Rock Fabric Characteristics And Pore Structure Evaluation Methods Of Tight Clastic Gas Reservoirs

Unconventional oil and gas resources have become one of the important targets of global exploration,and tight clastic gas reservoirs are becoming more and more important as a part of unconventional natural gas.Tight clastic rocks have various types of lithology and complex structures,reservoir space,reservoir property and strong heterogeneity of pore structure.Rock components,structure and pore structure are closely related to the reservoir quality.The study of the rock fabric,lithofacies,pore structure characteristics,logging identification and evaluation have become the most important problems in reservoir effectiveness analysis.There is a thick tight clastic sedimentary deposit in the Wangfu Fault Depression,which has major exploration potential for tight gas.Based on the study case of tight clastic rock of the Denglouku Formation in Wangfu Fault,mass data including core description,thin section authentication,XRD,physical property,mercury penetration,nuclear magnetic resonance,electron microscope and logging curves are used to research the fabric characteristics,lithofacies classification,lithofacies identification,pore structure characteristics analysis,type identification,calculation of pore structure parameters and well logging evaluation methods.(1)Considering the physical properties,imaging logging and conventional logging curves in the microscopic point,the rock fabric features are analysised,.The effect of rock fabric properties on reservoir effectiveness are researched.Furthermore,the elemental logging mineral model and the skeleton acoustic time-difference calculation are used to characterize the rock components and rock structure.Then,the tight clastic rocks are divided into 6 main types of lithofacies with consideration of rock composition and structural characteristics,and the types of lithofacies are effectively identified on the basis of the logging characterization of rock fabric.(2)The characteristics of capillary pressure curve are analyzed,and the pore structure types are divided into 3 categories,4 subcategories,and physical properties,NMR and well logging data are ued to analyze the characteristics of pore structure.On this basis,the pore structure types are qualitatively identified by using the logging sensitivity curves and NMR T2 spectral morphological features.Then the fractal dimension values of T2 magnetic resonance spectroscopy sensitive parameters are extracted,and their correlations with logging values are analyzed.And the computational models of fractal dimension of T2 are established to qualitatively identify the pore structure types.A qualitative and quantitative pore structure type identification scheme are determined.(3)The relationship between the mineral composition,rock structure and pore structure are analyzed based on the experimental test data.It's proved that the rock fabric is closely related to pore structure.(4)The porosity and permeability calculation model are established based on the pore structure classification,and a calculation model for effective porosity is established by calculation of irreducible water saturation.The calculation accuracy of pore structure parameters is improved.(5)Finally,the effective porosity,permeability,and reservoir quality index(RQI)are used as evaluation parameters of reservoir pore structure.The relationship between the above parameters and pore structure parameters such as expulsion pressure,maximum mercury saturation,median pressure,and average pore throat radius are analyzed.The well structure evaluation method for well structure is established to provide a reliable basis for the evaluation of the effectiveness of compact clastic reservoirs.The series of methods in the article improve the accuracy of favorable reservoir evaluation by logging for tight clastic rock.Using logging information to analysis the characteristics,relationships,and effects of reservoir composition,structure,and pore structure on reservoir validity,and taking full advantages of continuous and high-resolution logging information and compactness of logging information have good promotion value of the prediction of clastic rock stratum.