Abstract: Glutenite reservoir is characterized by large particle size range, low porosity and permeability, complex pore structure and strong heterogeneity, so it is difficult to predict its quality classification and productivity. Based on NMR logging, this paper proposes the classification scheme and productivity prediction method of glutenite reservoirs. Using the transverse relaxation time (T₂) distribution measured by NMR experiment of rocks, the paper extracts the characteristic parameters of T₂ distribution such as percentages of three-pore components (percentage of small pore components S₁, percentage of medium pore components S₂ and percentage of large pore components S₃) and geometric mean of T₂ distribution (T_{2_LM}), and builds the reservoir quality index (I_RQ) comprehensively reflecting the pore structure and physical properties of rock. Characteristic parameters of T₂ distribution and reservoir quality index have a good correlation with pore throat radius, displacement pressure and other mercury penetration experiment parameters, which can quantitatively characterize the rock pore structure. The classification chart of glutenite reservoirs has been established using S₃/S₁ and I_RQ. The productivity prediction comprehensive index (F) and the productivity prediction model of glutenite reservoir have been built based on S₃/S₁, T_{2_LM}, I_RQ and effective thickness (H) of the reservoir. The classification method and productivity prediction model of glutenite reservoirs based on NMR logging have achieved a good application effect in the glutenite reservoir of Baikouquan Formation in the west slope of Mahu sag, Junggar Basin, and the effectiveness and practicability of the method have also been verified, wichi is of certain reference significance for the research of glutenite reservoir classification and productivity.

Key words: glutenite reservoir, NMR logging, pore structure, reservoir classification, production prediction

摘要： 砂砾岩储层具有岩石颗粒粒径范围大、低孔低渗、孔隙结构复杂和非均质性强等特点，其品质分类与产能预测难度较大。基于核磁共振测井，提出了砂砾岩储层的分类方案与产能预测方法。利用岩石核磁共振实验测量的横向弛豫时间（T₂）分布，提取三孔隙组分百分比（小孔隙组分百分比S₁、中孔隙组分百分比S₂、大孔隙组分百分比S₃）、T₂分布几何平均值（T_{2_LM}）等T₂分布特征参数，构建了综合反映储层孔隙结构和岩石物理性质的储层品质指数（I_RQ）。T₂分布特征参数和储层品质指数与孔喉半径、排驱压力等压汞实验参数具有良好的相关性，可定量表征岩石孔隙结构。利用S₃/S₁和I_RQ建立了砂砾岩储层分类图版，基于S₃/S₁、T_{2_LM}、I_RQ和储层有效厚度（H）构建了砂砾岩储层的产能预测综合指数（F）和产能预测模型。基于核磁共振测井的砂砾岩储层分类方法和产能预测模型在准噶尔盆地玛湖凹陷西斜坡百口泉组砂砾岩储层研究中取得了良好的应用效果，验证了该方法的有效性和实用性。研究方法与认识对开展砂砾岩储层的分类与产能研究具有一定参考意义。

关键词: 砂砾岩储层, 核磁共振测井, 孔隙结构, 储层分类, 产能预测