td><strong>td</strong></td><td>None</td></tr><tr><td><strong>data</strong></td><td>CALI, DPHI_DOL, DPHI_LIM, DPHI_SAN, DRHO, DT, DTS, GR, HCAL, NPHI_DOL, NPHI_LIM, NPHI_SAN, PEF, RHOB, RLA1, RLA2, RLA3, RLA4, RLA5, RM_HRLT, RT_HRLT, RXOZ, RXO_HRLT, SP</td></tr></table>"], "text/plain": ["Well(uwi: 'Long = 63* 45'24.460  W', name: 'Kennetcook #2', 24 curves: ['CALI', 'HCAL', 'PEF', 'DT', 'DTS', 'DPHI_SAN', 'DPHI_LIM', 'DPHI_DOL', 'NPHI_SAN', 'NPHI_LIM', 'NPHI_DOL', 'RLA5', 'RLA3', 'RLA4', 'RLA1', 'RLA2', 'RXOZ', 'RXO_HRLT', 'RT_HRLT', 'RM_HRLT', 'DRHO', 'RHOB', 'GR', 'SP'])"]}, "execution_count": 3, "metadata": {}, "output_type": "execute_result"}], "source": ["well = project[0]\n", "\n", "well"]}, {"cell_type": "markdown", "metadata": {}, "source": ["The well's `header` contains the well information from the **WELL** part of the file.\n", "\n", "**PLEASE NOTE** The `header` attribute is under active development and will change in the next release of `welly`. We will make it more natural to find basic information about the well, without having to know how to read an LAS file."]}, {"cell_type": "code", "execution_count": 4, "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>original_mnemonic</th>\n", "      <th>mnemonic</th>\n", "      <th>unit</th>\n", "      <th>value</th>\n", "      <th>descr</th>\n", "      <th>section</th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>0</th>\n", "      <td>VERS</td>\n", "      <td>VERS</td>\n", "      <td></td>\n", "      <td>2.0</td>\n", "      <td></td>\n", "      <td>Version</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1</th>\n", "      <td>WRAP</td>\n", "      <td>WRAP</td>\n", "      <td></td>\n", "      <td>YES</td>\n", "      <td></td>\n", "      <td>Version</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2</th>\n", "      <td>STRT</td>\n", "      <td>STRT</td>\n", "      <td>M</td>\n", "      <td>1.0668</td>\n", "      <td>START DEPTH</td>\n", "      <td>Well</td>\n", "    </tr>\n", "    <tr>\n", "      <th>3</th>\n", "      <td>STOP</td>\n", "      <td>STOP</td>\n", "      <td>M</td>\n", "      <td>1939.1376</td>\n", "      <td>STOP DEPTH</td>\n", "      <td>Well</td>\n", "    </tr>\n", "    <tr>\n", "      <th>4</th>\n", "      <td>STEP</td>\n", "      <td>STEP</td>\n", "      <td>M</td>\n", "      <td>0.1524</td>\n", "      <td>STEP</td>\n", "      <td>Well</td>\n", "    </tr>\n", "    <tr>\n", "      <th>...</th>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "    </tr>\n", "    <tr>\n", "      <th>137</th>\n", "      <td>TLI</td>\n", "      <td>TLI</td>\n", "      <td>M</td>\n", "      <td>280.0</td>\n", "      <td>Top Log Interval</td>\n", "      <td>Parameter</td>\n", "    </tr>\n", "    <tr>\n", "      <th>138</th>\n", "      <td>UWID</td>\n", "      <td>UWID</td>\n", "      <td></td>\n", "      <td></td>\n", "      <td>Unique Well Identification Number</td>\n", "      <td>Parameter</td>\n", "    </tr>\n", "    <tr>\n", "      <th>139</th>\n", "      <td>WN</td>\n", "      <td>WN</td>\n", "      <td></td>\n", "      <td>Kennetcook #2</td>\n", "      <td>Well Name</td>\n", "      <td>Parameter</td>\n", "    </tr>\n", "    <tr>\n", "      <th>140</th>\n", "      <td>EPD</td>\n", "      <td>EPD</td>\n", "      <td>M</td>\n", "      <td>90.300003</td>\n", "      <td>Elevation of Permanent Datum above Mean Sea Level</td>\n", "      <td>Parameter</td>\n", "    </tr>\n", "    <tr>\n", "      <th>141</th>\n", "      <td></td>\n", "      <td>UNKNOWN</td>\n", "      <td></td>\n", "      <td></td>\n", "      <td></td>\n", "      <td>Other</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "<p>142 rows \u00d7 6 columns</p>\n", "</div>"], "text/plain": ["    original_mnemonic mnemonic unit          value  \\\n", "0                VERS     VERS                 2.0   \n", "1                WRAP     WRAP                 YES   \n", "2                STRT     STRT    M         1.0668   \n", "3                STOP     STOP    M      1939.1376   \n", "4                STEP     STEP    M         0.1524   \n", "..                ...      ...  ...            ...   \n", "137               TLI      TLI    M          280.0   \n", "138              UWID     UWID                       \n", "139                WN       WN       Kennetcook #2   \n", "140               EPD      EPD    M      90.300003   \n", "141                    UNKNOWN                       \n", "\n", "                                                 descr    section  \n", "0                                                         Version  \n", "1                                                         Version  \n", "2                                          START DEPTH       Well  \n", "3                                           STOP DEPTH       Well  \n", "4                                                 STEP       Well  \n", "..                                                 ...        ...  \n", "137                                   Top Log Interval  Parameter  \n", "138                  Unique Well Identification Number  Parameter  \n", "139                                          Well Name  Parameter  \n", "140  Elevation of Permanent Datum above Mean Sea Level  Parameter  \n", "141                                                         Other  \n", "\n", "[142 rows x 6 columns]"]}, "execution_count": 4, "metadata": {}, "output_type": "execute_result"}], "source": ["well.header"]}, {"cell_type": "markdown", "metadata": {}, "source": ["The well's `location` contains the location info from **PARAMS**:"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"text/plain": ["Location({'position': None, 'crs': CRS({}), 'location': 'Lat = 45* 12\\' 34.237\" N', 'country': 'CA', 'province': 'Nova Scotia', 'latitude': '', 'longitude': '', 'datum': '', 'section': '45.20 Deg N', 'range': 'PD 176', 'township': '63.75 Deg W', 'ekb': 94.8, 'egl': 90.3, 'gl': 90.3, 'tdd': 1935.0, 'tdl': 1935.0, 'td': None, 'deviation': None})"]}, "execution_count": 5, "metadata": {}, "output_type": "execute_result"}], "source": ["well.location"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Basic plots\n", "\n", "Welly produces simple `matplotlib` plots. You can add your own Matplotlib code to build on them.