This paper systematically reviews the current applications of various spatial information technologies in CO_(2)sequestration monitoring,analyzes the challenges faced by spatial information technologies in CO_(2)seque...This paper systematically reviews the current applications of various spatial information technologies in CO_(2)sequestration monitoring,analyzes the challenges faced by spatial information technologies in CO_(2)sequestration monitoring,and prospects the development of spatial information technologies in CO_(2)sequestration monitoring.Currently,the spatial information technologies applied in CO_(2)sequestration monitoring mainly include five categories:eddy covariance method,remote sensing technology,geographic information system,Internet of Things technology,and global navigation satellite system.These technologies are involved in three aspects:monitoring data acquisition,positioning and data transmission,and data management and decision support.Challenges faced by the spatial information technologies in CO_(2)sequestration monitoring include:selecting spatial information technologies that match different monitoring purposes,different platforms,and different monitoring sites;establishing effective data storage and computing capabilities to cope with the broad sources and large volumes of monitoring data;and promoting collaborative operations by interacting and validating spatial information technologies with mature monitoring technologies.In the future,it is necessary to establish methods and standards for designing spatial information technology monitoring schemes,develop collaborative application methods for cross-scale monitoring technologies,integrate spatial information technologies with artificial intelligence and high-performance computing technologies,and accelerate the application of spatial information technologies in carbon sequestration projects in China.展开更多
The leakage of stored and transported CO2 is a risk for geological sequestration technology. One of the most challenging problems is to recognize and determine CO2 leakage signal in the complex atmosphere background. ...The leakage of stored and transported CO2 is a risk for geological sequestration technology. One of the most challenging problems is to recognize and determine CO2 leakage signal in the complex atmosphere background. In this work, a time series model was proposed to forecast the atmospheric CO2 variation and the approximation error of the model was utilized to recognize the leakage. First, the fitting neural network trained with recently past CO2 data was applied to predict the daily atmospheric CO2. Further, the recurrent nonlinear autoregressive with exogenous input(NARX) model was adopted to get more accurate prediction. Compared with fitting neural network, the approximation errors of NARX have a clearer baseline, and the abnormal leakage signal can be seized more easily even in small release cases. Hence, the fitting approximation of time series prediction model is a potential excellent method to capture atmospheric abnormal signal for CO2 storage and transportation technologies.展开更多
As P-wave velocity is sensitive to the variations in coal reservoir parameters,it is possible to monitor the injected CO_(2)through P-wave velocity during CO_(2)sequestration in coal.However,the effects of CO_(2)on th...As P-wave velocity is sensitive to the variations in coal reservoir parameters,it is possible to monitor the injected CO_(2)through P-wave velocity during CO_(2)sequestration in coal.However,the effects of CO_(2)on the coal P-wave velocity under triaxial stress are not clearly discerned.In the present study,different boundary conditions and gases were utilised to investigate the factors affecting the P-wave velocity after the interaction of coal with CO_(2).Experiments with helium indicated that the pore pressure primarily affected the P-wave velocity by altering the effective stress.Experiments with CH4 and CO_(2)indicated that matrix swelling induced-cleats porosity decline significantly promoted P-wave velocity.Moreover,CO_(2)caused a wider scale and severe weakening of coal matrix than CH4,thereby significantly decreasing the P-wave velocity,and the decline in P-wave velocity increases with vitrinite content.Furthermore,experiments under different boundary conditions showed that with the boundary condition having more constraints,the decrement of pore pressure on P-wave velocity is more weaken,whereas the improvement of matrix swelling on P-wave velocity is more evident.This study contributes to understanding the mechanism of effect of CO_(2)on P-wave velocity under triaxial stress condition and provides guidance for monitoring CO_(2)sequestration in coal.展开更多
Accurate quantification of tree populations within regions is critical for evaluating forest ecosystem conditions and developing effective forest management strategies[1].High-quality tree census data,collected throug...Accurate quantification of tree populations within regions is critical for evaluating forest ecosystem conditions and developing effective forest management strategies[1].High-quality tree census data,collected through field surveys and remote sensing technologies,is fundamental to China's sustainable development and environmental conservation initiatives.This data facilitates the monitoring of forest structural changes,carbon sequestration dynamics,and ecosystem health evaluations.Notably,China maintains the world's largest managed forest area,achieved through comprehensive national afforestation and reforestation programs[2,3].Consequently,precise tree enumeration is crucial for formulating effective forest management policies,monitoring and protecting wildlife habitats,and preventing natural disasters in China.展开更多
基金Supported by the CNPC Science and Technology Major Project(2021ZZ01-05).
