| Index | UWI | Data | Curves |
|---|
| 0 | 11A | 21 curves | ABDCQF01, ABDCQF02, ABDCQF03, ABDCQF04, BS, CALI, DRHO, DT, DTS, GR, NPHI, PEF, RACEHM, RACELM, RD, RHOB, RM, ROP, RPCEHM, RPCELM, RT |
| 1 | 11B | 19 curves | ABDCQF01, ABDCQF02, ABDCQF03, ABDCQF04, BS, CALI, DRHO, GR, NPHI, PEF, RACEHM, RACELM, RD, RHOB, RM, ROP, RPCEHM, RPCELM, RT |
| 2 | 1A | 19 curves | ABDCQF01, ABDCQF02, ABDCQF03, ABDCQF04, BS, CALI, DRHO, DT, DTS, GR, NPHI, PEF, RACEHM, RACELM, RHOB, ROP, RPCEHM, RPCELM, RT |
| 3 | 1B | 22 curves | ABDCQF01, ABDCQF02, ABDCQF03, ABDCQF04, BS, CALI, DRHO, DT, DTS, GR, NBGRCFM, NPHI, PEF, RACEHM, RACELM, RD, RHOB, RM, ROP, RPCEHM, RPCELM, RT |
| 4 | 1C | 20 curves | ABDCQF01, ABDCQF02, ABDCQF03, ABDCQF04, BS, CALI, DRHO, GR, NBGRCFM, NPHI, PEF, RACEHM, RACELM, RD, RHOB, RM, ROP, RPCEHM, RPCELM, RT |
"
- ],
- "text/plain": [
- "Project(5 wells: 11A, 11B, 1A, 1B, 1C)"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "11A\n",
+ "11B\n",
+ "1A\n",
+ "1B\n",
+ "1C\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\n"
+ ]
}
],
"source": [
- "#Create a project class with all the well logs\n",
"p = Project.from_las('./*.las')\n",
- "#Print summary of imported files\n",
- "p"
+ "print(p)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Export data to a Pandas dataframe for scientific computing workflows"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "> Pandas can provide a seamless integration into existing workflows and databases. However, the Welly library provides an intitutive way of working with well and logs rather instead of dataframes.\n",
+ "\n",
+ ">The output displays the well logs of well 11A from 2500m to 3000m stored in the Pandas dataframe."
]
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 4,
"metadata": {},
"outputs": [
{
@@ -481,20 +511,33 @@
"[5000 rows x 22 columns]"
]
},
- "execution_count": 5,
+ "execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "#Data can be exported to a pandas dataframe to switch to classic scintific computing workflows\n",
"df_wells = p.df()\n",
"df_wells.loc['11A'].query('Depth > 2500 & Depth < 3000')"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Create a Well object from the project"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "> A well object 'well_11A' is created from the Project. The output prints the header of the LAS file."
+ ]
+ },
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 5,
"metadata": {},
"outputs": [
{
@@ -506,29 +549,51 @@
"Well(uwi: '11A', 21 curves: ['ABDCQF01', 'ABDCQF02', 'ABDCQF03', 'ABDCQF04', 'BS', 'CALI', 'DRHO', 'DT', 'DTS', 'GR', 'NPHI', 'PEF', 'RACEHM', 'RACELM', 'RD', 'RHOB', 'RM', 'ROP', 'RPCEHM', 'RPCELM', 'RT'])"
]
},
- "execution_count": 6,
+ "execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "#Create a well object from the project\n",
"well_11A = p.get_well('11A')\n",
"well_11A"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Plotting"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Plot Gamma ray and NPHI-RHOB well logs"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "> The object segment stores a section of the well log. The section is defined by a basis which can either be the Depth or Time data\n",
+ ">The depth of the Hugin formation in the 11A well is 3600m to 3700m. Gamma ray, Neutron Porosity, Density and Deep resistivity logs are segmented for analysis. \n",
+ ">The Output displays the Gamma ray log and also indicates the overlay of the Density and Neutron Porosity logs. The wells here are made using the Plotly library but other pltting libraries can easily be integrated"
+ ]
+ },
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "