A QUICK LOOK ON LITHO CLASSIFICATION USING COMBINATION OF PRINCIPAL COMPONENT ANALYSIS AND CLUSTER ANALYSIS OF SEISMIC ATTRIBUTES: A CASE STUDY ON BOONSVILLE FIELD

摘要

In this work, an attempt to identify lithologies based on the combination of principal component analysis and cluster analysis of seismic attributes has been held. A seismic signal will receive different responses by different lithologies. This can be recognized from in seismic attributes such as reflection strength, instantaneous phase, instantaneous frequency, and others. Displaying those attributes in N dimensions, where N is the number of attributes, will result in a number of clouds representing different clusters of lithologies. The aim of this work is to generate a quick lithology classification using the seismic attributes. To suppress the noise, a principal component analysis was implemented. The principal component analysis suppresses the noise by averaging the neighboring traces without the need of interpretation. The method has been applied to seismic data in Boonsville area and produces the result which was similar to existing geological interpretation based on the wells correlation.