The microstructural processes occurring in metals and alloys during hot deformation are： DRX （dynamic recrystallization）, superplastic deformation, dynamic recovery, wedge cracking, void formation, inter-crystallin...The microstructural processes occurring in metals and alloys during hot deformation are： DRX （dynamic recrystallization）, superplastic deformation, dynamic recovery, wedge cracking, void formation, inter-crystalline cracking, prior particle boundary （FFB） cracking, and flow instability processes. Deformation characteristics of materials are interpreted as follows： in the low temperature （T≤0.25 of melting temperature） and high strain rate regime of 10 to 100 s-1, void formation occurs at hard particles and leads to ductile fracture. Many researchers used the currently defined statistical approaches to characterize images and extract useful information from the captured images. For more suitable of specific tasks, some researchers are introducing new texture features. HOS （higher-order statistics） estimate properties of three or more pixels occurring at specific locations relative to each other. GLRLMs （gray level run-length matrices） are popular method of HOS to extract texture features. This paper deals with texture features of GLRLM to predict strain rate values for Aluminum/Silicon Carbide.展开更多
Deep coalbed methane(CBM)resources are enormous and have become a hot topic in the unconventional exploration and development of natural gas.The fractures in CBM reservoirs are important channels for the storage and m...Deep coalbed methane(CBM)resources are enormous and have become a hot topic in the unconventional exploration and development of natural gas.The fractures in CBM reservoirs are important channels for the storage and migration of CBM and control the high production and enrichment of CBM.Therefore,fracture prediction in deep CBM reservoirs is of great significance for the exploration and development of CBM.First,the basic principles of calculating texture attributes by gray-level cooccurrence matrix(GLCM)and gray-level run-length matrix(GLRLM)were introduced.A geological model of the deep CBM reservoirs with fractures was then constructed and subjected to seismic forward simulation.The seismic texture attributes were extracted using the GLCM and GLRLM.The research results indicate that the texture attributes calculated by both methods are responsive to fractures,with the 45°and 135°gray level inhomogeneity texture attributes based on the GLRLM showing better identification effects for fractures.Fracture prediction of a deep CBM reservoir in the Ordos Basin was carried out based on the GLRLM texture attributes,providing an important basis for the efficient development and utilization of deep CBM.展开更多
文摘The microstructural processes occurring in metals and alloys during hot deformation are： DRX （dynamic recrystallization）, superplastic deformation, dynamic recovery, wedge cracking, void formation, inter-crystalline cracking, prior particle boundary （FFB） cracking, and flow instability processes. Deformation characteristics of materials are interpreted as follows： in the low temperature （T≤0.25 of melting temperature） and high strain rate regime of 10 to 100 s-1, void formation occurs at hard particles and leads to ductile fracture. Many researchers used the currently defined statistical approaches to characterize images and extract useful information from the captured images. For more suitable of specific tasks, some researchers are introducing new texture features. HOS （higher-order statistics） estimate properties of three or more pixels occurring at specific locations relative to each other. GLRLMs （gray level run-length matrices） are popular method of HOS to extract texture features. This paper deals with texture features of GLRLM to predict strain rate values for Aluminum/Silicon Carbide.
文摘Deep coalbed methane(CBM)resources are enormous and have become a hot topic in the unconventional exploration and development of natural gas.The fractures in CBM reservoirs are important channels for the storage and migration of CBM and control the high production and enrichment of CBM.Therefore,fracture prediction in deep CBM reservoirs is of great significance for the exploration and development of CBM.First,the basic principles of calculating texture attributes by gray-level cooccurrence matrix(GLCM)and gray-level run-length matrix(GLRLM)were introduced.A geological model of the deep CBM reservoirs with fractures was then constructed and subjected to seismic forward simulation.The seismic texture attributes were extracted using the GLCM and GLRLM.The research results indicate that the texture attributes calculated by both methods are responsive to fractures,with the 45°and 135°gray level inhomogeneity texture attributes based on the GLRLM showing better identification effects for fractures.Fracture prediction of a deep CBM reservoir in the Ordos Basin was carried out based on the GLRLM texture attributes,providing an important basis for the efficient development and utilization of deep CBM.
