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Baziw E.,University of British Columbia | Baziw E.,Baziw Consulting Engineers Ltd. | Verbeek G.,University of Texas at Tyler
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014

A very common problem encountered in downhole seismic testing (DST) and crosshole seismic testing (CST) is the processing of seismograms that contain total internal reflections (TIRs). TIRs arise when the incident angle exceeds the critical angle, and they are associated with reflected source wave distortions due to the fact that the reflection coefficients become complex. TIRs are typical in CST investigations (since horizontally traveling source waves have high angles of incidence on bounding stratigraphic layers), whereas in DST investigations, TIRs are encountered whenever there are significant man-made structures (piles, stone columns, and deep underground structures such as deep basements, parking garages, and dam structures). To process seismograms containing TIRs, time-variant blind seismic deconvolution (BSDtv) techniques are required, and this paper outlines a new formulation of a previously published concept in blind seismic deconvolution referred to as principle phase decomposition (PPD). This new PPD filter formulation allows for BSDtv where the direct source wave is isolated from the reflected source waves. The BSDtv PPD filter formulation is referred to as BSDSolver-tv. © 1980-2012 IEEE.

Baziw E.,Baziw Consulting Engineers Ltd.
IEEE Transactions on Geoscience and Remote Sensing | Year: 2011

This paper outlines a more powerful formulation of a previously published new concept in blind seismic deconvolution, referred to as principle phase decomposition (PPD). In this new PPD filter formulation, an iterative forward modeling (IFM) algorithm is incorporated, which facilitates the estimation of parameters defining the source wave (i.e., dominant frequency, phase, and decay) and the overlapping source waves (i.e., reflection coefficients' corresponding arrival times and amplitudes). This IFM integrated PPD algorithm allows for a significantly more accurate approach in estimating the source wave and corresponding reflection series compared to the previously published technique of sequentially estimating the source wave and overlapping source waves utilizing a Rao-Blackwellized particle filter. In general terms, the source wave is modeled as an amplitude-modulated sinusoid, and the overlapping source waves are treated as known inputs within the Kalman filter formulation based on the current source wave and reflection series IFM parameter estimates. The source wave and reflection series parameters are obtained by iteratively minimizing a cost function defined to be the rms difference between the measured seismogram and the synthesized seismogram within the IFM algorithm. © 2006 IEEE.

Baziw E.,Baziw Consulting Engineers Ltd. | Verbeek G.,Baziw Consulting Engineers Ltd.
Geotechnical Testing Journal | Year: 2014

Downhole Seismic Testing (DST) and Crosshole Seismic Testing (CST) are important geotechnical testing techniques which provide for low strain (<10-5) in situ compression (Vp) and shear (Vs) wave velocity estimates. The Vs and Vp interval velocities are determined by obtaining relative arrival times of source waves as they travel through the stratigraphy and are recorded by one or more vertically (DST) and/or horizontally (CST) offset seismic sensors. The relative arrival times are typically obtained by cross-correlating the recorded source waves or identifying reference features within the seismic trace such as a peak, trough, crossover point, or first break. A very common and yet poorly understood problem encountered in DST and CST is the analysis of seismograms that contain Total Internal Reflections (TIRs). TIRs arise when the incident angle exceeds the critical angle; as a result of which reflection coefficients become complex, which in turn leads to distortions in the reflected source wave. This paper addresses the issue of TIRs and the signal processing challenges when processing seismic data containing TIRs. Copyright by ASTM Int'l (all rights reserved).

Baziw E.,Baziw Consulting Engineers Ltd. | Verbeek G.,Baziw Consulting Engineers Ltd.
Pure and Applied Geophysics | Year: 2012

Among engineers there is considerable interest in the real-time identification of "events" within time series data with a low signal to noise ratio. This is especially true for acoustic emission analysis, which is utilized to assess the integrity and safety of many structures and is also applied in the field of passive seismic monitoring (PSM). Here an array of seismic receivers are used to acquire acoustic signals to monitor locations where seismic activity is expected: underground excavations, deep open pits and quarries, reservoirs into which fluids are injected or from which fluids are produced, permeable subsurface formations, or sites of large underground explosions. The most important element of PSM is event detection: the monitoring of seismic acoustic emissions is a continuous, real-time process which typically runs 24 h a day, 7 days a week, and therefore a PSM system with poor event detection can easily acquire terabytes of useless data as it does not identify crucial acoustic events. This paper outlines a new algorithm developed for this application, the so-called SEED™ (Signal Enhancement and Event Detection) algorithm. The SEED™ algorithm uses real-time Bayesian recursive estimation digital filtering techniques for PSM signal enhancement and event detection. © 2012 Springer Basel AG.

Baziw E.,Baziw Consulting Engineers Ltd. | Verbeek G.,Baziw Consulting Engineers Ltd.
Geotechnical and Geophysical Site Characterization 4 - Proceedings of the 4th International Conference on Site Characterization 4, ISC-4 | Year: 2013

When analyzing downhole seismic testing data in soil profiles with minimal variance in impedance, the Straight Ray Assumption (SRA) methodology can be utilized to calculate interval velocities. However, source wave trajectories also adhere to Fermat's principle of least time. To properly account for this in soil profiles with significant impedance variance, the calculation of the interval velocities should no longer be based on the SRA methodology, but instead use the Iterative Forward Modeling (IFM) technique. This technique has many advantages over the SRA technique as outlined in this paper. In this paper we will discuss the IFM technique to improve upon the SRA interval velocity estimates and demonstrate that the application of the IFM technique becomes even more essential in case of a soil profile with a top layer that has a relatively low interval velocity. The latter may also explain why according to some the use of downhole seismic testing is not appropriate for shallow depths. © 2013 Taylor & Francis Group.

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