\n", "\n", "Let's plot some important logs. We can put two logs in the same track, as shown, and add depth tracks:"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["<Figure size 1008x864 with 7 Axes>"]}, "execution_count": 6, "metadata": {}, "output_type": "execute_result"}], "source": ["tracks = ['MD', 'CALI', 'GR', 'SP', 'RHOB', ['DT', 'DTS'], 'MD']\n", "\n", "well.plot(tracks=tracks)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Curve data\n", "\n", "The well curves are stored in `well.data`, which is a dictionary mapping mnemonic to `welly.Curve` object:"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"text/plain": ["{'CALI': Curve(mnemonic=CALI, units=in, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'HCAL': Curve(mnemonic=HCAL, units=in, start=1.0668, stop=1939.1376, step=0.1524, count=[2139]),\n", " 'PEF': Curve(mnemonic=PEF, units=, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'DT': Curve(mnemonic=DT, units=us/ft, start=1.0668, stop=1939.1376, step=0.1524, count=[10850]),\n", " 'DTS': Curve(mnemonic=DTS, units=us/ft, start=1.0668, stop=1939.1376, step=0.1524, count=[10850]),\n", " 'DPHI_SAN': Curve(mnemonic=DPHI_SAN, units=m3/m3, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'DPHI_LIM': Curve(mnemonic=DPHI_LIM, units=m3/m3, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'DPHI_DOL': Curve(mnemonic=DPHI_DOL, units=m3/m3, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'NPHI_SAN': Curve(mnemonic=NPHI_SAN, units=m3/m3, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'NPHI_LIM': Curve(mnemonic=NPHI_LIM, units=m3/m3, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'NPHI_DOL': Curve(mnemonic=NPHI_DOL, units=m3/m3, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RLA5': Curve(mnemonic=RLA5, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RLA3': Curve(mnemonic=RLA3, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RLA4': Curve(mnemonic=RLA4, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RLA1': Curve(mnemonic=RLA1, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RLA2': Curve(mnemonic=RLA2, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RXOZ': Curve(mnemonic=RXOZ, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RXO_HRLT': Curve(mnemonic=RXO_HRLT, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[2139]),\n", " 'RT_HRLT': Curve(mnemonic=RT_HRLT, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RM_HRLT': Curve(mnemonic=RM_HRLT, units=ohm.m, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'DRHO': Curve(mnemonic=DRHO, units=g/cm3, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'RHOB': Curve(mnemonic=RHOB, units=g/cm3, start=1.0668, stop=1939.1376, step=0.1524, count=[12707]),\n", " 'GR': Curve(mnemonic=GR, units=gAPI, start=1.0668, stop=1939.1376, step=0.1524, count=[12718]),\n", " 'SP': Curve(mnemonic=SP, units=mV, start=1.0668, stop=1939.1376, step=0.1524, count=[12718])}"]}, "execution_count": 7, "metadata": {}, "output_type": "execute_result"}], "source": ["well.data"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Let's assign `gr` to the gamma-ray log so we can inspect it more easily:"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"text/html": ["<table><tr><th style=\"text-align:center;\" colspan=\"2\">GR [gAPI]</th></tr><tr><td style=\"text-align:center;\" colspan=\"2\">1.0668 : 1939.1376 : 0.1524</td></tr><tr><td><strong>index_units</strong></td><td>m</td></tr><tr><td><strong>code</strong></td><td>None</td></tr><tr><td><strong>description</strong></td><td>Gamma-Ray</td></tr><tr><td><strong>log_type</strong></td><td>None</td></tr><tr><td><strong>api</strong></td><td>None</td></tr><tr><td><strong>date</strong></td><td>10-Oct-2007</td></tr><tr><td><strong>null</strong></td><td>-999.25</td></tr><tr><td><strong>run</strong></td><td>1</td></tr><tr><td><strong>service_company</strong></td><td>Schlumberger</td></tr><tr><td><strong>_alias</strong></td><td>GR</td></tr><tr><th style=\"border-top: 2px solid #000; text-align:center;\" colspan=\"2\"><strong>Stats</strong></th></tr><tr><td><strong>samples (NaNs)</strong></td><td>12718 (0)</td></tr><tr><td><strong><sub>min</sub> mean <sup>max</sup></strong></td><td><sub>3.89</sub> 78.986 <sup>267.94</sup></td></tr><tr><th style=\"border-top: 2px solid #000;\">Depth</th><th style=\"border-top: 2px solid #000;\">Value</th></tr><tr><td>1.0668</td><td>46.6987</td></tr><tr><td>1.2192</td><td>46.6987</td></tr><tr><td>1.3716</td><td>46.6987</td></tr><tr><td>\u22ee</td><td>\u22ee</td></tr><tr><td>1938.8328</td><td>92.2462</td></tr><tr><td>1938.9852</td><td>92.2462</td></tr><tr><td>1939.1376</td><td>92.2462</td></tr></table>"], "text/plain": ["Curve(mnemonic=GR, units=gAPI, start=1.0668, stop=1939.1376, step=0.1524, count=[12718])"]}, "execution_count": 8, "metadata": {}, "output_type": "execute_result"}], "source": ["gr = well.data['GR']\n", "\n", "gr"]}, {"cell_type": "markdown", "metadata": {}, "source": ["It's often helpful to make a quick plot:"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/plain": ["<AxesSubplot:title={'center':'GR'}, xlabel='gAPI'>"]}, "execution_count": 9, "metadata": {}, "output_type": "execute_result"}, {"data": {"image/png": 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\n", "text/plain": ["<Figure size 144x720 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["gr.plot()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Curve data as a `pandas.DataFrame`\n", "\n", "The `df` attribute (attributes are like ordinary variables; they do not have parentheses after them) of a single curve is a dataframe:"]}, {"cell_type": "code", "execution_count": 10, "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", "    </tr>\n", "    <tr>\n", "      <th>DEPT</th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>1.0668</th>\n", "      <td>46.69865036</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.2192</th>\n", "      <td>46.69865036</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.3716</th>\n", "      <td>46.69865036</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.5240</th>\n", "      <td>46.69865036</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.6764</th>\n", "      <td>46.69865036</td>\n", "    </tr>\n", "    <tr>\n", "      <th>...