Model-based analysis of geological structures in seismic images

Subsurface models, obtained by structural interpretation of seismic images, underpin all decisions in hydrocarbon exploration and production. The main interest in this field is directed towards the interpretation of horizons and faults: Horizons are strong reflection events which indicate boundaries between rock layering while faults are discrete fractures along which appreciable displacement has taken place. Horizon tracking across faults and thereby determining geologically valid correlations is an important but time consuming task which has not been automated satisfactorily yet. The difficulties of matching horizon segments across faults are due to the fact, that those images contain only a small amount of local information, furthermore partially disturbed by vague or noisy signals. We describe an approach which reduces interpretation uncertainties by introducing geological constraints derived from a fault model. Two optimisation methods have been examined: an exhaustive search algorithm which reliably delivers the optimal solution presuming correctness of the model and a more viable strategy; namely, a genetic algorithm. Both methods successfully matched all selected horizons across normal faults in typical seismic data images.