Data Mining for Seismic Exploration
Zhongbin Ouyang, Jing He, Keliang Zhang · 2008
Seismic exploration plays an important role in petroleum industry. It is widely admitted that there are a lot of limitations of conventional data analysis ways in oil and gas industry. Traditional methods in petroleum engineering are knowledge-driven and often neglect some underlying factors. On the contrary, data mining is to deal with mass of data and never overlook any important phenomena. Due to large volumes of seismic data, we apply data mining to seismic exploration in this paper. K-means based Cluster analysis is applied for the 3-D seismic and well log data. Comparing the clustering results with the well log data, it is easy to display the distribution of lithology in geo-space.