Petroleum Science

Open access

ISSN: 1995-8226

Petroleum Science

Open access

Editor-in-Chief

Lizhi Xiao

Editorial Board

Petroleum Science is a peer-reviewed, open-access international journal sponsored by China University of Petroleum and co-published with KeAi. It focuses on cutting-edge topics in petroleum, petrochem...

Petroleum Science is a peer-reviewed, open-access international journal sponsored by China University of Petroleum and co-published with KeAi. It focuses on cutting-edge topics in petroleum, petrochemical, and subsurface energy resources, publishing innovative and significant research in both fundamental theories and applied technologies across the following areas:

1. Petroleum Resources & Engineering

2. Oil & Gas Storage and Transportation Engineering

3. Petrochemistry & Chemical Engineering

4. Petroleum Economics & Management

5. Oil & Gas Materials Science

6. AI Applications in Petroleum & Petrochemicals

7. Emerging fields (e.g., geothermal energy, CCUS, gas hydrates, geological hydrogen)

The journal serves as a high-level platform for global academic exchange, promoting the dissemination of the latest research advancements in petroleum science and engineering. It welcomes original research articles, reviews, and short communications.

Editorial Board

Coordinate-transformation-based fast sweeping method for the factored eikonal equation on triangular meshes

Effect of CO2 pre-injection on fracture propagation morphology in shale reservoirs under CO2 hybrid fracturing

The control of paleo-geomorphology on the depositional architecture of a Late Jurassic axial submarine fan, North Sea, UK

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1. Synthetic polymers: A review of applications in drilling fluids

2. Physics-informed graph neural network for predicting fluid flow in porous media

3. Production decline curve analysis of shale oil wells: A case study of Bakken, Eagle Ford and Permian

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News

Petroleum Science Latest Impact Factor Announced: 6.1

Petroleum Science CiteScore 2024 Announced: 9.4

Petroleum Science 2023 impact factor: 6.0

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Call for Papers

Special Issue on InterPore2022: Uncertainty quantification and machine learning in porous media

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Article Collections

AI application in Petroleum Science

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