An improved interval fuzzy GRA-TOPSIS model for sustainable investment decision-making of oil and gas blocks

Abstract

Facing volatile oil prices, strict ecological regulations and complex geological conditions, traditional multi-attribute decision-making (MADM) methods for oilfield investment overemphasize economic benefits while ignoring non-economic indicators and attribute uncertainty. To solve these deficiencies, this paper proposes an improved MADM framework for oil and gas development investment decision-making. Firstly, a five-dimensional evaluation index system covering economic, technological, geological, ecological and social attributes is established. Secondly, interval-valued fuzzy numbers (IVFNs) and interval fuzzy analytic hierarchy process (IF-AHP) are adopted to quantify index weights and address decision uncertainty. Furthermore, grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to rank development schemes. A case study of six oilfield blocks in China verifies the reliability of the proposed framework. The results indicate that this method can effectively reduce decision bias and comprehensively characterize multidimensional attributes. This study provides a systematic decision-making tool for oilfield investment optimization and offers references for the sustainable development of oil and gas resources.