One-dimensional stochastic inversion for seismic reservoir characterization — A case study

Abstract

Estimation of reservoir properties and facies from seismic data is a well-established technique, and numerous methods are in common usage. We demonstrate that our 1D stochastic inversion process, based on matching large numbers of pseudowells to color-inverted angle stacks, can produce accurate estimations of facies and reservoir properties and, importantly, the associated uncertainties. Using a case study from an offshore siliciclastic field, we show that a thorough understanding of all input well data and a detailed validation of the parameters input to the inversion process are crucial to obtaining a good result. We also illustrate some of the various products that can be output from such an inversion process to help constrain subsequent geostatistical reservoir modeling.