Understanding the microheterogeneity of tight sandstone is the basis of reservoir science, and quantitative characterization of the reservoir’s microheterogeneity is key to reservoir evaluation. In this study, an image-processing analysis method to study the heterogeneity of tight reservoirs is established. A modified Image J plugin is used to accurately identify the surface porosity of a thin casting sheet; the heterogeneity of the microscopic pores in a reservoir is then abstracted into discrete values of the surface porosity. A new parameter for quantitative characterization of the microscopic heterogeneity of tight sandstone, that is, the heterogeneity index Q, is proposed. The fractal dimension calculated via a liquid nitrogen adsorption experiment is used to test the new parameter, and the geological significance of Q is discussed. The results show that Q has a good positive correlation with the fractal dimension, which is beneficial in determining the heterogeneity of the reservoir, pore throat distribution, and roughness of the pore surface. Q has a good correlation with physical parameters such as the specific surface area, average pore diameter, and total pore volume of the sample, indicating that this index can effectively characterize and quantitatively evaluate the reservoir. Therefore, this parameter provides a new basis for reservoir evaluation and classification and provides a new direction for delineating advantageous horizons as well as guiding development and mining.

了解致密砂岩的微观非均质性是储层科学的基础，定量表征储层的微观非均质性是评价储层的关键。本研究建立了一种研究致密油藏非均质性的图像处理分析方法。改进的Image J插件用于准确识别薄铸板的表面孔隙率；然后，将储层中微观孔隙的非均质性抽象为表面孔隙度的离散值。定量表征致密砂岩微观非均质性的新参数，即非均质性指数Q，建议。通过液氮吸附实验计算得到的分形维数用于测试新参数，并讨论了Q的地质意义。结果表明，Q与分形维数具有良好的正相关性，有利于确定储层的非均质性，孔喉分布和孔表面粗糙度。问与比表面积，平均孔径和样品的总孔体积等物理参数具有良好的相关性，表明该指数可以有效地表征和定量评价储层。因此，该参数为储层评价和分类提供了新的依据，为划定有利的层位以及指导开发和开采提供了新的方向。