</th>\n", "      <td>...</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.5280</th>\n", "      <td>92.24622345</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.6804</th>\n", "      <td>92.24622345</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.8328</th>\n", "      <td>92.24622345</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.9852</th>\n", "      <td>92.24622345</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1939.1376</th>\n", "      <td>92.24622345</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "<p>12718 rows \u00d7 1 columns</p>\n", "</div>"], "text/plain": ["                    GR\n", "DEPT                  \n", "1.0668     46.69865036\n", "1.2192     46.69865036\n", "1.3716     46.69865036\n", "1.5240     46.69865036\n", "1.6764     46.69865036\n", "...                ...\n", "1938.5280  92.24622345\n", "1938.6804  92.24622345\n", "1938.8328  92.24622345\n", "1938.9852  92.24622345\n", "1939.1376  92.24622345\n", "\n", "[12718 rows x 1 columns]"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["gr.df"]}, {"cell_type": "markdown", "metadata": {}, "source": ["And you can get at all of the well data in a similar way, except that this is a **method** not an attribute."]}, {"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>CALI</th>\n", "      <th>HCAL</th>\n", "      <th>PEF</th>\n", "      <th>DT</th>\n", "      <th>DTS</th>\n", "      <th>DPHI_SAN</th>\n", "      <th>DPHI_LIM</th>\n", "      <th>DPHI_DOL</th>\n", "      <th>NPHI_SAN</th>\n", "      <th>NPHI_LIM</th>\n", "      <th>...</th>\n", "      <th>RLA1</th>\n", "      <th>RLA2</th>\n", "      <th>RXOZ</th>\n", "      <th>RXO_HRLT</th>\n", "      <th>RT_HRLT</th>\n", "      <th>RM_HRLT</th>\n", "      <th>DRHO</th>\n", "      <th>RHOB</th>\n", "      <th>GR</th>\n", "      <th>SP</th>\n", "    </tr>\n", "    <tr>\n", "      <th>DEPT</th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></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>1.0668</th>\n", "      <td>2.4438154697</td>\n", "      <td>4.3912849426</td>\n", "      <td>3.5864000320</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.1574800014</td>\n", "      <td>0.1984400004</td>\n", "      <td>0.2590999901</td>\n", "      <td>0.4650999904</td>\n", "      <td>0.3364700079</td>\n", "      <td>...</td>\n", "      <td>0.0320999995</td>\n", "      <td>0.0279399995</td>\n", "      <td>0.0576100014</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0550099984</td>\n", "      <td>0.1942329407</td>\n", "      <td>2.3901498318</td>\n", "      <td>46.69865036</td>\n", "      <td>120.1250</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.2192</th>\n", "      <td>2.4438154697</td>\n", "      <td>4.3912849426</td>\n", "      <td>3.5864000320</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.1574800014</td>\n", "      <td>0.1984400004</td>\n", "      <td>0.2590999901</td>\n", "      <td>0.4650999904</td>\n", "      <td>0.3364700079</td>\n", "      <td>...</td>\n", "      <td>0.0320999995</td>\n", "      <td>0.0279399995</td>\n", "      <td>0.0576100014</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0550099984</td>\n", "      <td>0.1942329407</td>\n", "      <td>2.3901498318</td>\n", "      <td>46.69865036</td>\n", "      <td>120.1250</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.3716</th>\n", "      <td>2.4438154697</td>\n", "      <td>4.3912849426</td>\n", "      <td>3.5864000320</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.1574800014</td>\n", "      <td>0.1984400004</td>\n", "      <td>0.2590999901</td>\n", "      <td>0.4650999904</td>\n", "      <td>0.3364700079</td>\n", "      <td>...</td>\n", "      <td>0.0320999995</td>\n", "      <td>0.0279399995</td>\n", "      <td>0.0576100014</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0550099984</td>\n", "      <td>0.1942329407</td>\n", "      <td>2.3901498318</td>\n", "      <td>46.69865036</td>\n", "      <td>120.1250</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.5240</th>\n", "      <td>2.4438154697</td>\n", "      <td>4.3912849426</td>\n", "      <td>3.5864000320</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.1574800014</td>\n", "      <td>0.1984400004</td>\n", "      <td>0.2590999901</td>\n", "      <td>0.4650999904</td>\n", "      <td>0.3364700079</td>\n", "      <td>...</td>\n", "      <td>0.0320999995</td>\n", "      <td>0.0279399995</td>\n", "      <td>0.0576100014</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0550099984</td>\n", "      <td>0.1942329407</td>\n", "      <td>2.3901498318</td>\n", "      <td>46.69865036</td>\n", "      <td>120.1250</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.6764</th>\n", "      <td>2.4438154697</td>\n", "      <td>4.3912849426</td>\n", "      <td>3.5864000320</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.1574800014</td>\n", "      <td>0.1984400004</td>\n", "      <td>0.2590999901</td>\n", "      <td>0.4650999904</td>\n", "      <td>0.3364700079</td>\n", "      <td>...</td>\n", "      <td>0.0320999995</td>\n", "      <td>0.0279399995</td>\n", "      <td>0.0576100014</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0255800001</td>\n", "      <td>0.0550099984</td>\n", "      <td>0.1942329407</td>\n", "      <td>2.3901498318</td>\n", "      <td>46.69865036</td>\n", "      <td>120.1250</td>\n", "    </tr>\n", "    <tr>\n", "      <th>...</th>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "      <td>...</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.5280</th>\n", "      <td>2.4202680588</td>\n", "      <td>NaN</td>\n", "      <td>2.2369799614</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.5464199781</td>\n", "      <td>585.9415283200</td>\n", "      <td>541.6757202100</td>\n", "      <td>0.1283400059</td>\n", "      <td>0.0841699988</td>\n", "      <td>...