A5110440283- Enhanced Oil Recovery Techniques
- Atmospheric and Environmental Gas Dynamics
- Hydraulic Fracturing and Reservoir Analysis
- Global Energy and Sustainability Research
- Hydrocarbon exploration and reservoir analysis
- Real-time simulation and control systems
- Software-Defined Networks and 5G
- Environmental Impact and Sustainability
- Maritime Transport Emissions and Efficiency
- Cloud Computing and Resource Management
- Graph theory and applications
- Gene Regulatory Network Analysis
- Atmospheric chemistry and aerosols
- Sustainable Industrial Ecology
- Drilling and Well Engineering
- Complex Network Analysis Techniques
- Methane Hydrates and Related Phenomena
- Carbon Dioxide Capture Technologies
- Software System Performance and Reliability
- Advanced Decision-Making Techniques
- Software Testing and Debugging Techniques
- Reservoir Engineering and Simulation Methods
- IoT and Edge/Fog Computing
The University of Texas at Austin
2024
China Telecom (China)
2022-2024
China Telecom
2022-2024
China University of Petroleum, Beijing
2020-2021
Chongqing University
2016
Growth in US liquefied natural gas (LNG) exports have increased concerns about the climate impacts of methane leakage along LNG supply chains. Current life cycle analysis (LCA) models chains are based on emissions estimates national inventories that been demonstrated to significantly underestimate emissions. In addition, recent top-down measurements exhibit significant sub-national spatial and temporal variation across oil (O&G) basins. this study, we develop a geospatial, measurement...
Addressing methane emissions across the liquefied natural gas (LNG) supply chain is key to reducing climate impacts of LNG. Actions address have emphasized importance use measurement-informed inventories, given systematic underestimation in official GHG emission inventories. Despite significant progress field measurements chain, no detailed at US liquefaction terminals are publicly available. In this work, we conduct multiscale, periodic and carbon dioxide two LNG over a 16-month campaign....
Methane measurements at liquefied natural gas (LNG) facilities play an important role in characterizing methane emissions from the supply chain. The large size and complexity of LNG make quantifying with ground-based monitoring systems challenging, making aerial platforms one preferred methods for these sites. However, typically provide a snapshot given instance, necessitating further analytical steps to infer both annualized range possible different instants time. This study uses two...
Growth in US liquefied natural gas (LNG) exports has increased concerns about the climate impacts of methane leakage along LNG supply chains. Current life cycle analysis (LCA) models chains are based on emission estimates national inventories that have been demonstrated to significantly underestimate emissions. In addition, recent top–down measurements emissions exhibit significant subnational spatial and temporal variations across oil (O&G) basins. this study, we develop a geospatial,...
There are quite a number of different metrics network robustness. This paper addresses the rationality four robustness (the algebraic connectivity, effective resistance, average edge betweenness, and efficiency) by investigating robust growth generalized meshes (GMs). First, heuristic algorithm Proximity-Growth algorithm) is proposed. The resulting proximity-optimal GMs intuitively hence adopted as benchmark. Then, mesh (GM) grown up stepwise optimizing given measure following findings...
Addressing methane emissions across the liquefied natural gas (LNG) supply chain is key to reducing climate impacts of LNG. Actions address have emphasized importance use measurement-informed inventories given systematic underestimation in official greenhouse (GHG) emission inventories. Despite significant progress field measurements GHG chain, no detailed at US liquefaction terminals are publicly available. In this work, we conduct multiscale, periodic and carbon dioxide two LNG over a...
The reliability of cloud computing platforms is crucial. Due to its numerous levels and components, testing requires a significant amount time. existing research aimed at shortening test time has room for improvement. They ignored situation that not all steps are necessary, which our direction We design virtual machine feature transformation method enable it reused across cases, thus avioding the spent in frequent creation deletion machine. In this scenario, we abstract problem into an...
Heavy oil reservoirs with edge-bottom water represent a huge portion of the world’s reserves, and effective development such cyclic steam stimulation (CSS) is significant for petroleum supply. However, cut some CSS wells increases, production decreases, increase circulation turns. Discerning source produced basis targeted treatment measures. In this paper, new model established discriminating from in reservoirs. The combines traditional hydrochemical characteristics analysis factor analysis,...
NFV systems are becoming more complicated with various of software modules, vendors and interfaces introduced. Testing such is very time consuming requires lots expertise. In this paper, we propose an efficient automatic testing framework to simplify speedup the process. There two critical components in framework, i.e., a structured reusable test case format abstraction layer adapt different tools. Based on tester can quickly compose cases by just setting corresponding parameters tools...
Abstract A major concern with water injection in offshore oil reservoir is the breakthrough. The formation heterogeneity main reason for it. In order to evaluate efficiency, a visualized 2-D experiment was carried out obtain distribution law of injected and variation parameters homogeneous heterogeneous formation. addition, coupled wellbore/reservoir model established by applying microelement method, superposition principle imaging. This considers pressure drop caused wellbore friction. sand...