Tutorial: Advanced concepts in active and passive time-lapse 4D seismic monitoring

David Lumley
University of Texas at Dallas

Time-lapse seismic imaging of the earth's interior, and inversion for dynamic rock and fluid physical property changes, has produced many spectacular results over the past 25 years; however we are still making many theoretical approximations, and extracting only a small percentage of the information available in the data. I will present advanced concepts in full wavefield imaging and inversion with application to active-source, passive, ambient noise and real-time 4D seismic data, in order to improve time-varying images of the subsurface, and quantitative estimates of the earth's time-varying physical properties.
4D seismology has become a mainstream technology to monitor subsurface fluid flow… provided that certain optimal conditions are present. However, there are many rock and fluid combinations which are currently impossible to monitor in typical noise environments, with state-of-the-art seismic acquisition systems. I will show that we may be able to overcome such difficult challenges by making use of the full complex time-varying scattered wavefields, which I term “4D seismic coda waves”.
In parallel with active-source 4D seismic developments, semi-permanent Large N sensor arrays capable of long-term continuous recording are bringing new ideas and science together from the exploration and earthquake seismology communities. I will discuss how advanced wave-equation imaging and inversion methods can be applied to continuous array data including natural and induced seismicity, and ambient noise wavefields. Continuous passive seismic recording allows us to isolate ambient noise body waves for subsurface imaging and inversion. In some cases we are able to achieve ambient noise image convergence at reservoir depth in less than 60 minutes of recording time, which allows the possibility to make time-lapse movies of the subsurface with a frame rate of about 1 hour. Since these arrays have a small environmental footprint and require no man-made source energy, we may be heading for a future of low-cost real-time monitoring of the subsurface using the natural ocean ambient noise that is continuously generated and scattered within the earth.

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