The present application relates to a dessert
identification technology field, and is a low-permeability reservoir dessert identification method and device combining dynamic and static parameters, which comprises the following steps: evaluating the development degree of each cluster of fractures according to the change amount of
anisotropy of the formation before and after fracturing; calculating the yield contribution rate of each cluster according to the yield of each cluster; determining the reservoir
quality score of each cluster by using the
evaluation result of the development degree of each cluster of fractures and the yield contribution rate of each cluster; and screening out the cluster with a reservoir
quality score greater than or equal to a threshold
score, which is regarded as the best dessert reservoir section. The present application screens out the best dessert reservoir with high yield and developed fracturing fractures by combining the yield contribution rate of each cluster after fracturing and the development degree of the fractures after fracturing, thereby improving the identification precision of the dessert reservoir in the low-permeability reservoir. In addition, the present application can also combine the
grey correlation method to reversely analyze the main control factors of the best dessert reservoir on the
logging and
well logging data, thereby guiding the geological steering in the later drilling, improving the drilling rate of the best dessert reservoir, guiding the fracturing segmentation and clustering, and improving the
production rate of the best dessert reservoir.