Multimodal comparative analysis based on geological and technological parameters

Abstract

Effective reservoir management require integrating multiple geological and technological parameters to optimize decision-making. This article examines various methodologies for data-driven comparative analysis and its application for selection of drilling points and water flooding operations. Advanced computational techniques, including machine learning applications, are explored for their role in improving evaluation accuracy. Additionally, this study compares different comparative analysis approaches used in the industry, highlighting their strengths, limitations, and adaptability to various geological conditions. By synthesizing recent research findings, this paper identifies potential advancements in multimodal analysis and proposes future directions.