Today, we show an example of how to de-risk an exploration prospect using OpendTect’s Fluid Contact Finder (FCF) and Machine Learning plugins.

FCF is a tool to enhance hydrocarbon-induced seismic amplitude anomalies. The idea is simple: all seismic traces lying on the same (depth-)contour of a hydrocarbon-filled structure are expected to encounter the same hydrocarbon column length. In other words, the seismic response will be affected by hydrocarbon-fill in a similar manner. Stacking all traces lying in the same contour interval thus enhances the hydro-carbon effect (the anomaly) while cancelling all other effects (noise and lithological differences). The result of a FCF analysis is presented in the form of a panel of stacked traces organized in contour intervals. Step-changes in amplitude response indicate changes in fluid-fill. Another useful output of FCF analysis is a volume of FCF stacked traces to display amplitude maps of FCF-enhanced anomalies

Seismic Chimney Cubes are created in OpendTect’s Machine Learning plugin using a supervised neural network approach. Chimney Cubes show vertical fluid migration paths. They are used for geohazard interpretation and for analyzing petroleum systems. In the video, we show an example of using FCF and Chimney interpretation on an anticlinal structure of a carbonate reservoir. No conformable anomalies are visible on the seismic data. However, FCF analysis reveals two amplitude anomalies: one interpreted as a possible Gas-Oil-Contact (GOC) and the other as a possible Oil-Water-Contact (OWC). Chimney analysis shows that there are hardly any chimneys above the structure, implying that we are dealing with a good top seal. Most chimneys are located down-structure along a major fault system. This shows that there is charge into the structure. The interpreted OWC coincides with the depth of the fault / chimney trend, which indicates that the structure is filled to spill point.