wellpy.las.read_v1_2 example

wellpy.las.read_v1_2.ipynb

{
 "metadata": {
  "name": ""
 },
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 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import glob\n",
      "fns = glob.glob(r'f:\\code\\las\\examples\\1.2\\*.las')\n",
      "pprint.pprint(fns)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "['f:\\\\code\\\\las\\\\examples\\\\1.2\\\\1475IBK3.las',\n",
        " 'f:\\\\code\\\\las\\\\examples\\\\1.2\\\\4ALS.las',\n",
        " 'f:\\\\code\\\\las\\\\examples\\\\1.2\\\\5_1.las',\n",
        " 'f:\\\\code\\\\las\\\\examples\\\\1.2\\\\sample.las',\n",
        " 'f:\\\\code\\\\las\\\\examples\\\\1.2\\\\sample_big.las',\n",
        " 'f:\\\\code\\\\las\\\\examples\\\\1.2\\\\sample_curve_api.las',\n",
        " 'f:\\\\code\\\\las\\\\examples\\\\1.2\\\\sample_minimal.las',\n",
        " 'f:\\\\code\\\\las\\\\examples\\\\1.2\\\\sample_wrapped.las']\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import wellpy"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "6210 wellpy._logging:27 <module> : Initiated logging of calls >= DEBUG\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "log = wellpy.read_las(fns[2])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "125818 wellpy.las:58 get_text : opening f:\\code\\las\\examples\\1.2\\5_1.las\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "125819 wellpy.las:78 detect_version : LAS version 1.20\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "125891 wellpy.las:226 read_v1_2 : Replaced -9999.0 with NaN\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "125894 wellpy.las:45 read_las : elapsed time 0.0759999752045 s\n"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "type(log)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "wellpy.las.LAS"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "log.data.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x7eda170>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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iIpqt/nTw4EHcd999KCwsRHBwMORyOSZPnowHH3wQ69evt4hOY5AnT9gD8t7tj0N48p0N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\nHh6YaeIVQ6dJLBLBx8kJMrW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4U1AQHjXhO/ybTIZVJSU4bMIFV6XV4rvbt3Gyrg6/yWS4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\nogdDQZ4gCKIH8/8BuMD939WF7yIAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7ee3770>"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print log"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "{'Curves': {'DEPT': {'api_code': None,\n",
        "                     'data': 25.0    25.0\n",
        "25.2    25.2\n",
        "25.4    25.4\n",
        "25.6    25.6\n",
        "25.8    25.8\n",
        "26.0    26.0\n",
        "26.2    26.2\n",
        "26.4    26.4\n",
        "26.6    26.6\n",
        "26.8    26.8\n",
        "27.0    27.0\n",
        "27.2    27.2\n",
        "27.4    27.4\n",
        "27.6    27.6\n",
        "27.8    27.8\n",
        "...\n",
        "407.2    407.2\n",
        "407.4    407.4\n",
        "407.6    407.6\n",
        "407.8    407.8\n",
        "408.0    408.0\n",
        "408.2    408.2\n",
        "408.4    408.4\n",
        "408.6    408.6\n",
        "408.8    408.8\n",
        "409.0    409.0\n",
        "409.2    409.2\n",
        "409.4    409.4\n",
        "409.6    409.6\n",
        "409.8    409.8\n",
        "410.0    410.0\n",
        "Name: DEPT, Length: 1926, dtype: float64,\n",
        "                     'mnemonic': 'DEPT',\n",
        "                     'name': 'Depth curve',\n",
        "                     'order': 1,\n",
        "                     'unit': 'M'},\n",
        "            'DS': {'api_code': None,\n",
        "                   'data': 25.0       NaN\n",
        "25.2       NaN\n",
        "25.4    0.3332\n",
        "25.6    0.3478\n",
        "25.8    0.3617\n",
        "26.0    0.3763\n",
        "26.2    0.3427\n",
        "26.4    0.3370\n",
        "26.6    0.3414\n",
        "26.8    0.3363\n",
        "27.0    0.3465\n",
        "27.2    0.3560\n",
        "27.4    0.3535\n",
        "27.6    0.3376\n",
        "27.8    0.3262\n",
        "...\n",
        "407.2   NaN\n",
        "407.4   NaN\n",
        "407.6   NaN\n",
        "407.8   NaN\n",
        "408.0   NaN\n",
        "408.2   NaN\n",
        "408.4   NaN\n",
        "408.6   NaN\n",
        "408.8   NaN\n",
        "409.0   NaN\n",
        "409.2   NaN\n",
        "409.4   NaN\n",
        "409.6   NaN\n",
        "409.8   NaN\n",
        "410.0   NaN\n",
        "Name: DS, Length: 1926, dtype: float64,\n",
        "                   'mnemonic': 'DS',\n",
        "                   'name': 'Kavernogramma',\n",
        "                   'order': 2,\n",
        "                   'unit': 'M'},\n",
        "            'PS': {'api_code': None,\n",
        "                   'data': 25.0   NaN\n",
        "25.2   NaN\n",
        "25.4   NaN\n",
        "25.6   NaN\n",
        "25.8   NaN\n",
        "26.0   NaN\n",
