Statistical algorithms for surface seismic monitoring of reservoir hydraulic fracturing

The problem is considered of statistically optimal estimation of micro-seismic source parameters using multichannel data from surface arrays of seismometers affected by strong seismic noise. The problem is treated as a statistical task of parameters estimation of the general type multidimensional linear system with a random or completely unknown input time function. The maximum-likelihood generic estimator is derived and its relationship with well-known seismic emission tomography (SET) algorithm is established. Using the method of successive independent trials (Monte-Karlo) was demonstrated that a proposed statistical estimation algorithm provide much higher accuracy of micro-seismic event source location in real noise conditions than widely used SET algorithm and is more reliable in practical applications. The proposed estimation algorithm perform processing of multichannel discrete observations in the frequency domain and can be implemented in on-line mode.