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Hydrocarbon-bearing geological structures might cause characteristic modifications of the ambient vibration background noise. This question is addressed in a project supported by the Commission for Technology and Innovation (CTI) together with the company SpectraSeis. The link between observations and geological structure can only be made by understanding the wavefield that is recorded. This requires the simultaneous recording and analysis of ambient vibration wave-fields on arrays. Such methods have been developed in the past, and they have been applied to study soft-sediment surface deposits for seismic hazard analysis. The analysis of all three components of ground motion is addressed. Analysis of such recordings targets to distinguish between standing waves (global resonances) and propagating surface waves (Love- and Rayleigh-waves) as well as body waves (SH and PSV). By adapting array configurations during the measurements in the field, the identification of the wave-types with the corresponding propagation velocity and direction is optimized and allows to determine the source region of the waves and their possible origin. From the wave characteristics, structural information can be inverted that allows to improve structural models. The development of a real-time system for array measurements is part of the project. |
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| Project Leader at SED | Donat Fäh |
| SED Project Members | Stefano Maranò, Javier Revilla |
| Funding Source | Commission for Technology and Innovation (CTI) |
| Duration | 2009-2012 |
| Keywords | Array methods, ambient vibration, hydrocarbon reservoir detection |
| Research Field | Strong-motion interpretation and site-effects, Signal Processing |
Maranò, S., Reller, C., Fäh, D. and Loeliger, H.-A. (2011). Seismic waves estimation and wave field decomposition with factor graphs. Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, 2748–2751. Prague, Czech Republic: IEEE. doi: 10.1109/ICASSP.2011.5947054
Reller, C., Loeliger, H.-A. and Maranò, S. (2011). Multi-sensor estimation and detection of phase-locked sinusoids. Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, 3872–3875. Prague, Czech Republic: IEEE. doi: 10.1109/ICASSP.2011.5947197
Maranò, S., Reller, C., Loeliger, H.-A. and Fäh, D. (2012). Seismic waves estimation and wave field decomposition: Application to ambient vibrations. Geophys. J. Int. 191, 175–188. doi: 10.1111/j.1365-246X.2012.05593.x
Maranò, S. and Fäh, D. (2013). Processing of Translational and Rotational Motions of Surface Waves: Performance Analysis and Applications to Single Sensor and to Array Measurements. Geophys. J. Int. 196, 317-339. doi: 10.1093/gji/ggt18
Maranò, S., Fäh, D. and Lu, Y.M. (2014). Sensor placement for the analysis of seismic surface waves: sources of error, design criterion and array design algorithms. Geophys. J. Int. 197(3), 1566–1581. doi: 10.1093/gji/ggt489
S. Maranò Seismic wave field decomposition application to the analysis of ambient vibrations. European Seismological Commission 32nd Assembly, September 6-10 2010, Montpellier, France.
S. Maranò Seismic Waves Estimation and Wave Field Decomposition With Factor Graphs. IEEE International Conference on Acoustics, Speech, and Signal Processing, May 22-27 2011, Prague, Czech Republic.
S. Maranò Maximum likelihood parameter estimation for surface waves: application to ambient vibrations. 4th International IASPEI/IAEE Symposium on the Effects of Surface Geology on Seismic Motion, August 23-26 2011, Santa Barbara, California.
S. Maranò Maximum Likelihood wavefield parameters estimation: Application to the analysis of ambient vibrations. European Seismological Commission 33rd Assembly, August 19-24 2012, Moscow, Russia.
S. Maranò Joint processing of translational and rotational motions of seismic surface waves: Performance analysis and applications. IASPEI Assembly, July 12-26 2013, Gothenburg, Sweden. Invited presentation.
S. Maranò Analysis of ambient vibrations using a maximum likelihood method. European Seismological Commission 34th Assembly, August 24-29 2014, Istanbul, Turkey.