A New Reservoir Prediction Method Based on Geological Seismic Conditioning for Complex Barrier Island and Its Application at H Oil Field

Abstract

Abstract In order to improve the accuracy of reservoir prediction results, the conventional method usually include seismic inversion, and seismic attribute analysis. Due to the limitation of the vertical resolution of seismic data, it is hard to identify the thin reservoir by seismic attributes directly. In order to improve the prediction accuracy of reservoir, this paper show a new reservoir characterization technique based on geological seismic conditioning. The new method mainly includes five steps. The first step is sedimentary facies classification based on the geological seismic analysis, such as core data, thin section analysis, FMI logging, NMR logging and conventional logging. The second step is modern sedimentary model optimization and forward modelling. In order to establish a reasonable sedimentary facies model, a similar barrier island modern sedimentary model was chosen. To understand the geological significance of seismic data, two different dominant frequency were designed for forward modelling based on the sedimentary facies model and petrophysical analysis. The third step is seismic conditioning under the guide of sedimentary facies model forward modelling. The next step is seismic constraint stochastic inversion, and the last step is reservoir characterization and new well confirm. The application of this method in A oilfield shows that the techniques not only improved the identification ability of the reprocessing seismic data, but also improved the prediction accuracy of the reservoir characterization results. This new reservoir characterization technique can integrated multidisplinary information, such as modern sedimentary model, well data and seismic data, to establish a reasonable sedimentary model, to enhance the resolution of seismic data by conditioning, and get an reasonable reservoir characterization results based on the seismic inversion.