HR: 10:45h
AN: S32A-02 INVITED     [Abstracts]
TI: Virtual Sources, a new Reality for Imaging.
AU: * Calvert, R W
EM: rodney.calvert@shell.com
AF: Shell Intl. E and P, Bellaire Technology Center P.O. Box 481, Houston, TX 77001-0481 United States
AU: Bakulin, A
EM: andrey.bakulin@shell.com
AF: Shell Intl. E and P, Bellaire Technology Center P.O. Box 481, Houston, TX 77001-0481 United States
AB: We have developed a technique for sensitive imaging and hydrocarbon reservoir monitoring which we call Virtual Source. Although the methodology is different, our description will be different and the motivation is different, the underlying physics is similar to that employed in Passive Imaging. Our ability to seismically image the subsurface for exploration and to closely repeat surveys for monitoring is compromised by earth heterogeneity. With heterogeneity at all scales we can never make a property model complex and accurate enough to enable a full bandwidth high-resolution image from the energy we put into the ground. To be able to measure small differences in our reservoirs we would like to have multi-path scattering travel times to repeat within 0.1msec or better. This requires impractical positioning repetition of source elements and unexpected stability of naturally changing overburden. We therefore need fixed sources and receivers under the overburden. Our budgets demand the sources, at least, be virtual ! With buried geophone receivers Rj under the troublesome overburden we can shoot over them with conventional sources Si. We record the direct arrivals in traces Tij. This direct arrival energy going down through Rj is the result of a particular source waveform, a particular coupling to the earth, multi-path scattering, reverberations, transmission losses; the whole real heterogeneous earth transmission response from Si to Rj. We may invert this "wavelet" to a pulse by deconvolution. A practical deconvolution is correlation and zero phase spectral shaping to a desired bandwidth to give a custom zero phase pulse W. The deconvolution filter Tij-1 would be of form Tij*.W/[Tij.Tij*]. If we filter the whole shot Si gather into all receivers Rk with Tij-1 then that signal energy from Si which goes through Rj will be received at Rk as Tik.Tij-1 as though it was sourced from Rj at zero time with waveform W. If we now sum over all Si we may simulate a downward radiating source at Rj with known wavelet W being received in receivers Rk. We thus have the ability to recast the seismic experiment as having a controlled downward radiating Virtual Source at each receiver location in turn. What is nice is that we can do this without any knowledge of the overburden, without knowledge of the physical source waveform or exact location. We can get repeatable results even if the overburden should change, as this will be automatically compensated by Tij-1. Another interesting property is that the worse the overburden is for conventional seismic the better it is for Virtual Source work. With a highly scattering overburden we need less physical source locations to give a good Virtual Source radiation pattern. The method has given encouraging results on initial tests. We obtain remarkable repeat of detail from survey to survey and we can see reservoir changes with improved resolution and sensitivity. It is interesting to compare the Virtual Source with passive imaging from the surface. By going underground we can avoid the ground roll and other near surface noise. By using arrays and active sources we can recognize and choose energy for a desired radiation direction. We can use the method with low energy continuous sources such as uncontrolled Vibroseis or natural noise. We can also move our Virtual Source to the surface as in a conventional seismic survey and take advantage of a pulse waveform to select up and down going energy. Being on the surface and using natural noise would perhaps be the most difficult combination.
DE: 7200 SEISMOLOGY
DE: 0629 Inverse scattering
DE: 0674 Signal processing and adaptive antennas
DE: 0900 EXPLORATION GEOPHYSICS
DE: 0910 Data processing
SC: Seismology [S]
MN: 2004 AGU Fall Meeting