Fine-grained lacustrine sedimentation controlled by astronomical cycles remains a research weakness in sedimentology studies,as most studies have concentrated on how astronomical cycles affect the normal lacustrine fi...Fine-grained lacustrine sedimentation controlled by astronomical cycles remains a research weakness in sedimentology studies,as most studies have concentrated on how astronomical cycles affect the normal lacustrine fine-grained sedimentation,but how they affect the lacustrine fine-grained event sedimen-tation has been rarely studied.Therefore,this work researched the characteristics of event sedimentation by systematically observing the cores from 30 cored wells in the Shahejie Formation of the Dongying Sag at a depth of over 1800 m,with more than 4000 thin sections being authenticated and over 1000 whole rocks being analyzed by X-ray diffraction(XRD).The research object was the Chunshang Sub-member of Upper Es_(4) in the Fanye 1 well,as it had the most comprehensive analysis data and underwent the most continuous coring.We divided astronomical cycles into different orders and made corresponding curves using the gamma-ray(GR)curve,spectral analysis,power spectrum estimation,and module extreme values,there were 6 long eccentricity periods,22 short eccentricity periods,65.5 obliquity cycles,and 110.5 precession cycles in this sub-member.On this basis,this study analyzed the control of astronomical cycles on the lacustrine fine-grained event sedimentation,and the research shows deposits were developed by slide-slump,turbidities,hyperpycnites,and tempestites in the Chunshang Sub-member of the Upper Es_(4),with higher long eccentricity,the monsoon climate contributes to the formation of storm currents,while with lower long eccentricity,the surface deposits are severely eroded by rivers and rainfalls,thus developing the slide-slump,turbidities,and hyperpycnites.The relationship between the lacustrine fine-grained event sedimentation and astronomical cycles was studied in this case study,which can promote research on fine-grained sedimentary rocks in genetic dynamics and boost the theoretical and disciplinary development in fine-grained sedimentology.展开更多
In this study,a computational framework in the field of artificial intelligence was applied in computational fluid dynamics(CFD)field.This Framework,which was initially proposed by Google Al department,is called"...In this study,a computational framework in the field of artificial intelligence was applied in computational fluid dynamics(CFD)field.This Framework,which was initially proposed by Google Al department,is called"TensorFlow".An improved CFD model based on this framework was developed with a high-order difference method,which is a constrained interpolation profile(CIP)scheme for the base flow solver of the advection term in the Navier-Stokes equations,and preconditioned conjugate gradient(PCG)method was implemented in the model to solve the Poisson equation.Some new features including the convolution,vectorization,and graphics processing unit(GPU)acceleration were implemented to raise the computational efficiency.The model was tested with several benchmark cases and shows good performance.Compared with our former CIP-based model,the present Tensor Flow-based model also shows significantly higher computational efficiency in large-scale computation.The results indicate TensorFlow could be a promising framework for CFD models due to its ability in the computational acceleration and convenience for programming.展开更多
基金supported by the Study on Astronomical Stratigraphic Period of Lacustrine Shale and High Resolution Sedimentary Cycle in Logging(41872166)of the National Natural Science Foundation of China and the Exploration and Development Research Institute,Shengli Oilfield Company,SINOPEC.
文摘Fine-grained lacustrine sedimentation controlled by astronomical cycles remains a research weakness in sedimentology studies,as most studies have concentrated on how astronomical cycles affect the normal lacustrine fine-grained sedimentation,but how they affect the lacustrine fine-grained event sedimen-tation has been rarely studied.Therefore,this work researched the characteristics of event sedimentation by systematically observing the cores from 30 cored wells in the Shahejie Formation of the Dongying Sag at a depth of over 1800 m,with more than 4000 thin sections being authenticated and over 1000 whole rocks being analyzed by X-ray diffraction(XRD).The research object was the Chunshang Sub-member of Upper Es_(4) in the Fanye 1 well,as it had the most comprehensive analysis data and underwent the most continuous coring.We divided astronomical cycles into different orders and made corresponding curves using the gamma-ray(GR)curve,spectral analysis,power spectrum estimation,and module extreme values,there were 6 long eccentricity periods,22 short eccentricity periods,65.5 obliquity cycles,and 110.5 precession cycles in this sub-member.On this basis,this study analyzed the control of astronomical cycles on the lacustrine fine-grained event sedimentation,and the research shows deposits were developed by slide-slump,turbidities,hyperpycnites,and tempestites in the Chunshang Sub-member of the Upper Es_(4),with higher long eccentricity,the monsoon climate contributes to the formation of storm currents,while with lower long eccentricity,the surface deposits are severely eroded by rivers and rainfalls,thus developing the slide-slump,turbidities,and hyperpycnites.The relationship between the lacustrine fine-grained event sedimentation and astronomical cycles was studied in this case study,which can promote research on fine-grained sedimentary rocks in genetic dynamics and boost the theoretical and disciplinary development in fine-grained sedimentology.
基金Supported by the National Natural Science Foundation of China(Grant No.51679212,51979245).
文摘In this study,a computational framework in the field of artificial intelligence was applied in computational fluid dynamics(CFD)field.This Framework,which was initially proposed by Google Al department,is called"TensorFlow".An improved CFD model based on this framework was developed with a high-order difference method,which is a constrained interpolation profile(CIP)scheme for the base flow solver of the advection term in the Navier-Stokes equations,and preconditioned conjugate gradient(PCG)method was implemented in the model to solve the Poisson equation.Some new features including the convolution,vectorization,and graphics processing unit(GPU)acceleration were implemented to raise the computational efficiency.The model was tested with several benchmark cases and shows good performance.Compared with our former CIP-based model,the present Tensor Flow-based model also shows significantly higher computational efficiency in large-scale computation.The results indicate TensorFlow could be a promising framework for CFD models due to its ability in the computational acceleration and convenience for programming.
