Abstract <p>Resistivity anisotropy in bedded shales poses significant challenges for reservoir assessment in high-angle wells, mainly due to discrepancies between logging models and vertical well conditions. This study presents an integrated workflow for characterizing and correcting resistivity anisotropy in the Fengcheng Formation shale of the Mahu Sag. Petrophysical experiments and logging data reveal that anisotropy is influenced by the synergistic interaction of bedding density(<i>ρ</i>) and horizontal resistivity (<i>R</i>_<i>H</i>). Based on this, a composite parameter (<i>α</i> = lg(<i>R</i>_<i>H</i>) × <i>ρ</i>) was developed to enhance the prediction of the anisotropy coefficient (<i>λ</i>). An enhanced K-means clustering algorithm, utilizing high-resolution FMI (Formation Micro Imager) data, was employed to automate the identification of bedding planes. The anisotropy parameters were quantified by integrating the clustering results with a series–parallel resistor model, showing excellent agreement (discrepancies &lt; 10%) with experimental data. To correct resistivity distortions in high-angle wells, a joint inversion framework incorporating bedding structures and the Levenberg–Marquardt algorithm was established. Field validation of the method demonstrated that the corrected resistivity profiles align closely with vertical well reference data. This workflow provides a transferable solution for anisotropic resistivity correction, improving the accuracy of shale reservoir interpretation and supporting more efficient shale oil exploration.</p> Highlights <p><OrderedList> <ListItem> <ItemNumber>1.</ItemNumber> <ItemContent> <p>A composite parameter was developed to quantify the influence of sedimentary bedding on resistivity anisotropy, elucidating the governing mechanisms of anisotropic responses.</p> </ItemContent> </ListItem> <ListItem> <ItemNumber>2.</ItemNumber> <ItemContent> <p>Through FMI data-driven high-resolution bedding identification and resistivity anisotropy coefficient calculation, this study establishes a continuous anisotropy characterization method for laminated shales.</p> </ItemContent> </ListItem> <ListItem> <ItemNumber>3.</ItemNumber> <ItemContent> <p>A joint inversion architecture incorporating bedding structures and the Levenberg-Marquardt (LM) algorithm was implemented, enabling accurate resistivity anisotropy correction in highly deviated wells.</p> </ItemContent> </ListItem> </OrderedList></p>