The geological structure and reservoir characteristics of low-permeability carbonate gas reservoirs are complex

and the high uncertainty in data acquisition and interpretation makes it challenging to identify optimal development areas. To address this

the study introduces an intuitionistic fuzzy Multi-Attributive Border Approximation area Comparison（MABAC） model

combined with the Best Worst Method（BWM） for weighting

to select the most suitable areas for developing these reservoirs. The approach begins by establishing a comprehensive evaluation index system that considers geological characteristics

hydrocarbon generation capacity

and gas storage capability of the low-permeability carbonate formations. This system not only integrates geological data but also considers the construction conditions relevant to these reservoirs. Using the BWM

weights for each key evaluation indicator are determined

taking into account the multifactorial impacts on various oil and gas fields and establishing the hierarchical relationships between these factors. An improved intuitionistic fuzzy multi-attribute decision-making model is then developed. This model uses intuitionistic fuzzy data instead of precise information

enhancing the selection process for favorable areas. The application of this model on ten candidate blocks indicated that Block C is the most favorable

outperforming others in terms of remaining dynamic reserves

effective reservoir thickness

and other crucial indicators. The blocks were ranked as follows based on the overall distance value: Block C Block I Block H Block A Block D Block G Block J Block E Block F Block B. The effectiveness and rationality of the proposed intuitionistic fuzzy MABAC method were validated through comparisons with existing methods and analysis of numerical simulation results

confirming its utility in optimizing the development of low-permeability carbonate gas reservoirs.