Application of artificial intelligence network to predict the distribution of volcanic material in sequence D, field X, Cuu Long basin

Abstract

The presence of volcanic materials in reservoir will reduce the porosity value and effect to the quality of reservoirs. Therefore, understanding the distribution of this object will be of great significance in the orientation of oil and gas exploration and exploitation. This paper applies seismic attribute analysis method combined with artificial neural network (ANN) application to predict the distribution of volcanic materials in D sequence. Attributes selected as input for ANN training including RMS, RAI and Specdecom attribute. The results indicate that volcanic materials mainly appear in the to the Southwest of block (around D well and the West of E well), a small part is scattered near Con Son swell. The correlation coefficient among seismic attribute is from 71 to ~ 80%, this shows that the reliability of the results of network training is relatively high. Therefore, this method can be used to predict the distribution of volcanic materials in the study area.