</td>\n", "      <td>274.0264892600</td>\n", "      <td>663.1040649400</td>\n", "      <td>7.1023502350</td>\n", "      <td>NaN</td>\n", "      <td>7.3863301277</td>\n", "      <td>0.0272899996</td>\n", "      <td>0.0613951497</td>\n", "      <td>NaN</td>\n", "      <td>92.24622345</td>\n", "      <td>73.4375</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.6804</th>\n", "      <td>2.4202680588</td>\n", "      <td>NaN</td>\n", "      <td>2.2369799614</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.5464199781</td>\n", "      <td>585.9415283200</td>\n", "      <td>541.6757202100</td>\n", "      <td>0.1283400059</td>\n", "      <td>0.0841699988</td>\n", "      <td>...</td>\n", "      <td>274.0264892600</td>\n", "      <td>663.1040649400</td>\n", "      <td>7.1022100449</td>\n", "      <td>NaN</td>\n", "      <td>7.3860998154</td>\n", "      <td>0.0272899996</td>\n", "      <td>0.0613951497</td>\n", "      <td>NaN</td>\n", "      <td>92.24622345</td>\n", "      <td>73.6875</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.8328</th>\n", "      <td>2.4202680588</td>\n", "      <td>NaN</td>\n", "      <td>2.2369799614</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.5464199781</td>\n", "      <td>585.9415283200</td>\n", "      <td>541.6757202100</td>\n", "      <td>0.1283400059</td>\n", "      <td>0.0841699988</td>\n", "      <td>...</td>\n", "      <td>274.0264892600</td>\n", "      <td>663.1040649400</td>\n", "      <td>7.0968699455</td>\n", "      <td>NaN</td>\n", "      <td>7.3806500435</td>\n", "      <td>0.0272899996</td>\n", "      <td>0.0613951497</td>\n", "      <td>NaN</td>\n", "      <td>92.24622345</td>\n", "      <td>73.0000</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.9852</th>\n", "      <td>2.4202680588</td>\n", "      <td>NaN</td>\n", "      <td>2.2369799614</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.5464199781</td>\n", "      <td>585.9415283200</td>\n", "      <td>541.6757202100</td>\n", "      <td>0.1283400059</td>\n", "      <td>0.0841699988</td>\n", "      <td>...</td>\n", "      <td>274.0264892600</td>\n", "      <td>663.1040649400</td>\n", "      <td>7.0391001701</td>\n", "      <td>NaN</td>\n", "      <td>7.3211698532</td>\n", "      <td>0.0272899996</td>\n", "      <td>0.0613951497</td>\n", "      <td>NaN</td>\n", "      <td>92.24622345</td>\n", "      <td>73.9375</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1939.1376</th>\n", "      <td>2.4202680588</td>\n", "      <td>NaN</td>\n", "      <td>2.2369799614</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>0.5464199781</td>\n", "      <td>585.9415283200</td>\n", "      <td>541.6757202100</td>\n", "      <td>0.1283400059</td>\n", "      <td>0.0841699988</td>\n", "      <td>...</td>\n", "      <td>274.0264892600</td>\n", "      <td>663.1040649400</td>\n", "      <td>7.0019497871</td>\n", "      <td>NaN</td>\n", "      <td>7.1535902023</td>\n", "      <td>0.0272899996</td>\n", "      <td>0.0613951497</td>\n", "      <td>NaN</td>\n", "      <td>92.24622345</td>\n", "      <td>74.2500</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "<p>12718 rows \u00d7 24 columns</p>\n", "</div>"], "text/plain": ["                   CALI          HCAL           PEF  DT  DTS      DPHI_SAN  \\\n", "DEPT                                                                         \n", "1.0668     2.4438154697  4.3912849426  3.5864000320 NaN  NaN  0.1574800014   \n", "1.2192     2.4438154697  4.3912849426  3.5864000320 NaN  NaN  0.1574800014   \n", "1.3716     2.4438154697  4.3912849426  3.5864000320 NaN  NaN  0.1574800014   \n", "1.5240     2.4438154697  4.3912849426  3.5864000320 NaN  NaN  0.1574800014   \n", "1.6764     2.4438154697  4.3912849426  3.5864000320 NaN  NaN  0.1574800014   \n", "...                 ...           ...           ...  ..  ...           ...   \n", "1938.5280  2.4202680588           NaN  2.2369799614 NaN  NaN  0.5464199781   \n", "1938.6804  2.4202680588           NaN  2.2369799614 NaN  NaN  0.5464199781   \n", "1938.8328  2.4202680588           NaN  2.2369799614 NaN  NaN  0.5464199781   \n", "1938.9852  2.4202680588           NaN  2.2369799614 NaN  NaN  0.5464199781   \n", "1939.1376  2.4202680588           NaN  2.2369799614 NaN  NaN  0.5464199781   \n", "\n", "                 DPHI_LIM        DPHI_DOL      NPHI_SAN      NPHI_LIM  ...  \\\n", "DEPT                                                                   ...   \n", "1.0668       0.1984400004    0.2590999901  0.4650999904  0.3364700079  ...   \n", "1.2192       0.1984400004    0.2590999901  0.4650999904  0.3364700079  ...   \n", "1.3716       0.1984400004    0.2590999901  0.4650999904  0.3364700079  ...   \n", "1.5240       0.1984400004    0.2590999901  0.4650999904  0.3364700079  ...   \n", "1.6764       0.1984400004    0.2590999901  0.4650999904  0.3364700079  ...   \n", "...                   ...             ...           ...           ...  ...   \n", "1938.5280  585.9415283200  541.6757202100  0.1283400059  0.0841699988  ...   \n", "1938.6804  585.9415283200  541.6757202100  0.1283400059  0.0841699988  ...   \n", "1938.8328  585.9415283200  541.6757202100  0.1283400059  0.0841699988  ...   \n", "1938.9852  585.9415283200  541.6757202100  0.1283400059  0.0841699988  ...   \n", "1939.1376  585.9415283200  541.6757202100  0.1283400059  0.0841699988  ...   \n", "\n", "                     RLA1            RLA2          RXOZ      RXO_HRLT  \\\n", "DEPT                                                                    \n", "1.0668       0.0320999995    0.0279399995  0.0576100014  0.0255800001   \n", "1.2192       0.0320999995    0.0279399995  0.0576100014  0.0255800001   \n", "1.3716       0.0320999995    0.0279399995  0.0576100014  0.0255800001   \n", "1.5240       0.0320999995    0.0279399995  0.0576100014  0.0255800001   \n", "1.6764       0.0320999995    0.0279399995  0.0576100014  0.0255800001   \n", "...                   ...             ...           ...           ...   \n", "1938.5280  274.0264892600  663.1040649400  7.1023502350           NaN   \n", "1938.6804  274.0264892600  663.1040649400  7.1022100449           NaN   \n", "1938.8328  274.0264892600  663.1040649400  7.0968699455           NaN   \n", "1938.9852  274.0264892600  663.1040649400  7.0391001701           NaN   \n", "1939.1376  274.0264892600  663.1040649400  7.0019497871           NaN   \n", "\n", "                RT_HRLT       RM_HRLT          DRHO          RHOB  \\\n", "DEPT                                                                \n", "1.0668     0.0255800001  0.0550099984  0.1942329407  2.3901498318   \n", "1.2192     0.0255800001  0.0550099984  0.1942329407  2.3901498318   \n", "1.3716     0.0255800001  0.0550099984  0.1942329407  2.3901498318   \n", "1.5240     0.0255800001  0.0550099984  0.1942329407  2.3901498318   \n", "1.6764     0.0255800001  0.0550099984  0.1942329407  2.3901498318   \n", "...                 ...           ...           ...           ...   \n", "1938.5280  7.3863301277  0.0272899996  0.0613951497           NaN   \n", "1938.6804  7.3860998154  0.0272899996  0.0613951497           NaN   \n", "1938.8328  7.3806500435  0.0272899996  0.0613951497           NaN   \n", "1938.9852  7.3211698532  0.0272899996  0.0613951497           NaN   \n", "1939.1376  7.1535902023  0.0272899996  0.0613951497           NaN   \n", "\n", "                    GR        SP  \n", "DEPT                              \n", "1.0668     46.69865036  120.1250  \n", "1.2192     46.69865036  120.1250  \n", "1.3716     46.69865036  120.1250  \n", "1.5240     46.69865036  120.1250  \n", "1.6764     46.69865036  120.1250  \n", "...                ...       ...  \n", "1938.5280  92.24622345   73.4375  \n", "1938.6804  92.24622345   73.6875  \n", "1938.8328  92.24622345   73.0000  \n", "1938.9852  92.24622345   73.9375  \n", "1939.1376  92.24622345   74.2500  \n", "\n", "[12718 rows x 24 columns]"]}, "execution_count": 11, "metadata": {}, "output_type": "execute_result"}], "source": ["well.df()"]}, {"cell_type": "markdown", "metadata": {}, "source": [" It has to be a method because we can pass in extra options like aliases."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Curve aliases\n", "\n", "We can make a dictionary mapping alias names (what we want to call curves) to a list of mnemonics (what they are actually called). The list of mnemonics is *ordered*, and this order expresses your preference. So, for example, in the alias dictionary below, the **GR** log will be used in preference to the **GAM** log."]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": ["alias = {\n", "    \"Gamma\": [\"GR\", \"GAM\", \"GRC\", \"SGR\", \"NGT\"],\n", "    \"Density\": [\"RHOZ\", \"RHOB\", \"DEN\", \"RHOZ\"],\n", "    \"Sonic\": [\"DT\", \"AC\", \"DTP\", \"DT4P\"],\n", "    \"Caliper\": [\"CAL\", \"CALI\", \"CALS\", \"C1\"],\n", "    'Porosity SS': ['NPSS', 'DPSS'],\n", "}"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Lots of methods in `welly` take an alias. Welly will use the alias dictionary to decide what to show. \n", "\n", "Here, the `keys` argument narrows down the columns to include in the dataframe."]}, {"cell_type": "code", "execution_count": 13, "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>Gamma</th>\n", "      <th>Density</th>\n", "      <th>Sonic</th>\n", "      <th>DTS</th>\n", "    </tr>\n", "    <tr>\n", "      <th>DEPT</th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>1.0668</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.2192</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.3716</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.5240</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.6764</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</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", "    </tr>\n", "    <tr>\n", "      <th>1938.5280</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.6804</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.8328</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.9852</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1939.1376</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "<p>12718 rows \u00d7 4 columns</p>\n", "</div>"], "text/plain": ["                 Gamma       Density  Sonic  DTS\n", "DEPT                                            \n", "1.0668     46.69865036  2.3901498318    NaN  NaN\n", "1.2192     46.69865036  2.3901498318    NaN  NaN\n", "1.3716     46.69865036  2.3901498318    NaN  NaN\n", "1.5240     46.69865036  2.3901498318    NaN  NaN\n", "1.6764     46.69865036  2.3901498318    NaN  NaN\n", "...                ...           ...    ...  ...\n", "1938.5280  92.24622345           NaN    NaN  NaN\n", "1938.6804  92.24622345           NaN    NaN  NaN\n", "1938.8328  92.24622345           NaN    NaN  NaN\n", "1938.9852  92.24622345           NaN    NaN  NaN\n", "1939.1376  92.24622345           NaN    NaN  NaN\n", "\n", "[12718 rows x 4 columns]"]}, "execution_count": 13, "metadata": {}, "output_type": "execute_result"}], "source": ["well.df(keys=['Gamma', 'Density', 'Sonic', 'DTS'], alias=alias)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["There are a lot of NaNs there, but if we just wanted to see the middle of the well, we can pass in a `basis` to narrow it down (and even resample the data if we want).