In order to investigate the migration and accumulation efficiency of hydrocarbon natural gas in the Xujiaweizi fault depression, and to provide new evidence for the classification of its genesis, a source rock pyrolys...In order to investigate the migration and accumulation efficiency of hydrocarbon natural gas in the Xujiaweizi fault depression, and to provide new evidence for the classification of its genesis, a source rock pyrolysis experiment in a closed system was designed and carried out. Based on this, kinetic models for describing gas generation from organic matter and carbon isotope fractionation during this process were established, calibrated and then extrapolated to geologic conditions by combining the thermal history data of the Xushen-1 Well. The results indicate that the coal measures in the Xujiaweizi fault depression are typical ＂high-efficiency gas sources＂, the natural gas generated from them has a high migration and accumulation efficiency, and consequently a large-scale natural gas accumulation occurred in the area. The highly/over matured coal measures in the Xujiaweizi fault depression generate coaliferous gas with a high δ^13C1 value （〉 -20‰） at the late stage, making the carbon isotope composition of organic alkane gases abnormally heavy. In addition, the mixing and dissipation through the caprock of natural gas can result in the negative carbon isotope sequence （δ^13C1 〉δ^13C2 〉δ^13C3 〉δ^13C4） of organic alkane gases, and the dissipation can also lead to the abnormally heavy carbon isotope composition of organic alkane gases. As for the discovery of inorganic nonhydrocarbon gas reservoirs, it can only serve as an accessorial evidence rather than a direct evidence that the hydrocarbon gas is inorganic. As a result, it needs stronger evidence to classify the hydrocarbon natural gas in the Xujiaweizi fault depression as inorganic gas.展开更多
With the advent of the era of cloud computing, the high energy consumption of cloud computing data centers has become a prominent problem, and how to reduce the energy consumption of cloud computing data center and im...With the advent of the era of cloud computing, the high energy consumption of cloud computing data centers has become a prominent problem, and how to reduce the energy consumption of cloud computing data center and improve the efficiency of data center has become the research focus of researchers all the world. In a cloud environment, virtual machine consolidation(VMC) is an effective strategy that can improve the energy efficiency. However, at the same time, in the process of virtual machine consolidation, we need to deal with the tradeoff between energy consumption and excellent service performance to meet service level agreement(SLA). In this paper, we propose a new virtual machine consolidation framework for achieving better energy efficiency-Improved Underloaded Decision(IUD) algorithm and Minimum Average Utilization Difference(MAUD) algorithm. Finally, based on real workload data on Planet Lab, experiments have been done with the cloud simulation platform Cloud Sim. The experimental result shows that the proposed algorithm can reduce the energy consumption and SLA violation of data centers compared with existing algorithms, improving the energy efficiency of data centers.展开更多
基金the National Natural Science Foundation of China （No. 40572079）； the Program for New Century Excellent Talents in University （No. NCET-04-0345）； the Venture Capital Foundation of PetroChina （No. 2005-01-02）.
文摘In order to investigate the migration and accumulation efficiency of hydrocarbon natural gas in the Xujiaweizi fault depression, and to provide new evidence for the classification of its genesis, a source rock pyrolysis experiment in a closed system was designed and carried out. Based on this, kinetic models for describing gas generation from organic matter and carbon isotope fractionation during this process were established, calibrated and then extrapolated to geologic conditions by combining the thermal history data of the Xushen-1 Well. The results indicate that the coal measures in the Xujiaweizi fault depression are typical ＂high-efficiency gas sources＂, the natural gas generated from them has a high migration and accumulation efficiency, and consequently a large-scale natural gas accumulation occurred in the area. The highly/over matured coal measures in the Xujiaweizi fault depression generate coaliferous gas with a high δ^13C1 value （〉 -20‰） at the late stage, making the carbon isotope composition of organic alkane gases abnormally heavy. In addition, the mixing and dissipation through the caprock of natural gas can result in the negative carbon isotope sequence （δ^13C1 〉δ^13C2 〉δ^13C3 〉δ^13C4） of organic alkane gases, and the dissipation can also lead to the abnormally heavy carbon isotope composition of organic alkane gases. As for the discovery of inorganic nonhydrocarbon gas reservoirs, it can only serve as an accessorial evidence rather than a direct evidence that the hydrocarbon gas is inorganic. As a result, it needs stronger evidence to classify the hydrocarbon natural gas in the Xujiaweizi fault depression as inorganic gas.
基金supported by the National Natural Science Foundation of China (NSFC) (No. 61272200, 10805019)the Program for Excellent Young Teachers in Higher Education of Guangdong, China (No. Yq2013012)+2 种基金the Fundamental Research Funds for the Central Universities (2015ZJ010)the Special Support Program of Guangdong Province (201528004)the Pearl River Science & Technology Star Project (201610010046)
文摘With the advent of the era of cloud computing, the high energy consumption of cloud computing data centers has become a prominent problem, and how to reduce the energy consumption of cloud computing data center and improve the efficiency of data center has become the research focus of researchers all the world. In a cloud environment, virtual machine consolidation(VMC) is an effective strategy that can improve the energy efficiency. However, at the same time, in the process of virtual machine consolidation, we need to deal with the tradeoff between energy consumption and excellent service performance to meet service level agreement(SLA). In this paper, we propose a new virtual machine consolidation framework for achieving better energy efficiency-Improved Underloaded Decision(IUD) algorithm and Minimum Average Utilization Difference(MAUD) algorithm. Finally, based on real workload data on Planet Lab, experiments have been done with the cloud simulation platform Cloud Sim. The experimental result shows that the proposed algorithm can reduce the energy consumption and SLA violation of data centers compared with existing algorithms, improving the energy efficiency of data centers.
