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资源说明：Inverse model to quantify subsurface temperatures and their uncertainty from borehole temperature data
# PyBHT
## Description
PyBHT is a model code that calculates formation temperature from time
series of three or more bottom hole temperatures (BHT) recorded at the same
depth. The model simulates cooling as a result of drilling and the
subsequent thermal recovery using an explicit finite difference
solution of the radial heat flow equation.
Formation and borehole temperature are calibrated using the downhill
simplex algorithm provided by Scipy.
## Installation
- Clone pyBHT or download and unpack the zip file at the right hand side
- Navigate to the pyBHT folder and run the model code from a terminal, IDLE
or your favorite python editor::
python PyBHT.py
- The model will now calibrate the formation and mud temperature for 2 example
BHT datasets from the Roer Valley Graben in the Netherlands
## Usage
- Use a text editor or excel to construct a .csv file containing bottom hole
temperature input data. An example file is located in: `/input/BHTinput.csv`
- Use a text editor to adjust the default model parameters or the names of the
BHT input files in the model parameter file `PyBHT_params.py`
- The thermal parameters of the formation rocks surrounding the borehole,
pore water, and drilling mud are located in the files:
`input/litho_params.csv`, `input/water_params.csv` and
`input/mud_params.csv`. Adjust these if needed.
- For each BHT series you can specify a lithology type, pore water type and
drilling mud type in the file `/input/BHTinput.csv`. The model will look for
the lithology, water type and mud type in the thermal parameter .csv files
and assign thermal parameters accordingly.
- The model calculates the bulk thermal conductivity, density and specific heat
of the formation using data on porosity and the thermal parameters of the
pore water and formation specified in `input/litho_params.csv` and
input/water_params.csv. Porosity can be assigned directly for each BHT
series in the file `input/BHTinput.csv`.
- If porosity is not specified in `input/BHTinput.csv` (ie. the porosity column
is left empty), porosity for each BHT series will be calculated using an
exponential porosity-depth equation:
phi = phi0 * exp(-compressibility * depth)
- The phi_0 and compressibility parameters for each lithology are specified in
the file `input/litho_params.csv`
- After running the model a .csv file that contains the model results,
including the calibrated formation temperatures is stored in the folder
`results/`. See `results/BHTout.csv` for an example of the output
- A figure of the model results for each BHT series is created automatically
and stored in the folder `fig/`
## Dependencies
PyBHT requires the following python packages:
* Python 2.x: http://www.python.org/
* NumPy: http://www.scipy.org/NumPy
* Matplotlib: http://matplotlib.sourceforge.net/
* SciPy: http://www.scipy.org/
* Pandas: http://pandas.pydata.org/
## Reference
Please cite the following article if you publish work that uses PyBHT:
Luijendijk, E., M. Ter Voorde, R.T. Van Balen, H. Verweij, E. Simmelink. (2011)
Thermal state of the Roer Valley Graben, part of the European Cenozoic Rift System.
Basin Research, 23(1), 65-82. DOI: 10.1111/j.1365-2117.2010.00466.x
A bibtex file of this citation can be found in the PyBHT folder
You can find a copy of the paper at:
http://dx.doi.org/10.1111/j.1365-2117.2010.00466.x.
Contact me by email if you do not have access to this journal.
## License
PyBHT is distributed under the GNU General Public License, version 3:
http://www.gnu.org/copyleft/gpl.html
A copy of this license is distributed along with PyBHT, see: gpl-3.0.txt
Elco Luijendijk
November 2014
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