深度学习方法在数字岩石技术中的应用进展

IF 9 1区地球科学 Q1 ENERGY & FUELS

Advances in Geo-Energy Research Pub Date : 2023-02-02 DOI:10.46690/ager.2023.04.02

Xiaobin Li, Bing Li, Fangzhou Liu, Tingting Li, Xin Nie

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引用次数: 4

摘要

：数字岩石技术在储层工程和岩石物理学中变得至关重要。三维数字岩石重建、图像分辨率增强、图像分割和岩石参数预测都是使数字岩石的整体分析能够克服传统方法的缺点和局限性的关键步骤。人工智能技术已经开始在许多不同的领域发挥重要作用，可能会为数字岩石技术的发展提供一个新的方向。这项工作系统地回顾了应用于数字岩石分析任务的深度学习方法，包括数字岩石的重建、高分辨率图像采集、灰度图像分割

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Advances in the application of deep learning methods to digital rock technology

: Digital rock technology is becoming essential in reservoir engineering and petrophysics. Three-dimensional digital rock reconstruction, image resolution enhancement, image segmentation, and rock parameters prediction are all crucial steps in enabling the overall analysis of digital rocks to overcome the shortcomings and limitations of traditional methods. Artificial intelligence technology, which has started to play a significant role in many different fields, may provide a new direction for the development of digital rock technology. This work presents a systematic review of the deep learning methods that are being applied to tasks within digital rock analysis, including the reconstruction of digital rocks, high-resolution image acquisition, grayscale image segmentation

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来源期刊

Advances in Geo-Energy Research natural geo-energy (oil, gas, coal geothermal, and gas hydrate)-Geotechnical Engineering and Engineering Geology

CiteScore

12.30

自引率

8.50%

发文量

审稿时长

2~3 weeks

期刊介绍： Advances in Geo-Energy Research is an interdisciplinary and international periodical committed to fostering interaction and multidisciplinary collaboration among scientific communities worldwide, spanning both industry and academia. Our journal serves as a platform for researchers actively engaged in the diverse fields of geo-energy systems, providing an academic medium for the exchange of knowledge and ideas. Join us in advancing the frontiers of geo-energy research through collaboration and shared expertise.