Tight oil reservoirs are key research targets of petroleum geological exploration. Due to their strong heterogeneity, reservoir classification is fuzzy and efficiency is low, which affects reservoir evaluation accuracy. This study aims to improve the accuracy of the evaluation of microscopic pore throats of tight reservoir. Tight oil reservoir is classified on the basis of microscopic pore-throat grading with machine learning technology including Box-Cox transformations, Grey relational analysis, Q-cluster analysis, and discriminant analysis, in combination with traditional measures of reservoir quality in the Fuyu oil layer, Bayanchagan area, Songliao Basin. The results show that Class I reservoirs are high-quality, medium compaction-strong dissolution-weak cementation reservoirs, with large pore-throat radii, concentrated from 0.16 μm to 1.00 μm. Class II reservoirs have medium potential, with strong compaction-medium dissolution-medium cementation. Pore throats have relatively uniform distribution with low connectivity, and radii mainly between 0.016 μm to 0.16 μm. The Class III reservoir has the lowest potential and strong heterogeneity, with strong compaction, weak dissolution, and strong cementation. Small pore-throat radii range from 0.002 μm to 0.016 μm. We infer that this method can effectively evaluate tight oil reservoirs and provide a basis for the prediction of favorable areas for tight oil exploration and development.

致密油藏是石油地质勘探的重点研究对象。由于储层非均质性强，储层分类模糊，效率低，影响储层评价精度。本研究旨在提高致密油藏微观孔喉评价的准确性。致密油藏是基于微观孔喉分级的机器学习技术进行分类的，包括Box-Cox变换，灰色关联分析，Q聚类分析和判别分析，并结合扶余油层的传统油藏质量度量松辽盆地巴彦察干地区。结果表明，Ⅰ类储层是优质，中等压实度强，溶解弱的胶结储层，孔喉半径大，浓度范围为0.16μm至1.00μm。II类储层具有中等潜力，具有强密实度-中度溶蚀-中度胶结作用。孔喉的分布相对均匀，连通性较低，半径主要在0.016μm至0.16μm之间。III类储层潜力最低，非均质性强，具有强夯实，弱溶性和强固结作用。小孔喉半径范围为0.002μm至0.016μm。我们认为，该方法可以有效评价致密油储层，为预测致密油勘探开发有利区域提供依据。III类储层潜力最低，非均质性强，具有强夯实，弱溶性和强固结作用。小孔喉半径范围为0.002μm至0.016μm。我们认为，该方法可以有效评价致密油储层，为预测致密油勘探开发有利区域提供依据。III类储层潜力最低，非均质性强，具有强夯实，弱溶性和强固结作用。小孔喉半径范围为0.002μm至0.016μm。我们认为，该方法可以有效评价致密油储层，为预测致密油勘探开发有利区域提供依据。