Microseismic event location using multi-scale time reversed imaging

Locating passive seismic sources in a reservoir monitoring system has attracted considerable interest recently due to its ability to image the induced fracture geometry that results from fluid injection and fracturing processes. Time reversed imaging (TRI) techniques are well recognized localization tools, which back-propagates the received microseismic recordings to focus at its real source location without picking various arrival phases. However, the time reversed images are often contaminated due to the strong noise, coherent noise and poor spatial constraints especially in surface microseismic measurements, leading to unreliable location estimations. To minimize these interferences, we propose 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 Birge-Massart threshold is applied to the wavelet coefficients at each level to further attenuate the noise amplitude. The TRI are then applied to the reconstructed waveform component at each level. Both the synthetic and field studies show that the multi-scale cross-correlation of TR images at effective levels substantially improved the quality of the final image of subsurface microseismic events with a much sharper and brighter focus. On the other hand, the images at noise levels 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, which can be further used in microseismic sensitivity and location uncertain analysis.