Identification of Induced Seismicity in the Fault Zone of the Korobkovskoye Deposits (Kursk Magnetic Anomaly) Based on Observations of a Small-Aperture Seismic Array

Doklady Earth Sciences - The results of recording and determining the locations of seismic events triggered by industrial explosions conducted by OJSC Kombinat KMAruda at the Korobkovskoe iron ore...     

Robustness of statistical algorithms for location of microseismic sources based on surface array data

Here, we present a statistical simulation study of several array data processing techniques used for the location of sources of elastic waves. The source location problem arises in such engineering applications as radio-communications, acoustics, sonar, meteorology, astrophysics, seismology, etcetera. Recently, this problem has become important for applied geophysics in connection with the modern technology of hydrocarbon production based on the hydraulic fracturing of the surface layers of the Earth’s environment. These techniques are required for the monitoring of hydraulic fracturing through the location of sources of numerous microearthquakes that occur during cracking of crustal rocks. We have established theoretical connections among several location algorithms. In particular, two different theoretical interpretations were proposed for the phase alignment location algorithm, recently proposed for the seismic array data processing. The robustness properties of the phase alignment location algorithm and the adaptive maximum likelihood location algorithm were demonstrated through Monte Carlo simulation in regard to variations of those noise statistical features, which are typical under monitoring of microseismicity at the hydrocarbon production sites. In the framework of the Monte Carlo modeling, we also compared the two mentioned location algorithms with the so-called emission tomography algorithm that is developed for the location of microseismic sources during the monitoring of hydraulic fracturing.     

Recognizing of Microseismic Source Types Based on Small-Aperture Seismic Array Data

Izvestiya, Physics of the Solid Earth - Abstract—In this paper, we consider the problem of recording and processing the microseismic data with their subsequent interpretation and making the...     

Robust phase algorithms for estimating apparent slowness vectors of seismic waves from regional events

In this paper, we consider the problem of estimating the apparent slowness vector p of a plane P wave caused by a regional seismic event and recorded by a small-aperture seismic array. The case is considered when strong non-stationary and non-Gaussian random interferences act on the array sensors. In this case, the well-known estimate of wideband frequency-wave-number analysis (WFK) becomes ineffective due to large estimation errors. We have proposed three new algorithms for estimating the vector p that are robust i.e. resistant to changes in the statistical properties of the random interferences. They mainly use information about the slowness vector contained in the phases of the spectra of seismograms recorded by the array sensors. An intensive Monte Carlo simulation was carried out to compare the accuracy of the proposed phase-based estimates with the accuracy of WFK-estimate in the case when non-stationary and non-Gaussian anthropogenic interferences act on the array sensors. In the simulation we used synthetic mixtures of signals caused by a seismic event and anthropogenic seismic interferences. These signals and interferences were recorded by real small-aperture seismic arrays. It was shown that the proposed phase-based estimates of the vector p provide significantly better accuracy than traditional WFK-estimate in the case of strong anthropogenic interferences, and have approximately the same accuracy in the case of white Gaussian noise.

     

Determining the microseismic event source parameters from the surface seismic array data with strong correlated noise and complex focal mechanisms of the source

The world experience shows that hydraulic fracturing (fracking) is an efficient tool for increasing oil and gas production of low-permeable reservoirs in hydrocarbon fields. The fracking-induced fractures in the rock, which are hydrodynamically connected with the wells, significantly enhance the volumes of extracted hydrocarbons. Controlling the processes of fracture formation and propagation is a vital question in the oil and gas reservoir management. A key means to implement this control is provided by microseismic monitoring of fracking, which makes it possible to promptly reconstruct the geometry of the fractures from the data on seismic waves from the microearthquakes induced by the formation and propagation of fractures.