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Vol.1 (2025) Iss. 1

Advanced Energy Systems and Intelligent Geoscience

Advanced Energy Systems and Intelligent Geoscience (AESIG) is an international academic journal dedicated to the intersection of energy engineering, fundamental physics, and advanced computational science, dedicated to providing a high-quality academic exchange platform for researchers, scholars, and industry experts. The journal covers a wide range of research results, technological advancements, theoretical discussions, and practical applications in energy physics experimentation and computational technologies, with a particular focus on the cutting-edge dynamics and development trends in multi-physics characterization, AI-driven energy modeling, and quantum computing applications. We welcome experts and scholars from academia and industry around the world to submit original research articles, reviews, and technical reports, contributing to the diversity and academic value of the journal.
The Advanced Energy Systems and Intelligent Geoscience is committed to promoting knowledge sharing and collaboration in the academic community. The journal will regularly publish important topics and research directions related to complex reservoir simulation, renewable energy systems, and carbon neutrality technologies, helping readers understand and grasp the latest scientific research achievements and industry trends. In addition, the journal will invite authoritative experts in the field to write special articles, comments, and case studies, providing readers with in-depth academic resources.
We hope to become a bridge between academia and industry through the Advanced Energy Systems and Intelligent Geoscience, promoting interdisciplinary cooperation and knowledge exchange worldwide, and contributing to the development of sustainable and intelligent energy systems. [Aims & Scope]

Publisher: Macao Scientific Publishers (MOSP)

Editor-in-Chief: Yuhui Zhou, Xiang Rao | [View the Editorial Board]

Statement: 2025 © MOSP. The journal complies with the Open Access License (CC BY 4.0)

Print ISSN: 3106-9886 | Online ISSN: 3106-9894

Indexing: Under review

Quick Links: Submission Guidelines | Submission System | Contact Editors

Latest Articles

Review

Review of the Application of Upwind Generalized Finite Difference Method in Two-Phase Fluid-Solid Coupling of Porous Media

Authors: Yina Liu*

Abstract: Porous media oil-water two-phase fluid-solid coupling is critical for oil-gas exploitation efficiency and environmental protection, but traditional mesh-based methods (FDM, FEM, FVM) suffer from mesh generation difficulties, poor dynamic adaptability, and numerical dissipation. The Generalized Finite Difference Method (GFDM), a promising meshless approach [...] Read More.

Keywords: Closed-loop optimization; History matching; Production optimization; Optimization algorithm

AESIG 2025, 1(1), 4-23;

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Views：159

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Review

A Review of Integrated CCUS-EOR and Storage Prediction and Optimization: From Accelerated Compositional Simulation to Data–Physics Coupled Intelligent Models

Authors: Yunfeng Xu*, Zhuyi Zhu

Abstract: Carbon dioxide enhanced oil recovery with geological storage has attracted increasing attention because it can simultaneously improve hydrocarbon recovery and reduce emissions. Accurate and efficient prediction of development performance, together with reliable support for injection–production design and optimization, has therefore become a central scientific and engineering [...] Read More.

Keywords: CCUS-EOR; Numerical simulation; Reduced-order models; Deep learning; Data–physics coupling; Physics-informed neural networks

AESIG 2025, 1(1), 24-53;

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Views：297

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Review

Review of Reservoir Closed-Loop Optimization Control Methods

Authors: Deng Liu*

Abstract: This paper presents a review of reservoir closed-loop optimization management technology, with a particular focus on its core software component—reservoir closed-loop optimization control technology. This technology constitutes a closed-loop process encompassing two fundamental steps: automatic history matching and production optimization. History matching [...] Read More.

Keywords: Meshless method; Reservoir numerical simulation; Generalized finite difference method; Fluid-solid coupling; Numerical algorithm

AESIG 2025, 1(1), 54-65;

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Views：135

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Review

A Review of Gas Injection and Energy Supplement for Shale Condensate Gas Reservoirs

Authors: Chenjie Luo*

Abstract: Natural gas has become a core component of the global clean energy transition, and shale condensate gas reservoirs represent a high-value unconventional resource critical to improving national energy security, especially for countries with a coal-dominated energy mix like China. This paper reviews the current status of gas injection and energy supplement technologies [...] Read More.

Keywords: Shale condensate gas reservoir; Component gradient; Nano-confinement effect; Projection-based embedded discrete fracture model (pEDFM); Gas injection and energy supplement

AESIG 2025, 1(1), 66-79;

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Views：152

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Treatise

Boundary-integral Type Neural Network (BINN) for Flow Problems in Reservoirs

Authors: Yina Liu , Xiang Rao*, Xupeng He, Qirun Fu, Hussein Hoteit

Abstract: This study pioneers the application of Boundary-Integral Neural Networks (BINNs) to subsurface flow simulation, addressing steady-state single-phase flow governed by Laplace-type equations in hydrocarbon reservoirs. BINNs synergistically integrate boundary integral equations (BIEs) with deep learning to overcome limitations of traditional mesh-based methods [...] Read More.

Keywords: Deep Learning; Boundary integral equations (BIEs); Physics-informed neural networks (PINNs); Boundary-Integral Neural Networks(BINNs); Meshless Reservoir Simulation; Dimensionality Reduction

AESIG 2025, 1(1), 80-94;

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Views：144

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