Locating microseismic events with multi-scale time reversed imaging: A synthetic case study

Locating microseismic events in a reservoir monitoring system has attracted considerable interest recently due to its ability to image the induced fracture geometry that result from fluid injection and fracturing processes. Time reversed imaging (TRI) techniques are well recognized localization tools developed in the last few years. This technique back-propagates the received full waveforms to focus at its real source location without picking different arrival phases. However, the time reversed images are often contaminated due to the strong noise and other interference in surface microseismic measurements, leading to unreliable location estimation. To minimize the interference of strong noise, we present a multi-scale TRI technique using the shift-invariant dual-tree complex wavelet transform (DTCWT) to decompose the original waveforms into multiple time-frequency domains (different levels). The TRI are then applied to the waveform component at each level. Images of effective components substantially improved the quality of the final image of subsurface microseismic events with a much sharper focus. On the other hand, the images of noise components may reveal the velocity structure which is helpful in event location. In addition, the noise components recognized by the multi-scale TRI can be applied to estimate the background noise level.