文摘This paper systematically reviews the current applications of various spatial information technologies in CO_(2)sequestration monitoring,analyzes the challenges faced by spatial information technologies in CO_(2)sequestration monitoring,and prospects the development of spatial information technologies in CO_(2)sequestration monitoring.Currently,the spatial information technologies applied in CO_(2)sequestration monitoring mainly include five categories:eddy covariance method,remote sensing technology,geographic information system,Internet of Things technology,and global navigation satellite system.These technologies are involved in three aspects:monitoring data acquisition,positioning and data transmission,and data management and decision support.Challenges faced by the spatial information technologies in CO_(2)sequestration monitoring include:selecting spatial information technologies that match different monitoring purposes,different platforms,and different monitoring sites;establishing effective data storage and computing capabilities to cope with the broad sources and large volumes of monitoring data;and promoting collaborative operations by interacting and validating spatial information technologies with mature monitoring technologies.In the future,it is necessary to establish methods and standards for designing spatial information technology monitoring schemes,develop collaborative application methods for cross-scale monitoring technologies,integrate spatial information technologies with artificial intelligence and high-performance computing technologies,and accelerate the application of spatial information technologies in carbon sequestration projects in China.
基金the National Natural Science Foundation of China(21808181)China Postdoctoral Science Foundation(2019M653651)+1 种基金Shaanxi Provincial Science and Technology Department(2017ZDXM-GY-115)Basic Research Project of Natural Science in Shaanxi Province(2020JM-021)。
文摘The leakage of stored and transported CO2 is a risk for geological sequestration technology. One of the most challenging problems is to recognize and determine CO2 leakage signal in the complex atmosphere background. In this work, a time series model was proposed to forecast the atmospheric CO2 variation and the approximation error of the model was utilized to recognize the leakage. First, the fitting neural network trained with recently past CO2 data was applied to predict the daily atmospheric CO2. Further, the recurrent nonlinear autoregressive with exogenous input(NARX) model was adopted to get more accurate prediction. Compared with fitting neural network, the approximation errors of NARX have a clearer baseline, and the abnormal leakage signal can be seized more easily even in small release cases. Hence, the fitting approximation of time series prediction model is a potential excellent method to capture atmospheric abnormal signal for CO2 storage and transportation technologies.
基金supported by the National Natural Science Foundation of China(No.51974304)the Natural Science Foundation of Hebei Province(No.E2020402075)+2 种基金the 2nd Xplorer Prize sponsored by the Tencent Foundationthe Program for Changjiang Scholars and Innovative Research Team in University(No.IRT 17R103)the Qinglan Project of Jiangsu Province.
文摘As P-wave velocity is sensitive to the variations in coal reservoir parameters,it is possible to monitor the injected CO_(2)through P-wave velocity during CO_(2)sequestration in coal.However,the effects of CO_(2)on the coal P-wave velocity under triaxial stress are not clearly discerned.In the present study,different boundary conditions and gases were utilised to investigate the factors affecting the P-wave velocity after the interaction of coal with CO_(2).Experiments with helium indicated that the pore pressure primarily affected the P-wave velocity by altering the effective stress.Experiments with CH4 and CO_(2)indicated that matrix swelling induced-cleats porosity decline significantly promoted P-wave velocity.Moreover,CO_(2)caused a wider scale and severe weakening of coal matrix than CH4,thereby significantly decreasing the P-wave velocity,and the decline in P-wave velocity increases with vitrinite content.Furthermore,experiments under different boundary conditions showed that with the boundary condition having more constraints,the decrement of pore pressure on P-wave velocity is more weaken,whereas the improvement of matrix swelling on P-wave velocity is more evident.This study contributes to understanding the mechanism of effect of CO_(2)on P-wave velocity under triaxial stress condition and provides guidance for monitoring CO_(2)sequestration in coal.
基金supported by the National Key Research and Development Program of China(2022YFF1300203)the National Natural Science Foundation of China(42371329 and 32301285)。
文摘Accurate quantification of tree populations within regions is critical for evaluating forest ecosystem conditions and developing effective forest management strategies[1].High-quality tree census data,collected through field surveys and remote sensing technologies,is fundamental to China's sustainable development and environmental conservation initiatives.This data facilitates the monitoring of forest structural changes,carbon sequestration dynamics,and ecosystem health evaluations.Notably,China maintains the world's largest managed forest area,achieved through comprehensive national afforestation and reforestation programs[2,3].Consequently,precise tree enumeration is crucial for formulating effective forest management policies,monitoring and protecting wildlife habitats,and preventing natural disasters in China.
