Reservoir Lithology Classification by the Hidden Markov Model

Abstract

Hidden Markov Model has been applied to predict the reservoir lithologies by using seismic inversion results as inputs. This method can take the conditional probability between different states or lithologies into account which is the vertical correlation in geology. In order to consider the misfit between the inversion results and the true well-logging data, the model needs to be trained. The application on a field example is quite successful in which most of lithologies have been predicted correctly even for some thin layers. However, this method is only 1D which means that the lateral continuity has not been considered yet.