Integrating data from multiple disciplines for reservoir microfacies forecasting

A new method has been proposed for forecasting the distribution of the microfacies, integrating the core data, logging data, seismic data and testing data of multiple disciplines. The flowchart of this method follows the basic idea of from points (well) to surfaces (the 2-D maps) to zones (the 3-D maps). The recognition and core-log response model has first been constructed by the analysis of sedimentary environments of the region and core data; then, the microfacies of non-core wells have been identified according to the core-log response model; thirdly, the 2-D map of microfacies is forecasted by the 2-D map of sandstone thickness and the information from the analysis of seismic data. The shape parameters of microfacies have been achieved by dissecting the microfacies using the testing data. Finally, the 3-D distribution of microfacies has been reproduced by reservoir stochastic modeling methods. The 3-D microfacies distribution of the fluvial environments has been accomplished in Gangdong exploitation district of Dagang Oilfield. This high precise reservoir model can give more information to the oil engineerings, and is a basis of petrophysical properties forecasting and the reservoir numerical simulating.