Signal-to-noise Estimates of Time-reverse Images

Locating subsurface sources from passive seismic recordings is difficult when attempted with low signal-to-noise data that do not contain observable arrivals. Using time reversal techniques, recorded energy can be focused at its source depth. However, when a focus cannot be mat-ched to a particular event in the data, it can be difficult to distinguish true focusing from artifacts. Artificial focusing can arise from numerous causes, including surface waves, local noise sources, acquisition geometry and velocity model effects. We present a method to better locate subsurface sources that reduces the ambiguity of the results by creating an estimate of the signal-to-noise ratio in the image domain. Time-reverse imaging techniques are used to image the recorded data and a noise model. In the data domain, the noise model only approximates the energy of local noise sources. After imaging, however, the result also captures the effects of acquisition geometry and spurious focusing due to the velocity model. The noise image is then used to correct the data image to produce an estimate of the signal-to-noise ratio. Synthetic data examples with various amounts of noise demonstrates the versatility of this technique.