多孔性
地质学
致密气
毛细管压力
磁导率
饱和(图论)
测井
矿物学
化学
多孔介质
岩土工程
水力压裂
石油工程
生物化学
膜
数学
组合数学
作者
Jianping Yan,Xu He,Shaolong Zhang,Chun-Zhen Feng,Jun Wang,Qinhong Hu,Jingong Cai,Min Wang
标识
DOI:10.1016/j.marpetgeo.2019.08.025
摘要
Abstract The evaluation of the pore structure of tight sandstone reservoirs has a significant influence on the effective exploration and development of tight sandstone oil. Laboratory measurements including scanning electron microscopy (SEM), mercury-injection capillary pressure (MICP), gas adsorption, nuclear magnetic resonance (NMR), and Nano-CT can provide detailed pore structure data. However, only NMR results can be used to evaluate the pore structure in a logging profile due to NMR logging. In this study, the relationships between NMR T2 distribution, pore structure, and pore size of tight sandstone in Chang 7 of the Yanchang Formation, in the Heshui area of the Ordos Basin, are analyzed based on NMR principles. The characteristics of the NMR T2 distribution of different rock samples are analyzed; the sensitive parameters of the NMR T2 spectrum are proposed. These parameters are then used to classify pore structure types in tight sandstone reservoirs and divide the active layers in the logging profile of the study area. The results indicate that different pore size structures have different distributions, and that the NMR T2 spectrum can highlight the difference in the pore structure type and pore size distribution using sensitive parameters such as T2P2 (the value of T2 corresponding to the last peak of the bimodal NMR T2 spectrum) and TDM (the mean value of T2 relaxation time obtained by weighted average method). As the pore structure of the rock samples in the study area worsened, their porosity and permeability worsened, T2P2 and TDM decreased, and the displacement pressure and NMR irreducible water saturation increased. The results of classifying the pore structure types obtained in the logging profile are helpful in evaluating the effectiveness of the reservoir and in the broad application of NMR logging in terms of understanding pore structure.
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