Abstract:

Seismic attribute analysis is an efficient method for reservoir prediction. However, using only one attribute to predict reservoir leads to multiple-understanding, especially for the fault-depressed basin which has the characteristics of multi-provenances, fast variation of sedimentary facies, multi-period volcanic movements and complicated lithologies. All of these factors result in poor prediction accuracy. Therefore, this paper proposed a seismic multi-attribute fusion technique based on different sedimentary characteristics and separated regions for reservoir prediction. Firstly, according to the sedimentary characteristics, different regions were divided with seismic waveform classification technique. Then, the relation statistics between seismic multi-attribute and reservoir information were carried out and the linear fitting was completed for the further step. At last, the separated fitting results were integrated into the final prediction results for the whole area. For the reservoir prediction of Nantun Formation in Beier Depression, Hailaer Basin, stepwise linear regression was put into use on the basis of sand data from 164 wells and the selected 8 seismic attributes. Its correlation coefficient is only 0.42. With the seismic multi-attribute fusion technique based on sedimentary characteristics and selected regions, the whole area fitting was carried out. Its correlation coefficient reaches 0.89 and the reservoir prediction result fits well with the reservoir development and the sedimentary rules in drilled wells, which indicates that the method can improve the accuracy of reservoir prediction.

Key words: horizontal well, production rate equation, formation damage, formation improvement, skin factor, skin effect