Optimal Selection of Oil and Gas Exploitation Projects Based on Gray Multiattribute Decision-Making

Selecting optimal technological projects for oil and gas extraction enterprises is a critical decision-making problem under high uncertainty, where traditional methods often ignore decision-makers’ psychological biases and inherent gray information. This study constructs a gray multiattribute decision-making model based on the cumulative prospect theory. The evaluation indicators covering effectiveness, technical, and economic criteria (10 specific metrics) are represented as interval gray numbers. By establishing scenario-specific reference points using positive and negative ideal solutions and employing gray distance measures, the model incorporates decision-makers’ risk attitudes using a cumulative prospect value function. Case validation demonstrated that the constructed indicator system and decision-making model were scientifically sound and feasible. The proposed method achieves higher discriminative power than TOPSIS and gray relational analysis, with comprehensive prospect values producing a clear ranking of alternatives. The model provides a new and effective solution for oil and gas extraction enterprises to optimize technological projects aimed at enhancing production and controlling water content, thereby providing significant practical value.