oilgas-analysis 0.1.0

A package for oil and gas well analysis

Oil and Gas Analysis Package

This package provides tools for analyzing well logs, generating IPR curves, predicting reservoir performance, and selecting candidates for artificial lift in the oil and gas industry.

Installation

pip install oilgas_analysis

Usage

Well Log Analysis

from oilgas_analysis import load_well_log_data, analyze_well_log

# Load well log data
log_data = load_well_log_data('well_log.csv')

# Analyze well log
analysis_results = analyze_well_log(log_data)
print(analysis_results)

IPR Curve Generation

from oilgas_analysis import generate_ipr_curve, plot_ipr_curve

# Generate IPR curve
pressures, rates = generate_ipr_curve(reservoir_pressure=3000, bubble_point_pressure=2500, productivity_index=2.5, water_cut=0.2)

# Plot IPR curve
plot_ipr_curve(pressures, rates, title="Well X IPR Curve")

Reservoir Performance Prediction

from oilgas_analysis import predict_reservoir_performance, forecast_production
import numpy as np

# Historical production data
time = np.array([0, 30, 60, 90, 120])
production_data = np.array([1000, 950, 905, 865, 830])

# Predict reservoir performance
params = predict_reservoir_performance(time, production_data)

# Forecast future production
forecast_time, forecast_rates = forecast_production(params, time_horizon=24)
print(f"Forecasted production after 2 years: {forecast_rates[-1]:.2f} STB/day")

Artificial Lift Analysis

from oilgas_analysis import select_artificial_lift_candidates, analyze_lift_performance

# Select artificial lift candidates
wells_data = [
    {'name': 'Well A', 'production_rate': 40, 'economic_limit': 50, 'reservoir_pressure': 2000, 'bottomhole_pressure': 1000, 'water_cut': 0.3},
    {'name': 'Well B', 'production_rate': 60, 'economic_limit': 50, 'reservoir_pressure': 1800, 'bottomhole_pressure': 1200, 'water_cut': 0.5},
    {'name': 'Well C', 'production_rate': 30, 'economic_limit': 50, 'reservoir_pressure': 2200, 'bottomhole_pressure': 1100, 'water_cut': 0.8}
]

candidates = select_artificial_lift_candidates(wells_data)
print(f"Candidates for artificial lift: {candidates}")

# Analyze lift performance
initial_rate = 50
time = np.array([0, 30, 60, 90])
lifted_rates = np.array([100, 95, 92, 90])
lift_type = 'ESP'

lift_analysis = analyze_lift_performance(initial_rate, time, lifted_rates, lift_type)
print(lift_analysis)

Running the Package

To run this package:

1. Install the package and its dependencies:

   pip install oilgas_analysis
   

2. Create a Python script (e.g., analysis_script.py) and import the necessary functions as shown in the usage examples above.

3. Run your script:

   python analysis_script.py
   

Running Tests

To run the test suite:

1. Ensure you have the package and its dependencies installed.
2. Navigate to the root directory of the package.
3. Run the following command:

   python -m unittest discover tests
   

This will discover and run all the tests in the tests directory.

Contributing

Contributions to this package are welcome. Please ensure that you add or update tests as appropriate when making changes. Follow these steps to contribute:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Write your code and tests.
4. Run the test suite to ensure all tests pass.
5. Submit a pull request with a clear description of your changes.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any questions or issues, please open an issue on the GitHub repository or contact the maintainer at [[e-mail]].