Horizon correlation across faults guided by geological constraints

A new approach towards automating the interpretation of geological structures like horizons or faults in reflection seismic data images is presented. Horizons are strong reflection events which indicate boundaries between rock formations while faults are discrete fractures across which there is measurable displacement of rock layering. Horizon tracking across faults and thereby determining geologically valid correlations is an important but time consuming task although it has still not been automated satisfactorily. The difficulties of matching horizon segments across faults are due to those types of images which contain only a small amount of local information, furthermore partially disturbed by vague or noisy signals. In this paper we describe a model-based approach which reduces these uncertainties by introducing global features based on geological constraints. Two optimisation methods have been examined: an exhaustive search algorithm which reliably delivers the optimal solution presuming correctness of the model and a more practicable strategy; viz, a genetic algorithm. Both methods successfully matched all selected horizons across normal faults in typical seismic data images.