With the advent of multi-version interpretation of AVO and 4D many more 3D volumes need interpreting. Traditional band-limited, fast-track inversion techniques (e.g. trace integration, recursive inversion and phase rotation) are prone to error because no account is taken of the seismic wavelet or calibration to the Earth. Sophisticated techniques, such as sparse spike do take account of the seismic wavelet, but require specialist skills and are time consuming. Even using sophisticated techniques the resultant seismic inversion can still give an erroneous result. What is needed is a technique which is fast, easy to use and is calibrated against well log AI data
Inversion of seismic data to Acoustic Impedance (AI) is usually seen as a specialist activity. In spite of publicised benefits, inverted data are only used in a minority of cases. To help overcome this obstacle, this algorithm which is quick and easy to use, can increase the use of inversion technology. SCI performs significantly better than traditional fast-track methods such as recursive inversion, and benchmarks well against unconstrained sparse-spike inversion. With the inclusion of de-trend and normalisation functionality within SCI, geophysical meaning can now be assigned to the observed amplitude changes in the derived impedance volumes. This can be very powerful, particularly with 4D projects. Once the SCI operator has been derived, it can be simply applied using the 3D processing tool included within the SCI software. In this way, inversion can be achieved within hours since the volume data do not have to be exported to another package. SCI takes into account the seismic wavelet and is consistent with log data. With this technique, it is now possible to routinely invert any dataset within hours and establish a base case against which more sophisticated techniques must be judged. SCI enables the rapid inversion of 2D/3D data. A single convolution inversion operator is derived that optimally inverts the data and honours available well data in a global sense. In this way, the process is intrinsically stable and broadly consistent with known AI behaviour in the area. Construction of the operator is a simple process and implementation can be readily performed within the processing module included in SCI. As an explicit wavelet is not required, other than testing for a residual constant phase rotation as the last step, this removes an inherently weak link that more sophisticated processes rely on.
Generally, traditional inversion methods (e.g.sparse- spike) are time consuming, expensive,require specialists and are not performed routinely by the Interpretation Geophysicist, whereas SCI is rapid, easy to use, inexpensive, robust and does not require expert users. SCI and unconstrained sparse-spike appear to give broadly equivalent results. SCI seamlessly connects with third party seismic and well data repositories (including SeisWorks, OpenWorks, GeoFrame and OpendTect) using our client/server technology. This allows SCI analysis,operator design and processing to be performed without separately importing or exporting data.