Shengyu Yang

ORCID: 0000-0003-3730-1213
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About
Contact & Profiles
Research Areas
  • Hydrocarbon exploration and reservoir analysis
  • Petroleum Processing and Analysis
  • Hydraulic Fracturing and Reservoir Analysis
  • Geological Studies and Exploration
  • Enhanced Oil Recovery Techniques
  • Atmospheric and Environmental Gas Dynamics
  • Geochemistry and Geologic Mapping
  • Radioactive element chemistry and processing
  • NMR spectroscopy and applications
  • Geological and Geochemical Analysis
  • Geochemistry and Elemental Analysis
  • Geological and Geophysical Studies
  • Planetary Science and Exploration
  • Methane Hydrates and Related Phenomena
  • Seismic Waves and Analysis
  • Paleontology and Stratigraphy of Fossils
  • Metal and Thin Film Mechanics
  • Drilling and Well Engineering
  • Electromagnetic wave absorption materials
  • Coal and Its By-products
  • Magnetic Properties and Applications
  • CO2 Sequestration and Geologic Interactions
  • Coal Properties and Utilization
  • Plant-Microbe Interactions and Immunity
  • Bauxite Residue and Utilization

Changsha University of Science and Technology
2025

China University of Petroleum, East China
2020-2024

Qingdao National Laboratory for Marine Science and Technology
2020-2024

Southwest University
2024

GFZ Helmholtz Centre for Geosciences
2015-2024

Lanzhou University
2023

Xi'an Technological University
2021

ExxonMobil (United States)
2002

National Dong Hwa University
2000

Rice University
1999

Logging is critical for reservoir and fluid characterization by integrating the geophysical properties of rock layers. Traditional evaluation methods struggle with parameter selection, compromising predictive accuracy generalizability. Machine learning, particularly conditional generative adversarial networks (CGAN), offers a robust alternative, addressing disparity between labeled unlabeled logging data that can lead to discrepancies. This study applies CGAN augment data, enhancing input...

10.1063/5.0255353 article EN Physics of Fluids 2025-03-01

Porosity is a pivotal factor affecting the capacity for storage and extraction in shale reservoirs. The paucity of labeled data conventional well logs interpretation supervised learning models leads to inadequate generalization diminished prediction accuracy, thus limiting their effectiveness precise porosity evaluation. This study introduces contrastive – convolutional neural network (CL-CNN) framework that utilizes CL pretraining on vast array unlabeled data, followed by fine-tuning using...

10.1063/5.0206449 article EN Physics of Fluids 2024-05-01

The presence of some minerals can strongly influence the composition laboratory pyrolysates. question is whether similar effects may also occur in nature, thereby influencing gas–oil ratio and other bulk compositional characteristics. A series experiments have been conducted at varying heating rates to examine this issue. Three source rocks that vary significantly mineralogy (a quartz-rich, a calcite-rich, clay-rich sample), namely, Alum shale, Bowland Toolebuc oil respectively, were tested...

10.1021/acs.energyfuels.6b00934 article EN Energy & Fuels 2016-07-14

The Carboniferous Bowland Shale of northern England has drawn considerable attention because it been estimated to have 1329 trillion cubic feet hydrocarbons in-place (gas and liquids) resource potential (Andrews 2013). Here we report on the oil gas generation characteristics three selected whole-rock samples taken from cores their respective kerogen concentrates. Compositional kinetics phase properties primary secondary fluids were calculated through PhaseKinetics GOR-Fit approaches PVT...

10.1144/jgs2015-056 article EN Journal of the Geological Society 2015-11-25

Abstract The harsh radiation environment on Mars is widely believed to destroy organic matter, but elucidating the systematic degradation pathway and its controlling factors has proved elusive. Here we show alteration of macromolecular matter in ∼500-m.y.-old uranium-rich Alum Shale Formation (northwestern Europe), which suggested as a geological analogue Earth Martian surface samples, response ⟨-particle irradiation. composition quantity pyrolysates well extractability immature are governed...

10.1130/g47171.1 article EN Geology 2020-04-29

The correlation of lower Palaeozoic marine source rocks with reservoired oils by biomarkers is complex due to the uniform early Phanerozoic biomass (bacteria and algae) lack land plant animal input.Accordingly, main for most prolific oil province in Baltic Basin are still a matter debate.Ten 15 samples from five north European countries bordering Sea were analysed gas chromatography (GC) flame ionization detector, GC-MS (mass spectrometry), GC-MS/MS detect acyclic isoprenoids, aliphatic,...

10.1306/02071716194 article EN AAPG Bulletin 2017-12-01

Free oil, rather than adsorbed is the main contributor to shale oil production with current development technologies, and assessing contents in different occurrence states (adsorbed vs. free oil) a critical component evaluating economics of wells plays. Although various methodologies have been developed, there are still some fundamental issues shale. In this study, new method was developed estimate Second Member Eocene Kongdian Formation (Ek2) shales Cangdong Sag, Bohai Bay Basin. This...

10.3390/jmse12091557 article EN cc-by Journal of Marine Science and Engineering 2024-09-05

China has been said to have the largest putative shale gas resources in world. The highest potential occurs Sichuan Basin, with overmature Qiongzhusi (Cambrian) and Longmaxi (Silurian) Formations as prime exploration targets. Here, likelihood of late formation is examined using less mature equivalents from Georgina Basin (Australia) Baltic (Lithuania). We consider respective functions kerogen polar bitumen generation reference Eagle Ford, Yanchang, Niobrara, Vaca Muerta Formations. Both...

10.1306/11182018244 article EN AAPG Bulletin 2021-04-16
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