Abstract: The fluidity attribute reflects the mobility of fluids and is commonly used to describe reservoir quality, becoming an important indicator for identifying and evaluating reservoir fluids. The accuracy of fluid fluidity attribute extraction significantly influences the effectiveness of reservoir identification, while the resolution of time-frequency analysis methods directly impacts the precision of fluid fluidity attribute extraction. To enhance the identification accuracy of reservoir fluids through fluid fluidity attribute, the generalized linear Chirplet Transform (GLCT), which exhibited superior time-frequency resolution, was introduced, and a method for extracting fluid fluidity attribute based on GLCT was proposed. Specifically, the dominant frequency of the reservoir was first determined by calculating the maximum value of the frequency spectrum derivative at the reservoir location. Subsequently, the first-order derivative of the amplitude with respect to frequency at the dominant frequency was extracted using GLCT to derive the fluid fluidity attribute of the reservoir. Both synthetic signal tests and real data analyses demonstrate that the fluidity attribute extracted via GLCT exhibits enhanced resolution for reservoirs and can accurately delineate the boundaries of thin reservoirs, providing a basis for identifying thin reservoirs.