Stochastic inversion of seismic data by implementing image-quilting to build a lithofacies model for reservoir characterization of Delhi Field, Louisiana
Considering the depositional and geological complexity present in the fluvial deltaic systems, such as Delhi Field, Louisiana, application of conventional geostatistics for reservoir modelling or conventional seismic inversion approaches will not obtain a detailed and accurate lithofacies and rock property model for the field. Therefore, incorporation of advanced geostatistical approaches that can capture the complex depositional features of the reservoir is of great importance. The producing formations in Delhi Field consist of Paluxy and Tuscaloosa. The Paluxy is a fluvial deltaic interval of Early Cretaceous age and Tuscaloosa of Late Cretaceous age unconformably overlying the Paluxy and made up of transgressive marine deposits overlaid by a shallowing upward sequence of barrier bars and a fluvial deltaic interval at the top (Davis, 2014). This creates a complex depositional environment for Delhi reservoir that cannot be modelled via conventional modeling approaches. A new modelling method in the form of inversion has been implemented in this field to capture the complex depositional features and provide a detailed definition for the reservoir. The method is a multiple point statistics (MPS) algorithm, which incorporates pattern recognition and reconstruction methods along with seismic data in an inversion approach.