The transportation of magma in sedimentary basins often occurs through extensive dyke-sill networks.The role of sills on the plumbing system in rifted margins and the impact of sills on hydrocarbon reservoirs of prosp...The transportation of magma in sedimentary basins often occurs through extensive dyke-sill networks.The role of sills on the plumbing system in rifted margins and the impact of sills on hydrocarbon reservoirs of prospective sedimentary basins has long been an area of great industrial interest and scientific debate.Based on 2D seismic reflection,we present data on how the sills emplaced to form a magmatic plumbing system of the volcanic system for the Zhongjiannan Basin(ZJNB).The results show that sixty-nine sills and fourteen forced folds have been identified.The distribution and geometry of the sills suggest that magma flowed from west to east and then ascended to near the surface.The onlap relationship of the forced folds indicates that the timing of magmatic activities can be constrained at ca.0.2 Ma.The spatial and temporal occurrences of intrusions imply that the strong post-rift magmatism in ZJNB was associated with the Hainan mantle plume arising from the core-mantle boundary.Furthermore,these forced folds could produce several types of hydrocarbon traps,due to accommodation through bending and uplift of the overlying rock and free surface,but it is critical to evaluate the effect of such emplacement when setting exploration targets.展开更多
In the last few decades,deep learning(DL)has afforded solutions to macroscopic problems in petroleum engineering,but mechanistic problems at the microscale have not benefited from it.Mechanism studies have been the st...In the last few decades,deep learning(DL)has afforded solutions to macroscopic problems in petroleum engineering,but mechanistic problems at the microscale have not benefited from it.Mechanism studies have been the strong demands for the emerging projects,such as the gas storage and hydrate production,and for some problems encountered in the storage process,which are common found as the chemical interaction between injected gas and mineral,and the formation of hydrate.Emerging advances in DL technology enable solving molecular dynamics(MD)with quantum accuracy.The conventional quantum chemical method is computational expensive,whereas the classical MD method cannot guarantee high accuracy because of its empirical force field parameters.With the help of the DL force field,precision at the quantum chemistry level can be achieved in MD.Moreover,the DL force field promotes the computational speed compared with first-principles calculations.In this review,the basic knowledge of the molecular force field and deep neural network(DNN)is first introduced.Then,three representative opensource packages relevant to the DL force field are introduced.As the most common components in the development of oil and gas reservoirs,water and methane are studied from the aspects of computational efficiency and chemical reaction respectively,providing the foundation of oil and gas researches.However,in the oil and gas problems,the complex molecular topo structures and various element types set a high challenge for the DL techniques in MD.Regarding the computational efficiency,it needs improvement via GPU and parallel accelerations to compete with classical MD.Even with such difficulties,the booming of this technique in the area of petroleum engineering can be predictable.展开更多
基金supported by the National Key Research and Development Project(2019YFA0708500)the National Natural Science Foundation of China(No.42202170 and U20B6001)。
文摘The transportation of magma in sedimentary basins often occurs through extensive dyke-sill networks.The role of sills on the plumbing system in rifted margins and the impact of sills on hydrocarbon reservoirs of prospective sedimentary basins has long been an area of great industrial interest and scientific debate.Based on 2D seismic reflection,we present data on how the sills emplaced to form a magmatic plumbing system of the volcanic system for the Zhongjiannan Basin(ZJNB).The results show that sixty-nine sills and fourteen forced folds have been identified.The distribution and geometry of the sills suggest that magma flowed from west to east and then ascended to near the surface.The onlap relationship of the forced folds indicates that the timing of magmatic activities can be constrained at ca.0.2 Ma.The spatial and temporal occurrences of intrusions imply that the strong post-rift magmatism in ZJNB was associated with the Hainan mantle plume arising from the core-mantle boundary.Furthermore,these forced folds could produce several types of hydrocarbon traps,due to accommodation through bending and uplift of the overlying rock and free surface,but it is critical to evaluate the effect of such emplacement when setting exploration targets.
基金We would like to express appreciation to the following financial support:National Natural Scientific Foundation of China(Grants No.51936001)King Abdullah University of Science and Technology(KAUST)through the grants BAS/1/1351-01,URF/1/4074-01,and URF/1/3769-01.
文摘In the last few decades,deep learning(DL)has afforded solutions to macroscopic problems in petroleum engineering,but mechanistic problems at the microscale have not benefited from it.Mechanism studies have been the strong demands for the emerging projects,such as the gas storage and hydrate production,and for some problems encountered in the storage process,which are common found as the chemical interaction between injected gas and mineral,and the formation of hydrate.Emerging advances in DL technology enable solving molecular dynamics(MD)with quantum accuracy.The conventional quantum chemical method is computational expensive,whereas the classical MD method cannot guarantee high accuracy because of its empirical force field parameters.With the help of the DL force field,precision at the quantum chemistry level can be achieved in MD.Moreover,the DL force field promotes the computational speed compared with first-principles calculations.In this review,the basic knowledge of the molecular force field and deep neural network(DNN)is first introduced.Then,three representative opensource packages relevant to the DL force field are introduced.As the most common components in the development of oil and gas reservoirs,water and methane are studied from the aspects of computational efficiency and chemical reaction respectively,providing the foundation of oil and gas researches.However,in the oil and gas problems,the complex molecular topo structures and various element types set a high challenge for the DL techniques in MD.Regarding the computational efficiency,it needs improvement via GPU and parallel accelerations to compete with classical MD.Even with such difficulties,the booming of this technique in the area of petroleum engineering can be predictable.
