Application of Grey Relational Analysis in Oil and Gas Resource Exploration

Since its inception in 1982, grey relational analysis (GRA) has evolved from early point relational coefficient models and generalized grey relational analysis models to contemporary complex models integrating multiple methods and robustness assessment. Its research objects have also expanded from one-dimensional sequence similarity to relationship analysis of three-dimensional spatial bodies and even high-dimensional hypersurfaces. In the field of oil and gas resource exploration, GRA, with its adaptability to systems characterized by poor information and small samples, has been applied in engineering practice across multiple stages, including the screening of main controlling geological factors, comprehensive reservoir evaluation, productivity prediction and hydrocarbon-bearing property discrimination, and optimization of favorable exploration areas. However, existing studies still face common methodological problems such as the empirical determination of the resolution coefficient and the sensitivity of reference sequences, as well as characteristic problems in scenario applications such as weak three-dimensional spatial relational modeling and redundancy of geological indicators. On the basis of a systematic review of technological development and application status, this paper suggests seeking breakthroughs in directions such as constructing a systematic technical framework, hybrid intelligent integration coupled with cutting-edge algorithms, developing three-dimensional grey relational geological modeling technology, and building standardized evaluation procedures and open-source professional tools, with the aim of providing methodological support and engineering means for intelligent oil and gas resource exploration.