3D Multi-Level Facies Constrained Geostatistical Inversion for Predicting Carbonate Thin Reservoirs

Abstract Carbonate reservoirs are highly heterogeneous and poor in interwell connectivity. Therefore, it is difficult to predict the thin oil layers and water layers inside the carbonate reservoir with thickness less than 10 ft by seismic data. Based on the petrophysical analysis with core and well logging data, the carbonate target layers can be divided into two first level lithofacies (reservoir and non-reservoir) and three second-level lithofacies (oil, water and non-reservoir) by fluids. In this study, the 3D lithofacies probabilistic cubes of the first level and second-level level lithofacies were constructed by using the simulation method of well-seismic cooperative waveform indication. Afterwards, constrained by these probability cubes, the prestack geostatistical inversion was carried out to predict the spatial distribution of thin oil layers and water layers inside the thin reservoir. The major steps include: (1) Conduct rock physics analysis and lithofacies classification on carbonate reservoirs; (2) Construct the models constrained by two-level lithofacies; (3) Predict thin reservoirs in carbonates by prestack geostatistical inversion under the constraint of two-level lithofacies probability cubes. The prediction results show that through the two-level lithofacies-controlled prestack geostatistical inversion, the vertical and horizontal resolution of thin oil layers and water layers in carbonate reservoirs has been improved significantly, and the accuracy of thin oil reservoir prediction and the analyzing results of interwell oil layer connectivity have been improved significantly. Compared with the actual drilling results, the prediction results by 3D multi-level lithofacies-controlled inversion are consistent with the drilling results, and the details of thin carbonate reservoirs can be predicted. It has been proved that this method is reasonable and feasible. With this method, the prediction accuracy on thin reservoirs can be improved greatly. Compared with the conventional geostatistical inversion results, the 3D multi-level lithofacies-controlled inversion can improve significantly the vertical and horizontal resolution of prediction results of thin reservoirs and thin oil layers, and improve the reliability of interwell prediction results. For the prediction of thin carbonate reservoirs with serious heterogeneity, the 3D multi-level lithofacies-controlled inversion is an effective prediction method.