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《Chinese Journal of Geophysics》 2019-01
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Study on digital rock reconstruction method based on sedimentological process

TIAN Zhi;XIAO LiZhi;LIAO GuangZhi;DONG Hu;TIAN ShouCeng;SONG XianZhi;State Key Laboratory of Petroleum Resources and Prospecting,China University of Petroleum;Exploration and Development Research Institute of Liaohe Oilfield Company;iRock Technologies;  
Digital Rock Physics(DRP)is widely used to accurately characterize pore structures and mineral distributions of hydrocarbon bearing rocks based on their three-dimensional(3D)images at micro-and nano-meter scales.It also plays an important role to numerically calculate rock elasticity,formation factor,permeability and simulate multi-phase flow properties etc.However,3D images are not always readily available for reservoir rocks and it is sometimes difficult to satisfy modeling requirements to cover heterogeneity due to limited rock volumes captured in 3D.Therefore,3D reconstruction methods become alternative approaches to model porous rocks.Comparing with statistical methods,geological process based reconstruction hasproved itself to be successful to reproduce sandstone structures.In this paper,we developed a method to improve the existing models with more realistic sedimentological processes and extend it to reconstruct shaly sandstone,carbonate rocks and shale by introducing more mechanism of diagenesis.The grain size distribution is extracted from a slice of 2D Micro-CT images using watershed segmentation algorithm;and then it is used as initial input information for the 3D reconstruction.The accuracy of modeling is evaluated by comparing their local porosity distributions and average percolation probability function distributions of the 3D digital rock images obtained by MicroCT imaging.The results show that our reconstruction can accurately reproduce heterogeneity and percolation characteristics of original Micro-CT images,which provide geologically realistic rock models for petrophysical studies.
【Fund】: 国家自然科学基金(21427812 41674137 41504101);; “111”创新引智基地(B13010)联合资助
【CateGory Index】: TE311
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