<p>This study introduces the “mineral-pore integration” paradigm to address unresolved challenges in understanding flow characteristics within heterogeneous tight oil reservoirs. By analyzing the complementary relationship between minerals and pore-fractures, we highlight the critical role of mineralogical composition in regulating fluid flow dynamics. Existing research has focused on the qualitative pore morphology and size characterization, neglecting the quantitative dependency between minerals and pore structures. To bridge this gap, we propose the development of quantitative discrimination models using machine learning algorithms to decode mineral-pore coupling mechanisms. Additionally, we advocate for multiscale experimental and numerical approaches, including multi-physics field coupling simulations and microscale visualization experiments, to quantify flow disparities in pores formed by different minerals (e.g., feldspar, clay, carbonate). The integration of these methods aims to reveal novel flow behaviors, optimize displacement strategies, and enhance residual oil recovery. This framework provides a foundational basis for precise reservoir management by linking mineralogy to pore-scale flow mechanisms, offering actionable insights for tight oil exploitation.</p>