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bluebonnet-0.2.0
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مشاهده بیشترتوضیحات
Scaling solutions for production analysis from unconventional oil and gas wells
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | bluebonnet-0.2.0 |
| نام | bluebonnet |
| نسخه کتابخانه | 0.2.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | - |
| ایمیل نویسنده | Frank Male <frank.male@psu.edu>, Michael Marder <marder@chaos.utexas.edu> |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/bluebonnet/ |
| مجوز | BSD 3-Clause License Copyright (c) 2021, Frank Male All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
# bluebonnet
Scaling solutions for production analysis from unconventional oil and gas wells.
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## Installation
Run the command
```bash
pip install bluebonnet
```
## Usage
`bluebonnet` has a collection of tools for performing reservoir simulation in
tight oil and shale gas reservoirs. The main tools are:
1. `fluids` for modeling PVT and viscosity of oil, water, and gas;
2. `flow` for building physics-based production curves; and
3. `forecast` for fitting and forecasting unconventional production.
Examples can be found in
[the documentation](https://bluebonnet.readthedocs.io/en/latest).
## Contributing
Interested in contributing? Check out the
[contributing guidelines](https://bluebonnet.readthedocs.io/en/latest/contributing.html)
to get started. Please note that this project is released with a Code of
Conduct. By contributing to this project, you agree to abide by its terms.
### Contributor Hall of Fame
Michael Marder
## License
`bluebonnet` was created by Frank Male. It is licensed under the terms of the
BSD 3-Clause license.
## Credits
This work was funded in part by an ExxonMobil grant to the University of Texas
at Austin, with Michael Marder as PI and Larry Lake as co-PI. The Physics-based
scaling curve was developed for shale gas reservoirs by Patzek et al. (2013). It
was extended to tight oil by Male (2019). It was extended to two-phase by Ruiz
Maraggi et al. (2020). It was extended to include variable fracture face
pressure by Ruiz Maraggi et al. (2021). In the future, it might be extended
further.
`bluebonnet` was created with
[`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the
`py-pkgs-cookiecutter`
[template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
## Bibliography
Papers developing or using this approach include:
1. Patzek, T. W., Male, F. and Marder, M., 2013. "Gas production in the Barnett
Shale obeys a simple scaling theory," Proceedings of the National Academy of
Science. https://doi.org/10.1073/pnas.1313380110
1. Patzek, T. W., Male, F. and Marder, M., 2014. "A simple model of gas
production from hydrofractured horizontal wells in shales," AAPG Bulletin v.
98, no. 12. https://doi.org/10.1306/03241412125
1. Male, F., Islam, A.W., Patzek, T.W., Ikonnikova, S.A., Browning, J.R., and
Marder, M.P., 2015. "Analysis of gas production from hydraulically fractured
wells in the Haynesville shale using scaling methods." Journal of
Unconventional Oil and Gas Resources.
https://doi.org/10.1016/j.juogr.2015.03.001
1. Male, F., 2015. Application of a one dimensional nonlinear model to flow in
hydrofractured shale gas wells using scaling solutions (Doctoral
dissertation). https://repositories.lib.utexas.edu/handle/2152/46706
1. Eftekhari, B., Marder, M. and Patzek, T.W., 2018. Field data provide
estimates of effective permeability, fracture spacing, well drainage area and
incremental production in gas shales. Journal of Natural Gas Science and
Engineering, 56, pp.141-151. https://doi.org/10.1016/j.jngse.2018.05.027
1. Male, F. 2019, "Assessing impact of uncertainties in decline curve analysis
through hindcasting." Journal of Petroleum Science and Engineering, 172,
340-348. https://doi.org/10.1016/j.petrol.2018.09.072
1. Male, F. 2019, "Using a segregated flow model to forecast production of oil,
gas, and water in shale oil wells." Journal of Petroleum Science and
Engineering, 180, 48-61. https://doi.org/10.1016/j.petrol.2019.05.010
1. Patzek, T.W., Saputra, W., Kirati, W. and Marder, M., 2019. "Generalized
extreme value statistics, physical scaling, and forecasts of gas production
in the Barnett shale." Energy & fuels, 33(12), pp.12154-12169.
https://doi.org/10.1021/acs.energyfuels.9b01385
1. Ruiz Maraggi, L.M., Lake, L.W. and Walsh, M.P., 2020. "A Two-Phase Non-Linear
One-Dimensional Flow Model for Reserves Estimation in Tight Oil and Gas
Condensate Reservoirs Using Scaling Principles." In SPE Latin American and
Caribbean Petroleum Engineering Conference. OnePetro.
https://doi.org/10.2118/199032-MS
1. Ruiz Maraggi, L.M., Lake, L.W. and Walsh, M.P., 2020. "A Bayesian Framework
for Addressing the Uncertainty in Production Forecasts of Tight Oil
Reservoirs Using a Physics-Based Two-Phase Flow Model." In SPE/AAPG/SEG Latin
America Unconventional Resources Technology Conference. OnePetro.
https://doi.org/10.15530/urtec-2020-10480
1. Maraggi, L.M.R., Lake, L.W. and Walsh, M.P., 2021. Deconvolution of
Time-Varying Bottomhole Pressure Improves Rate-Time Models History Matches
and Forecasts of Tight-Oil Wells Production. In SPE/AAPG/SEG Unconventional
Resources Technology Conference. OnePetro.
1. Ruiz Maraggi, L.M., Lake, L.W., and Walsh. M.P., 2022 "Rate-Pseudopressure
Deconvolution Enhances Rate-Time Models Production History Matches and
Forecasts of Shale Gas Wells." Paper presented at the SPE Canadian Energy
Technology Conference, Calgary, Alberta, Canada, March 2022. doi:
https://doi.org/10.2118/208967-MS
1. Ruiz Maraggi, L.M., Lake, L.W. and Walsh, M.P., 2022. Deconvolution Overcomes
the Limitations of Rate Normalization and Material Balance Time in
Rate-Transient Analysis of Unconventional Reservoirs. In SPE Canadian Energy
Technology Conference. OnePetro.
1. Male, F., Duncan, I.J., 2022, "The Paradox of Increasing Initial Oil
Production but Faster Decline Rates in Fracking the Bakken Shale:
Implications for Long Term Productivity of Tight Oil Plays," Journal of
Petroleum Science and Engineering,
https://doi.org/10.1016/j.petrol.2021.109406
1. Ruiz Maraggi, L.M., 2022. Production analysis and forecasting of shale
reservoirs using simple mechanistic and statistical modeling (Doctoral
dissertation). http://dx.doi.org/10.26153/tsw/42112
نیازمندی
| مقدار | نام |
|---|---|
| - | lmfit>=1.0 |
| - | matplotlib>=3.4.3 |
| - | numpy>=1.22 |
| - | pandas>=1.3.4 |
| - | scipy>=1.7.1 |
| xtr | jupyter>=1.0.0; |
| xtr | pre-commit>=2.19; |
| xtr | myst-nb>=0.13.1; |
| xtr | sphinx-autoapi>=1.8.4; |
| xtr | sphinx-rtd-theme>=1.0.0; |
| xtr | sphinx>=5.0.2; |
| xtr | pytest-cov>=2.12.1; |
| xtr | pytest-mpl>=0.16; |
| xtr | pytest-xdist>=2.4; |
| xtr | pytest>=6.2; |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| <3.12,>=3.8 | Python |
نحوه نصب
نصب پکیج whl bluebonnet-0.2.0:
pip install bluebonnet-0.2.0.whl
نصب پکیج tar.gz bluebonnet-0.2.0:
pip install bluebonnet-0.2.0.tar.gz