Seismic Impedance Inversion with Petrophysical Constraints via the Fuzzy Cluster Method

Abstract

Seismic impedance inversion produces results that should be better for geological interpretation. However, seismic impedance inversion in mineral exploration normally suffers from poor signal-to-noise, and a lack of well control normally assumed for the process. To counter these problems we have developed an approach that exploits the fact that the geology in these environments often has fewer distinct geological units so we can restrict the number of physical parameters possible. A model-based seismic impedance inversion method using fuzzy c-means clustering to constrain inversion with petrophysical information has been developed. Using synthetic examples, we show that our method effectively recovers the true model even when the data is strongly contaminated by noise. This method is applied to seismic data from a US gold mining district and the results are reasonably consistent with well log data. The impedance images provide a better basis for geological interpretation than reflection images alone.