Conventional logging interpretation methods qualitatively identify shale reservoirs using shale attribute parameters and interpretation templates. However, improving the identification accuracy of complex shale reservoirs is challenging due to the numerous evaluation parameters and the complexity of model calculations. To quantitatively characterize high-quality shale reservoirs effectively, this study utilizes the JY6-2 and JY10-4 wells in the Fuling shale gas field as examples. It establishes a comprehensive evaluation method for identifying high-quality shale gas reservoirs, utilizing multi-fractal spectrum analysis of well logging. Firstly, the conventional well logs were qualitatively analyzed and evaluated using the methods of multiple fractals and R/S analysis. Subsequently, a gray relational analysis is employed to combine the production well logging, which reflects dimensionless productivity contributions, with the fractal characteristics of conventional well logs to obtain the corrected weight multifractal spectrum width Δα^′ and fractal dimension D^′. Comprehensive fractal evaluation indexes λ and γ are introduced, forming three categories of productivity evaluation standards for shale gas reservoirs characterized by fractals. The calculation results show that the Δα^′ comprehensive fractal evaluation index for Class Ⅰ gas reservoirs is 0.6 < λ < 1, and the D^′ comprehensive fractal evaluation index is 0 < γ < 0.5; for Class Ⅱ gas reservoirs, the Δα^′ comprehensive fractal evaluation index is 0.25 < λ < 0.6, and the D^′ comprehensive fractal evaluation index is 0.5 < γ < 0.8; for Class Ⅲ gas reservoirs, the Δα^′ comprehensive fractal evaluation index is 0 < λ < 0.25, and the D^′ comprehensive fractal evaluation index is 0.8 < γ < 1. Overall, the comprehensive fractal evaluation index of the high-production wells Δα^′ is close to 1 and shows a decreasing trend from high to low production; the comprehensive fractal evaluation index of the low-production wells with the R/S fractal dimension D^′ is close to 1 and shows a decreasing trend from low-production to high-production. Finally, Well JY8-2 is employed as a validation well to demonstrate the effectiveness of the evaluation method. This research method is a simple way to extract the multifractal spectra based on conventional logging data to evaluate comprehensive sweet spot zones. It is of great significance for identifying high-quality reservoir areas in shale gas reservoirs, and provides technical support for the effective development of shale reservoirs on a large scale.