Research Data for "A Spatial-Stochastic Framework for Evaluating Technical Performance, Economic Viability, and Optimal Deployment of Distributed Fibre-Optic Sensing for Underground Oil Pipeline Monitoring"
Description
This dataset contains the Microsoft Excel simulation model, Oracle Crystal Ball implementation, Python scripts, input datasets, and supporting files used in the probabilistic technical, economic, and spatial deployment optimisation of Distributed Fibre-Optic Sensing (DFOS) for underground oil pipeline monitoring.
Files
Steps to reproduce
1. Open the Excel simulation workbook. 2. Create 5 worksheets (Input Data, Segment Analytics, Events Analysis, Forecasts, and Economic Model) 3. Populate Input parameters, Segment Analytics, and Event Analysis sheets. 4. Launch Oracle Crystal Ball. 5. Load the assumption and forecast cells and populate Forecast &Economic Model sheets. 6. Run the Monte Carlo simulation using the settings described in the manuscript. 7. Create a Post-Simulation Analysis Sheet and populate with simulation results (Segment VOIs) for optimal deployment analysis. 8. Export the trial values and key forecast statistics from Crystal Ball to MS Excel. 9. Execute the Python script to regenerate all published figures.
Institutions
- University of Port HarcourtRivers State, Port Harcourt