        "26.2   NaN\n",
        "26.4   NaN\n",
        "26.6   NaN\n",
        "26.8   NaN\n",
        "27.0   NaN\n",
        "27.2   NaN\n",
        "27.4   NaN\n",
        "27.6   NaN\n",
        "27.8   NaN\n",
        "...\n",
        "407.2   NaN\n",
        "407.4   NaN\n",
        "407.6   NaN\n",
        "407.8   NaN\n",
        "408.0   NaN\n",
        "408.2   NaN\n",
        "408.4   NaN\n",
        "408.6   NaN\n",
        "408.8   NaN\n",
        "409.0   NaN\n",
        "409.2   NaN\n",
        "409.4   NaN\n",
        "409.6   NaN\n",
        "409.8   NaN\n",
        "410.0   NaN\n",
        "Name: PS, Length: 1926, dtype: float64,\n",
        "                   'mnemonic': 'PS',\n",
        "                   'name': 'PS',\n",
        "                   'order': 4,\n",
        "                   'unit': 'MV'},\n",
        "            'PZ': {'api_code': None,\n",
        "                   'data': 25.0   NaN\n",
        "25.2   NaN\n",
        "25.4   NaN\n",
        "25.6   NaN\n",
        "25.8   NaN\n",
        "26.0   NaN\n",
        "26.2   NaN\n",
        "26.4   NaN\n",
        "26.6   NaN\n",
        "26.8   NaN\n",
        "27.0   NaN\n",
        "27.2   NaN\n",
        "27.4   NaN\n",
        "27.6   NaN\n",
        "27.8   NaN\n",
        "...\n",
        "407.2    36.31\n",
        "407.4    36.31\n",
        "407.6    36.31\n",
        "407.8    36.31\n",
        "408.0    36.37\n",
        "408.2    36.58\n",
        "408.4    36.62\n",
        "408.6    36.63\n",
        "408.8    36.51\n",
        "409.0    36.47\n",
        "409.2      NaN\n",
        "409.4      NaN\n",
        "409.6      NaN\n",
        "409.8      NaN\n",
        "410.0      NaN\n",
        "Name: PZ, Length: 1926, dtype: float64,\n",
        "                   'mnemonic': 'PZ',\n",
        "                   'name': 'Potencial-zond',\n",
        "                   'order': 3,\n",
        "                   'unit': 'OMM'}},\n",
        " 'Other': '',\n",
        " 'Parameters': {'DNOM': {'name': \"Nominal'nyi' diametr skvajiny\",\n",
        "                         'unit': 'MM',\n",
        "                         'value': 298},\n",
        "                'DTIS': {'name': \"Data okonchanija issledovanii'\",\n",
        "                         'unit': None,\n",
        "                         'value': nan},\n",
        "                'DTVR': {'name': \"00 : Data i vremja zamera krivoi'\",\n",
        "                         'unit': None,\n",
        "                         'value': nan},\n",
        "                'MSHGL': {'name': \"Masshtab glubin karotajnoi' diagrammy\",\n",
        "                          'unit': None,\n",
        "                          'value': 500},\n",
        "                'OCFR': {'name': \"Ustroi'stvo ocifrovki\",\n",
        "                         'unit': None,\n",
        "                         'value': nan},\n",
        "                'PRHJ': {'name': 'Uslovija prohojdenija pribora',\n",
        "                         'unit': None,\n",
        "                         'value': nan},\n",
        "                'SPMS': {'name': 'Sposob poluch cifrovogo massiva',\n",
        "                         'unit': None,\n",
        "                         'value': nan},\n",
        "                'TKRV': {'name': \"Tip krivoi' po sposobu preobrazovanija\",\n",
        "                         'unit': None,\n",
        "                         'value': nan}},\n",
        " 'Version': {'VERS': {'description': 'CWLS LAS  -  VERSION 1.20',\n",
        "                      'value': 1.2},\n",
        "             'WRAP': {'description': 'One line per depth step',\n",
        "                      'value': False}},\n",
        " 'Well': {'API': {'key': 'API NUMBER', 'unit': None, 'value': ''},\n",
        "          'CNTY': {'key': 'COUNTY', 'unit': None, 'value': ''},\n",
        "          'CTRY': {'key': 'COUNTRY', 'unit': None, 'value': 'Rossija'},\n",
        "          'DATE': {'key': 'LOG DATE', 'unit': None, 'value': '22.05.2006'},\n",
        "          'FLD': {'key': 'FIELD', 'unit': None, 'value': 'SHkapovskaja-JEKS'},\n",
        "          'LOC': {'key': 'LOCATION', 'unit': None, 'value': ''},\n",
        "          'NULL': {'key': 'NULL', 'unit': None, 'value': -9999.0},\n",
        "          'SRVC': {'key': 'SERVICE COMPANY',\n",
        "                   'unit': None,\n",
        "                   'value': 'SHkapovskaja PGJE'},\n",
        "          'STAT': {'key': 'STATE', 'unit': None, 'value': 'Bashkortostan'},\n",
        "          'STEP': {'key': 'STEP', 'unit': 'M', 'value': 0.2},\n",
        "          'STOP': {'key': 'STOP', 'unit': 'M', 'value': 410.0},\n",
        "          'STRT': {'key': 'STRT', 'unit': 'M', 'value': 25.0},\n",
        "          'UWI': {'key': 'UNIQUE WELL ID', 'unit': None, 'value': '5 ALS'},\n",
        "          'WELL': {'key': 'WELL', 'unit': None, 'value': '5ALS'}}}\n"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}