• Matlab

  • Sensor Planning

  • Dynamics

  • Path Planning

  • Sensor Optimization

Mobile Sensor Optimal Path Planning for Monitoring Methane Emissions in an Oil Field

Fall, 2017

01 description

This project addresses the problem of detecting methane emissions from distributed natural gas and oil field production sites using a mobile sampling vehicle that can measure methane concentrations along public roadways over a desired region of interest (ROI).  Assuming the oil field, the wells locations and the roadmap is known, the algorithm finds an optimal path for the tradeoff between the value of measurement and cost.​


Field and Roadmap for the current study*. Red circles represent the location of the wells, black lines represent the roads and the green dot represents the initial position of the sensor.    *Data provided by Prof. Silvia Ferrari


Example of a Mobile Sampling Vehicle equipped with air pollution sensors.   *Credits: Google and EDF, 2017.

2 significance

Methane, CH4, is a greenhouse gas twenty times more effective than carbon dioxide in trapping heat in the atmosphere over a 100 year period.  Approximately 35% of the methane released by these systems occurs during the field exploration and production stages of the natural gas and oil extraction processes.  


The optimal monitoring of oil fields by a mobile sensor is the motivation for this project.


3 proposed solution
roadmap G.png
tree like G.png
optimal path.png
4 acknowledgement

This work was developed under the supervision of Prof. Silvia Ferrari as part of the final project for MAE 6790: Intelligent Sensor Planning.

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