E-lectures accordion

This E-Lecture introduces virtual seismology: monitoring the subsurface with virtual sources and receivers, which is a new methodology to create virtual sources and virtual receivers in the subsurface from reflection measurements at the earth's surface. Unlike in seismic interferometry, no physical instrument (receiver or source) is needed at the position of the virtual source or receiver. Moreover, no detailed knowledge of the subsurface parameters and structures is required: a smooth velocity model suffices. Yet, the responses to the virtual sources, observed by the virtual receivers, fully account for multiple scattering. This method is not only useful for reflection imaging but is has also large potential for monitoring induced seismicity, characterizing the source properties and forecasting the response to potential future induced earthquakes. This will be demonstrated with numerical models and preliminary real-data results.

In this presentation,a novel seismic acquisition and processing methodology is demonstrated. The method retrieves the response of the earth from data acquired with continuous source and receiver wavefields. The ideal source wavefield would be band-limited white noise. Ways of generating a source wavefield which approaches the properties of white noise using existing air-gun equipment will be discussed using real data examples. Seismic data acquired by triggering individual air-guns with short randomized time intervals in a near continuous fashion will be compared to seismic data acquired with large source arrays triggered every 25m. The continuous source wavefield improves the sampling of common-receiver gathers compared to conventional acquisition methods. Spreading the source energy out in time results in reduced peak sound pressure levels with the new method.

QI workflows assume that seismic amplitudes are only linked to contrasts in rock properties, and that other wave propagation effects such as illumination, absorption, etc. have been addressed during seismic data processing and imaging. This assumption is often not met. The consequence is that 1D wavelets can’t adequately relate seismic amplitudes to reflectivity contrasts, and conventional time-domain inversion approaches inevitably struggle to accurately estimate the elastic rock properties. The effects of irregular illumination can be modelled by Point Spread Functions (PSFs), and removed from the seismic image with an inversion directly in the depth domain (Fletcher et at., 2012). This technique, called Depth Domain Inversion (DDI), improves imaging and inversion results by correcting for the effects of irregular illumination caused by the geological structure and overburden velocity variations. A North Sea case study is presented where DDI is enhances amplitude fidelity and resolution beneath cemented sand injectites.

In this presentation,a novel seismic acquisition and processing methodology is demonstrated. The method retrieves the response of the earth from data acquired with continuous source and receiver wavefields. The ideal source wavefield would be band-limited white noise. Ways of generating a source wavefield which approaches the properties of white noise using existing air-gun equipment will be discussed using real data examples. Seismic data acquired by triggering individual air-guns with short randomized time intervals in a near continuous fashion will be compared to seismic data acquired with large source arrays triggered every 25m. The continuous source wavefield improves the sampling of common-receiver gathers compared to conventional acquisition methods. Spreading the source energy out in time results in reduced peak sound pressure levels with the new method.