Qian Sun

ORCID: 0000-0002-4926-2883
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About
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Research Areas
  • Reservoir Engineering and Simulation Methods
  • Enhanced Oil Recovery Techniques
  • Hydraulic Fracturing and Reservoir Analysis
  • Hydrocarbon exploration and reservoir analysis
  • CO2 Sequestration and Geologic Interactions
  • Coal Properties and Utilization
  • Rock Mechanics and Modeling
  • Drilling and Well Engineering
  • Geological and Geochemical Analysis
  • Grouting, Rheology, and Soil Mechanics
  • Methane Hydrates and Related Phenomena
  • Advanced Mathematical Modeling in Engineering
  • Innovative concrete reinforcement materials
  • Geological and Geophysical Studies
  • earthquake and tectonic studies
  • Concrete and Cement Materials Research
  • Geoscience and Mining Technology
  • High-pressure geophysics and materials
  • Advanced Numerical Methods in Computational Mathematics
  • Oil and Gas Production Techniques
  • Nuclear and radioactivity studies
  • Composite Material Mechanics
  • Geotechnical Engineering and Analysis
  • Remote Sensing and Land Use
  • Landslides and related hazards

China University of Geosciences (Beijing)
2003-2025

Wuhan University of Technology
2007-2025

Tianjin Chengjian University
2025

China Building Materials Academy
2023-2025

University of Jinan
2023-2024

National Institute for Radiological Protection
2023-2024

University of Science and Technology Liaoning
2024

Hubei Normal University
2024

Xuzhou Medical College
2023

Cell Technology (China)
2023

In computer vision, superpixels have been widely used as an effective way to reduce the number of image primitives for subsequent processing. But only a few attempts made incorporate them into deep neural networks. One main reason is that standard convolution operation defined on regular grids and becomes inefficient when applied superpixels. Inspired by initialization strategy commonly adopted traditional superpixel algorithms, we present novel method employs simple fully convolutional...

10.1109/cvpr42600.2020.01398 article EN 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020-06-01

This article provides a comprehensive review of the state-of-art in area artificial intelligence applications to solve reservoir engineering problems. Research works including proxy model development, artificial-intelligence-assisted history-matching, project design, and optimization, etc. are presented demonstrate robustness systems. The successes developments prove advantages AI approaches terms high computational efficacy strong learning capabilities. Thus, implementation models enables...

10.3390/en12152897 article EN cc-by Energies 2019-07-27

Over the years we have seen recommender systems shifting focus from optimizing short-term engagement toward improving long-term user experience on platforms. While defining good is still an active research area, one specific aspect of improved here, which revisiting platform. These long term outcomes however are much harder to optimize due sparsity in observing these events and low signal-to-noise ratio (weak connection) between a single recommendation. To address challenges, propose...

10.1145/3534678.3539073 article EN Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2022-08-12

Summary Utilizing underground geological structures for hydrogen storage is an effective approach energy transformation. The depleted shale reservoirs can be considered as promising options large-scale because of the vast capacity, high containment security, and low operation cost. However, it challenging to characterize transportation mechanism estimate potential in formations from multiscale perspectives. In this paper, we propose a model transport partially hydraulically fractured...

10.2118/219472-pa article EN SPE Journal 2024-02-28

10.1007/s00362-025-01672-3 article EN Statistical Papers 2025-02-13
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