Speaker
Description
Underground nuclear explosions produce an immense change in pressure and temperature concentrated around the source origin. This results in the formation of characteristic static and dynamic phenomena. This study highlights the potential of using time-lapse seismic to identify ground zero by monitoring post-explosion dynamic phenomena. Time-lapse seismic is successfully employed in the oil and gas industry. It involves taking more than one 2D/3D survey at different calendar times over the same reservoir and studying the difference in seismic attributes.
Dynamic changes in rock and fluid properties due to UNE are observable for a prolonged period, even up to several decades. This is prominent near to source origin and is a result of the redistribution of residual energy, such as pressure, temperature, and saturation. Frequent seismic monitoring surveys (time-lapse seismic) would enable monitoring of changes to rock and fluid properties. The characteristics of the time-lapse seismic signature in a heterogeneous medium (or heterogeneous cavity), and the factors affecting land 4D repeatability on the 4D signature are discussed. We present a fast detection method using machine learning for the detection of explosion-related time-lapse signatures, which could be used to identify the source location or ground zero.
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This study highlights the potential of using time-lapse seismic to identify ground zero by monitoring post-explosion dynamic phenomena. The suggested technique is envisaged for field deployment during on-site inspection to locate the zone of 4D change or source location.
