The generation of microseismic events is often associated with induced fractures/faults during the extraction/injection of fluids. A full characterization of the spatiotemporal distribution of microseismic events provides constraints on fluid migration paths in the formations. We have developed a high-resolution source imaging method — a hybrid multiplicative time-reversal imaging (HyM-TRI) algorithm, for automatically tracking the spatiotemporal distribution of microseismic events. HyM-TRI back propagates the data traces from groups of receivers (in space and time) as receiver wavefields, multiplies receiver wavefields between all groups, and applies a causal integration over time to obtain a source evolution image. Using synthetic and field-data examples, we revealed the capability of the HyM-TRI technique to image the spatiotemporal sequence of asynchronous microseismic events, which poses a challenge to standard TRI methods. Moreover, the HyM-TRI technique is robust enough to produce a high-resolution image of the source in the presence of noise. The aperture of the 2D receiver array (azimuth coverage in 3D) with respect to the microseismic source area plays an important role on the horizontal and vertical resolution of the source image. The HyM-TRI results of the field data with 3D azimuthal coverage further verify our argument by producing a superior resolution of the source than TRI.

The estimation of the Q factor of rocks by seismic surveys is a powerful tool for reservoir characterization, as it helps detecting possible fractures and saturating fluids. Seismic tomography allows building 3D macro-models for the Q factor, using methods as the spectral ratio and the frequency shift. Both these algorithms require windowing the seismic signal accurately in the time domain; however, this process can hardly follow the continuous variations of the wavelet length as a function of offset and propagation effects, and it is biased by the interpreter choice. In this paper, we highlight some drawback of signal windowing in the frequency-shift method, and introduce a tomographic approach to estimate the Q factor using the complex attributes of the seismic trace. We show that such approach is particularly needed when the dispersion is broadening the waveforms of signals with a long wave-path. Our method still requires an interpretative event picking, but no other parameters as the time window length and its possible smoothing options. We validate the new method with synthetic and real data examples, involving the joint tomographic inversion of direct and reflected signals. We show that a calibration of the frequency-shift method is needed to improve the estimation of the absolute Q factor, otherwise only relative contrasts are obtained.

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