Objectives: A breakthrough has been made in natural gas exploration of bauxite reservoirs in Permian Taiyuan Formation. Aluminiferous rock series were thought to be good caprocks, but nowadays they have been proven to be good gas reservoirs. Reservoir characterization is a big challenge due to special mineral contents and complex logging responses of conventional logs. To better reveal the reservoir quality and identify fluid type, advanced logging technologies together with integrated evaluation were utilized. Methods, Procedures, Process: First, elemental concentrations such as silicon, calcium, aluminum, iron, sulfur, carbon were obtained based on spectroscopy data, and minerals were derived by oxide-closure method and calibrated by core data; second, lithology-independent porosity was calculated using nuclear magnetic resonance logging data, and pore structure were analyzed; third, rock texture was classified based on electrical image data and cores; fourth, far field sonic data was used to identify features far away from the wellbore; finally, fluid identification was performed using multiple advanced methods. Results, Observations, Conclusions: The aluminiferous rock series can be divided into 3 layers according to elemental concentrations. The bottom layer is aluminous mudstone with high iron and sulfur contents; the medium layer is mainly bauxite with high aluminum content and low silicon content; the top layer is aluminous mudstone with high carbon content. Good reservoirs usually locate at the medium layer. The aluminiferous rock series have 5 types of textures according to electrical images and cores, namely massive, interbedded, thinly laminated, patchy, and psephitic. The psephitic bauxite has the best reservoir quality with high effective porosity, high free fluid porosity and more big pores. High production wells usually have high formation dips, big bauxite thickness, and obvious reflectors 20-45m away from the wellbore based on the 3D far field sonic data. The achievements have dramatically improved geological understanding of the reservoir and provided valuable information for deployment of new wells. Novel/Additive Information: It is the first time to do an integrated reservoir evaluation for this special kind of reservoirs using advanced logging technologies and core data. The evaluation result matches well with the well production data.