A data discovery project was initiated to investigate whether analytics concepts commonly used in the Analytics of Things (AoT) can be applied to describe and understand Permanent Reservoir Monitoring seismic operations with a focus on the source side to further improve operational efficiency. The AoT refers to the use of advanced analytics applied to large amounts of data generated by connected devices and sensors, in this case sensors normally associated with the seismic source used in Permanent Reservoir Monitoring (PRM) operations. This data was combined with data from other sources, which also described oceanographic conditions. The analytics was able to establish the link between environmental conditions, experienced during time lapse seismic surveys for PRM, and the operational behaviour of the seismic source vessel and the seismic source. This operational behaviour was further linked to the seismic signal generated by the seismic source. The data science techniques used in the project and insight will be described.


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