Automating a Seismic Survey Using Heterogenous Sensor Teams and Unmanned Aerial Vehicles



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Seismic imaging is the primary technique for subsurface exploration. It requires placing a large number of sensors (geophones) in a grid pattern, triggering a seismic event, and recording the propagating waves. The location of hydrocarbons is inferred from these readings. Traditional seismic surveying for hydrocarbons employs human laborers for sensor placement, lays miles of cabling, and then recovers the sensors. Often sites of resource or rescue interest may be difficult or hazardous to access. The major drawbacks of surveying with human deployment are the high costs and time, and risks to humans due to explosives and harsh climatic conditions. Thus, there is a substantial need to automate the process of seismic sensor placement and retrievals using robots. We propose an autonomous, heterogeneous sensor deployment system using UAVs to plant immobile sensors and deploy mobile sensors. Detailed analysis and comparison with traditional surveying were conducted. Hardware experiments and simulations prove the effectiveness of automation regarding cost and time. The proposed system overcame the drawbacks and displayed higher efficiency. The deployed sensors essentially became a wireless sensor network (WSN). Thus traditional batteries cannot sustain a WSN. Energy is the major impediment to the sustainability of WSNs. Most energy is consumed by (i) wireless transmissions of sensed data and (ii) long-distance multi-hop transmissions from the source sensors to the sink. This research also presents an optimal path-planning algorithm for sustaining WSNs and validates the claim with simulations. The research in the future aims at exploring methods to exploit emerging wireless power transfer technology by using UAVs to service the WSNs. These UAVs cut data transmissions from long to short distances by collecting sensed information and replenishing WSN’s energy.



Seismic surveying, Unmanned aerial vehicle (UAV), Automation, Field robotics, Heterogeneous Sensors