\n", "\n", "Let's look at 1000 to 1500 m, resampled to 1 m sample interval:"]}, {"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>Gamma</th>\n", "      <th>Density</th>\n", "      <th>Sonic</th>\n", "      <th>DTS</th>\n", "    </tr>\n", "    <tr>\n", "      <th>DEPT</th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>1.0668</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.2192</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.3716</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.5240</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1.6764</th>\n", "      <td>46.69865036</td>\n", "      <td>2.3901498318</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", "    </tr>\n", "    <tr>\n", "      <th>1938.5280</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.6804</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.8328</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1938.9852</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1939.1376</th>\n", "      <td>92.24622345</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "      <td>NaN</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "<p>12718 rows \u00d7 4 columns</p>\n", "</div>"], "text/plain": ["                 Gamma       Density  Sonic  DTS\n", "DEPT                                            \n", "1.0668     46.69865036  2.3901498318    NaN  NaN\n", "1.2192     46.69865036  2.3901498318    NaN  NaN\n", "1.3716     46.69865036  2.3901498318    NaN  NaN\n", "1.5240     46.69865036  2.3901498318    NaN  NaN\n", "1.6764     46.69865036  2.3901498318    NaN  NaN\n", "...                ...           ...    ...  ...\n", "1938.5280  92.24622345           NaN    NaN  NaN\n", "1938.6804  92.24622345           NaN    NaN  NaN\n", "1938.8328  92.24622345           NaN    NaN  NaN\n", "1938.9852  92.24622345           NaN    NaN  NaN\n", "1939.1376  92.24622345           NaN    NaN  NaN\n", "\n", "[12718 rows x 4 columns]"]}, "execution_count": 14, "metadata": {}, "output_type": "execute_result"}], "source": ["basis = range(1000, 1501)\n", "\n", "well.df(keys=['Gamma', 'Density', 'Sonic', 'DTS'], alias=alias, basis=basis)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Curve quality\n", "\n", "We can check the quality of curves with a dictionary of tests. There are some predefined tests in the `welly.quality` module, but you can write your own functions and pass them in instead (the function should take a curve as its argument, and return `True` if the test passed)."]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": ["import welly.quality as q\n", "\n", "tests = {\n", "    'Each': [\n", "        q.no_flat,\n", "        q.no_monotonic,\n", "        q.no_gaps,\n", "    ],\n", "    'Gamma': [\n", "        q.all_positive,\n", "        q.all_below(450),\n", "        q.check_units(['API', 'GAPI']),\n", "    ],\n", "    'DT': [\n", "        q.all_positive,\n", "    ],\n", "    'Sonic': [\n", "        q.all_between(1, 10000),  # 1333 to 5000 m/s\n", "        q.no_spikes(10),          # 10 spikes allowed\n", "    ],\n", "}"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": ["passed = well.qc_data(tests, alias=alias)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["This returns a dictionary of curves in which the values are dictionaries of **test name: test result** pairs."]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"text/plain": ["{'CALI': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'HCAL': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'PEF': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'DT': {'no_flat': True,\n", "  'no_monotonic': True,\n", "  'no_gaps': True,\n", "  'all_positive': True,\n", "  'all_between': True,\n", "  'no_spikes': False},\n", " 'DTS': {'no_flat': True, 'no_monotonic': True, 'no_gaps': True},\n", " 'DPHI_SAN': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'DPHI_LIM': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'DPHI_DOL': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'NPHI_SAN': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'NPHI_LIM': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'NPHI_DOL': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RLA5': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RLA3': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RLA4': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RLA1': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RLA2': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RXOZ': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RXO_HRLT': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RT_HRLT': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RM_HRLT': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'DRHO': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'RHOB': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True},\n", " 'GR': {'no_flat': False,\n", "  'no_monotonic': False,\n", "  'no_gaps': True,\n", "  'all_positive': True,\n", "  'all_below': True,\n", "  'check_units': False},\n", " 'SP': {'no_flat': False, 'no_monotonic': False, 'no_gaps': True}}"]}, "execution_count": 17, "metadata": {}, "output_type": "execute_result"}], "source": ["passed"]}, {"cell_type": "markdown", "metadata": {}, "source": ["There's also an HTML table for rendering in Notebooks:"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [{"data": {"text/html": ["<table><tr><th>Curve</th><th>Passed</th><th>Score</th><th>all_below</th><th>no_flat</th><th>all_positive</th><th>no_monotonic</th><th>no_spikes</th><th>check_units</th><th>all_between</th><th>no_gaps</th></tr><tr><th>CALI</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>HCAL</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>PEF</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DT</th><td>5 / 6</td><td>0.833</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:#CCEECC;\">True</td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DTS</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:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DPHI_SAN</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DPHI_LIM</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DPHI_DOL</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>NPHI_SAN</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>NPHI_LIM</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>NPHI_DOL</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RLA5</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RLA3</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RLA4</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RLA1</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RLA2</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RXOZ</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RXO_HRLT</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RT_HRLT</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>RM_HRLT</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>DRHO</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></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>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>GR</th><td>3 / 6</td><td>0.500</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:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#CCEECC;\">True</td></tr><tr><th>SP</th><td>1 / 3</td><td>0.333</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></td><td style=\"background-color:#FFCCCC;\">False</td><td style=\"background-color:#EEEEEE;\"></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": 18, "metadata": {}, "output_type": "execute_result"}], "source": ["from IPython.display import HTML\n", "\n", "html = well.qc_table_html(tests, alias=alias)\n", "HTML(html)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Add a striplog\n", "\n", "In principle, Welly can hold data from anywhere. Let's add data from another source. [Striplog](https://code.agilescientific.com/striplog) can create a geological log from an image or a CSV. Let's try it:"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [{"data": {"image/png": 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Iyii8xELuNlvPpE+dvwfnHb6y6eE0Kt2pgqrNMiFnXosKFlSwDCqFl5jCS0zhJRayYNFLvMqEvgxi5r77+299bnw/JXTtEfvoMohBFHK32aLzPHSeN6hCzzxdBqGXeOWWbbepl3iVCRmelFF4iSm8xBReYuGrTRldyJmnarNMyJnXopP07XiSbmZ/BpwKGPB5d/+Umc0GLgf2BO4HTnD3tXXvhQuA44ANwLvd/Yedvr/WNtk+J+lmtj9VcIcABwJvMrO9gTOBb7r7IuCb9ecAbwQW1f9OAy7q9mdLpZdj3quA77n7hrqx0/8D3szm3bpGdvH6kldupmpbs2sPP3/c6yW8O4HXmdkcM9uRane4OzDP3R+q7/NLYF798YtdvGrtHb5e1N7Fa92GuE8UR9BLO5q7zewTwPXAr4HbgOdH3MfNbJsScPdlVG1t2Gf+BKXXQU+nCu5+sbsf7O6/Q9Wl8j+Ah1u7w/r/R+q7v9jFq9be4Uu60GvP2JfV/+9Bdby7hM27dY3s4vUuqxwGrGvbvUoXej3P+4qZzQGeA0539yfM7FzgCjM7BXgAOKG+7zVUx8XVVKcK79naN9d53nY8z3P3121h22NUvfRGbnfg9F5+nmwu5PKY3lCgTMjw9BKvMiHDkzIKLzGFl5jCSyz083kL7n2ajx9zd9PDaNaz+4x6U8jw2t8N4sP/PL4b/l7b4baQu02dKpQJGZ6UUXiJKbzEFF5iIcPTwnSZkOGp2iwTMjwpo/ASU3iJKbzEQq9t7sYuWpjusDAdcua1qs0ZNq3poYQWMjwpo/ASU3iJhSxYWh5cNIUPf05Pxo4m5MzT2maZkOFpbbNMyPCkjMJLLHTBoneDIN9bNkqZkDNPb19VJuTM09tXlQkZnpRReIkpvMQUXmIKLzGdKiQWcubpVKFMyPCkjMJLTOElpvASU7WZWMiZp2qzTMjwpEzI3WaL3iy185ulauYlpvASCxmeLrotY9VbP8e0z/wJfuGpOzQ9jEa9/iPPjFpyh5x5Umar4ZnZCjN7xMzubNs228xWmtm99f+z6u1mZp82s9VmdruZHdT2NSfX97/XzE7e0s+SbVMy874IHDti2zZ16qrbsp0DHErV9eucVuDSva2G5+43AY+P2LytnbqOAVa6++PuvhZYyUv/IGQbdXvM29ZOXUUdvEBdvLZFzwVL3amkb4+yuy9z9yXuvmTmjlrb7KTb8La1U5c6eG0H3Ya3rZ26rgOONrNZdaFydL1NerDVhWkzuxQ4HJhrZmuoqsZt6tTl7o+b2ceAW+r7fdTdRxZBso22Gp67nzTKTdvUqcvdVwArtml00lHIp4T0THqZkMtjeia9TMjwpIzCSyzkMa9Fl0HoMoiBpfASC7nbbJ0qvGL3yVw16y1ND6dhd4x6S8iZ1zpVmDk95PDC0KOTmMJLTOElpvASCxle66LbdU+90PRQQgsZnqrNMnp0ElN4iSm8xBReYiHDU7VZJmR4qjbL6NFJTOElpvASU3iJhQxP1WaZkOGp2iyjRycxhZeYwktM4SUWMjxVm2VChqdqs4wencQUXmIKLzGFl5jCSyxkeDpVKBMyPJ0qlNGjk5jCS0zhJabwEgsZnqrNMiHDU7VZRo9OYgovMYWXmMJLLGR4qjbLhAxP1WYZPTqJddvF621mtsrMXjCzJSPuf1bdxesnZnZM2/Zj622rzexMpGfddvG6E3gzcFP7RjPbDzgReHX9NRea2UQzmwh8lqrL137ASfV9pQclfRVuMrM9R2y7G8DsJe++vhS4zN2fAX5mZqupWq4BrHb3++qvu6y+7109jX6c6/cxr69dvB594vk+D2+whCtY2rt47bzTxKaHE1q/36a4U7cudfHqs37PvKuBE81syMwWUrUf/T5VA6hFZrbQzCZTFTVX9/lnjzvddvF6HPg/wM7Av5nZbe5+jLuvMrMrqAqRjcDp7v58/X3OoGq7NhFY4e6rtscvNJ6E7pN+8H5T/TuX7N30MBo1tPiOXH3StbZZJmR4Wtsso0cnMYWXmMJLTOElpvASCxmeThXKhAxPpwpl9OgkpvASU3iJKbzEQoanarNMyPBUbZbRo5NYyFbbLauffwVL136l6WE06toOt4V+Jn1o4rDvNuWwpofRqJ/++vpcz6RLmZC7TTM7Hjh+kk1teiihhZx5rWpzgoX82wojZHhSRuElpvASU3iJhawIVG2WCTnzVG2WCf3oTNl7DxZ97jNNDyOs0OFNn2q89oDQQ2xUyN2mlFF4iYXcJ7Wqzanz9+Df79jY9HCadcToN4Wcea1qc4fpM5oeSmghw5MyejI2OD0ZO6AUXmIKL7HQpwpamO4s5MzTwnSZkOFJGYWXmMJLTOElFrIiULVZJuTMU7VZJmR4UkbhJabwElN4iYWsCFRtlgk581RtlgkZnpTptovX35nZPWZ2u5l9zcx2artNXbzGSLddvFYC+7v7bwD/AZwF6uI11rYanrvfRNUEo33b9e7euqDyZqr2MtDWxcvdfwa0ungdQt3Fy92fBVpdvKQH/TjmvRf4v/XHfe3i9YI/14fhDa6eyjkz+zBV25kv92c4VRcvYBnAjJ2HfY+l4/yK6Q66Ds/M3g28CTjKN138qS5eY6ir8MzsWOBDwO+6+4a2m64GLjGzfwDms6mLl1F38aIK7UTgD7b2c559HH5+6Tg/11s++k3ddvE6CxgCVtatR2929/epi9fYCn25+4ydh33J0iVbv+MA+9byG0e93D3kPql9bVO7zdFvCrk8prXNMiHDkzIKLzGFl1jog8rk2aAVltFp5iUWcua1ThWmzNBlEJ2EPknXa9L1mvSBpfASU3iJKbzEQlebuui2s5AzTwvTZUKGJ2UUXmIKL7HQBxUtTHcWMjytbZYJudtsVZuThkL+bYURMjwpo/ASC71fGl7wco48t8O1b+OcZl5iIcMzs+PNbNnT659seiihhQyvVW1OGVZfhU5CXwah1yp0fq1CyJknZRReYgovsZDneVrbLBNy5mlts0zoalMX3eqi24Gl8BJTeIkpvMRClnO66LZMyPDc/evA12fsPHyqLkAanXabiSm8xHSSHpxO0gdUyIJF1WaZkDNPL/EqEzI8KaPwEgu9X9KrhDrTzEss5MzTZRBlQs48XQZRJvSjoxeadNZtF6+P1R28bjOz681sfr3dzOzTdaeu283soLavOdnM7q3/nbx9fp3xpdsuXn/n7r/h7ouBbwB/XW9/I1UjjEXAacBFAGY2m6ofw6FUTaHOMbNZvQ5+vOu2i9f6tk+nAa3V7aXAl7xyM7CTme0KHAOsdPfH3X0tVQu3kX8Qso166SX0ceBdwDrgiHpzX7p4Uc1aZu42v9vhjQtdV5vu/mF3352qg9cZ/RqQuy9z9yXuvmTanNn9+rYDqR+nCl8G3lJ/PFoXr07dvaRL3XbxWuTu99afLgXuqT++GjjDzC6jKk7WuftDZnYd8LdtRcrR1K1KO1n/4APceOYfdjPEgXH28htHva3bLl7Hmdm+wAvAA8D76rtfAxxH1W50A/AeAHd/3Mw+BtxS3++j7r5ZESTbLvRlEHplrLp45aYuXoMpZHhSRuElpvASU3iJKbzEQpZzuui2TMiZp1OFMiHDkzIKLzGFl5jCSyxkRaBqs0zI8PSGAmVCP5+nlzXrZc0DS+ElpvASC1mwqNosE3LmaW2zTOhHRy9r7izkzJMyCi8xhZdYyGOeLrpto4tuB1PI8KSMwktM4SUW+qCik/TOQoanarONqs3BFDI8KaPwElN4iYU+qKja7EwzL7GQM691qjB7od5vs5OQM691qjBleEbTQwktZHhSJvQV03oHpM7vgBQ6PF3ursvdB1boalMX3XYWcuZpYbpMyPCkjMJLTOElpvASC1kRqNosE3LmqdosE/rR0fN5nXXVxavttv9hZm5mc+vP1cVrDHXbxQsz252qucXP2zari9cY6qqLV+184ENs6uAF6uI1prptR7MUeNDdf2y22aJ3X7t4TbIpuui2w4UE2/zImNmOwF9R7TL7zt2XAcugekpoe/yMQdHNqcIrgIXAj83sfqqOXD80s11QF68xtc3hufsd7v4yd9/T3fek2gUe5O6/pOri9a666jyMuosXcB1wtJnNqguVo+tt0oOSU4VLge8C+5rZGjM7pcPdrwHuo+ri9Xng/VB18QJaXbxuQV28+kKXQQTX6TKIkKWc1jbLaG0zsZDhSZnQf9pT9t6DRZ/7TNPDCEszLzGFl5jCSyxkeGZ2vJkte+6pJ5seSmghw2udKuwwXS/x6iRkeFJGy2PB6VVCA0on6YmFnHmqNsuEDE/VZpmQ4UkZVZvBqdocUAovsZCnCroMokzImafLIMqEfnR0kt5ZyJknZRReYgovsZDHvPZq8943ndH0cJr16+tHvSnkzFO1WSZkeFJG4SUWer+k87zONPMSCxmenkkvEzI8PZNeJmR4UkbPpAenZ9IHlMJLTOElFvIkXZdBlAk587QwXSZkeFJG4SWm8BJTeImFrAhUbZYJvTy2YPEB/r4brmp6GI06e+5eud71r+Wp/3L+/Y5x3lfhiNFv0jEvsdAzb/pU47UHhB5io0I/Mtptkm+3qcsgyoSuNvVkrJ6MHVhbPeaZ2QrgTcAj7r5/ve1/A6cCj9Z3+yt3v6a+7SzgFOB54E/d/bp6+7HABcBEYLm7n7u1n60WbJ113cULON/dF9f/WsHtB5wIvLr+mgvNbKKZTQQ+S9Xlaz/gpPq+0oOtzjx3v8nM9iz8fkuBy9z9GeBnZraaquUawGp3vw/AzC6r73vXtg9ZWno55p1RNzhc0dYLry9dvMzsVjO79bn/eraH4Q2+bsO7iKoh1GLgIeDv+zUgd1/m7kvcfckOUyf369sOpK5O0t394dbHZvZ54Bv1p526damLV591NfPqbpQt/x1o9ZO9GjjRzIbMbCFV+9HvUzV/WmRmC81sMlVRc3X3wxYoO1W4FDgcmGtma6h6vx5uZoupWo7eD/wRgLuvMrMrqAqRjcDp7v58/X3OoGq7NhFY4e6r+v3LjDdaYQlOXbwGVMjlMV23WSZkeFJG4SUWer+khenONPMSU3iJhdxttk4VpszQqUInIWde61Rh0lDIv60wQoYnZUL/aQ8veDlHnru86WGEFXptc8bOw75k6ZKmh9Goby2/UVePDaKQu01Vm2VCzjxVm2VChidlFF5iCi8xhZdYyIqgVW3OXqiT9E50kh6cTtIHVMjdZovWNjvTzEtMx7zgOh3zQu42tbZZJuRuU2ubZUI/OipYOtMxL7h0x7wWzbzONPOCSzfztLZZJnS1OWVYXbw60W4zOC1MDyiFl1jIgqVFpwqdaeYlFrJgaVuYPvWwE8b3W3mkK1i0MF0mZHhSRuElpvASU3iJhawIdBlEmZAzT9VmmZDhSRmFl5jCS0zhJRayIlC1WSbkzFO1WSZkeFJmq+HV7WYeMbM7R2z/EzO7x8xWmdkn27afZWarzewnZnZM2/Zj622rzezM/v4a41PJfumLwGeAL7U2mNkRVI2cDnT3Z8zsZfX29i5e84EbzGyf+ss+C7yBqo/QLWZ2tburEVQPuu3i9cfAuXW3Ltz9kXq7uniNoW4rgn2A15nZx4GngQ+6+y1Unblubrtfe7eukV28Dt3SNzaz04DTAGbuNl/XsHTQbcEyCZgNHAb8JXCFmY36dP22aO/iNW3O7H58y4HV7cxbA3zVqwtgvm9mLwBz6XMXr/UPPsCNZ/5hl0McDGcvv3HU27qdef9K3cG7LkgmA79CXbzGVLddvFYAK+rTh2eBk+tZqC5eYyjkpX8teq1C4pd4aW2zs5DLY1rbLBMyPCmj8BJTeIkpvMQUXmIhyzmdKpQJOfN0qlAmZHhSRuElpvASU3iJhawIVG2WCTnzVG2WCRmelAn9ZOzQxGHfbcr4fh+Wn/76+lzvwyJlFF5iISuC9mpzjxM2Nj2csELOPFWbZUKGJ2VC/2nr/TY708xLLPR5ni661UW3AyvkblPVZpmQ4UkZhZdY6P2SThU6U7UZnKrNARXymKdqs0zI8KSMwktM4SWm8BJTeImFLOd0qlAm5MzTqUKZkOFJmdB/2lrb7Exrm8Gl61wpZULuNlVtlgk581RtlgkZnpRReIkpvMQUXmIhKwJVm2VCzjxVm2VChidluuriZWaXm9lt9b/7zey2ttvUxWuMdNXFy93f3vrYzP4eWFd/rC5eY6jbLl4A1P2DTgCOrDf1tYuXnlXorNeK4HXAw+5+b/15X7t4DU0bUi+h7dBLqOUk4NIev8dm2rt47TB1cj+/9cDpeuaZ2STgzcDBbZv72sVLOutl5r0euMfd17RtUxevMVRyqnAp8F1gXzNbY2an1DedyIhdZt2Zq9XF61rqLl7uvhFodfG6G7hCXbx6p8sggtNLvAZUyOUxrW2WCf3o6CS9Mx3zgtOlfwNK4SWm8BILWbDoVKFMyJmnU4UyIcOTMgovMYWXmMJLLGRFoGqzTMiZp2qzTOhHRwvTnWlhOrh0T8a2aOZ1ppkXXLqZp2qzTOiZt2DxAf6+G65qehiNOnvuXqPOvNDhabepZ9IHlsJLTOElpmozsZAzT2ubZUKGJ2UUXmKh90ta2+xMMy+xkOGZ2fFmtuzp9U82PZTQQobXqjanDM9oeiihhQxPyii8xBReYgovMYWXWMgnY9sWpk897ITDmh5Oo9I9GauF6TIhw5MyCi8xhZeYwkssZEWgyyDKhJx5qjbLhH509GRsZyFP0lt0xXTCk3Qpo/ASC3nMU7VZJuTMU7VZJmR4UqbbLl6LzezmuovXrWZ2SL3dzOzTdaeu283soLavOdnM7q3/nbx9fp3xpWTmfRE4dsS2TwIfcffFwF/XnwO8kaoRxiKqfkAXAZjZbOAcqv5BhwDnmNmsHsc+7nXbxcuB4frjmcAv6o+XAl/y6uTxZjPbycx2BQ4HVrr74wBmtpLqD6JjHyKdpHfWbUXw58B1ZnYe1ex9Tb19AS/t1rWgw/aXUBevzW2PLl5/DHzA3XcHPgBc3OX3eQl18SrXbXgnA1+tP/4XNjU4HK2LV6fuXtKlbsP7BfC79cdHAq3mh1cD76qrzsOAde7+EFUDqKPNbFZdqBxdb5MebPWYV3fxOhyYa2ZrqKrGU4EL6h56T1Mfo4BrgOOA1cAG4D0A7v64mX2MqhUbwEdbxYt0r6TaPGmUmw4euaGuMk8f5fusAFZs0+iko5DrT1rbLBNyeUxrm2VChidlFF5iCi8xhZeYwkssZDmnU4UyIWeeThXKhAxPyii8xBReYgovsZAVgarNMiFnnqrNMiHDkzIKLzGFl5jCSyxkRaBqs0zImadqs0zI8KSMwktM4SUW+qCil3h1FvJ9WPRmqZukex8WVZtlQoYnZUL/aeuY15lmXmIhC5YWvXFc54Il5G5Ta5tlQu42VW2WCRmelFF4iSm8xBReYgovsZDlnE4VyoSceTpVKBP60dHaZmchZ56UUXiJKbzEQoZnZseb2bKn1z/Z9FBCCxleq9qcMjyj6aGEFjI8KaPwElN4iSm8xEKGp2qzjC5ACi7dFdNSptsuXgea2XfN7A4z+7qZDbfddlbdxesnZnZM2/Zj622rzezM/v8q40+3XbyWA2e6+wHA14C/BDCz/YATgVfXX3OhmU00s4nAZ6m6fO0HnFTfV3qw1fDc/SZgZAOLfYCb6o9XAm+pP14KXObuz7j7z6iaYxxS/1vt7ve5+7PAZfV9pQfdPp+3iurB/1fgbWzqE7QAuLntfu3dukZ28Tp0S9+4vYvXzN3m6/m8DrotWN4LvN/MfgDMAJ7t14Dau3hNmzO7X992IHU189z9HqpmTpjZPsDv1Td16talLl591lV4ZvYyd3/EzCYA/wv4XH3T1cAlZvYPwHyq9qPfBwxYZGYLqUI7EfiDrf2cZ+97jgdO+sXW7jbYVu416k3ddvGabmathk9fBb4A4O6rzOwK4C5gI3C6uz9ff58zqNquTQRWuPuqbn8fqYReYdl5+JW+9NDxXbAsX/nbOV/iNWPqFtvKSi3k8ljrmfShSdObHkpoIcOTMgovMYWXmMJLTOElplOFxELOPJ0qlAkZnpRReIkpvMQUXmKqNhMLOfNUbZYJGZ6UCf1krJld6+4jrxmVWujwpDPtNhNTeIkpvMQUXmIKL7H/Dywe9AwZQM11AAAAAElFTkSuQmCC\n", "text/plain": ["<Figure size 108x1080 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["from striplog import Legend, Striplog\n", "\n", "legend = Legend.builtin('NSDOE')\n", "strip = Striplog.from_image('https://geocomp.s3.amazonaws.com/data/P-129_280_1935.png', 280, 1935, legend=legend)\n", "strip.plot()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Add this to the well data:"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": ["well.data['strip'] = strip"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["<Figure size 864x864 with 6 Axes>"]}, "execution_count": 21, "metadata": {}, "output_type": "execute_result"}], "source": ["tracks = ['MD', 'strip', 'GR', 'RHOB', ['DT', 'DTS'], 'MD']\n", "\n", "well.plot(tracks=tracks)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Write a LAS file\n", "\n", "At any point, you can write out a new LAS file.\n", "\n", "Let's write a new file with only the DT and DTS logs, and a different NULL value to the original:"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": ["well.to_las('out.las', keys=['DT', 'DTS'], null_value=-111.111)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["You can perform a shell command in Jupyter Notebooks by putting a `!` before the command. So on Linux, here's how we can check the new file exists:"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["-rw-rw-r-- 1 matt matt 434247 Feb 13 14:22 out.las\r\n"]}], "source": ["!ls -l out.las"]}, {"cell_type": "code", "execution_count": 24, "metadata": {"scrolled": true}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["~Version ---------------------------------------------------\r\n", "VERS.   2.0 : CWLS log ASCII Standard -VERSION 2.0\r\n", "WRAP.    NO : One line per depth step\r\n", "DLM . SPACE : Column Data Section Delimiter\r\n", "~Well ------------------------------------------------------\r\n", "STRT  .m                    1.06680 : START DEPTH\r\n", "STOP  .m                 1939.13760 : STOP DEPTH\r\n", "STEP  .m                    0.15240 : STEP\r\n", "NULL  .                    -111.111 : NULL VALUE\r\n", "COMP  . Elmworth Energy Corporation : COMPANY\r\n", "WELL  .               Kennetcook #2 : WELL\r\n", "FLD   .               Windsor Block : FIELD\r\n"]}], "source": ["!head -12 out.las"]}, {"cell_type": "markdown", "metadata": {}, "source": ["---\n", "\n", "&copy; 2022 Agile Scientific, CC BY"]}], "metadata": {"kernelspec": {"display_name": "Python 3 (ipykernel)", "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": "3.9.7"}}, "nbformat": 4, "nbformat_minor": 1}