Latest advancements in machine learning for geophysics — Introduction

IF 3 2区地球科学 Q1 GEOCHEMISTRY & GEOPHYSICS

Geophysics Pub Date : 2023-11-20 DOI:10.1190/geo2023-1116-spseintro.1

Haibin Di, Wenyi Hu, Aria Abubakar, Pandu Devarakota, Weichang Li, Yaoguo Li

引用次数: 0

Abstract

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地球物理学机器学习的最新进展 - 简介

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Geophysics 地学-地球化学与地球物理

CiteScore

6.90

自引率

18.20%

发文量

354

审稿时长

3 months

期刊介绍： Geophysics, published by the Society of Exploration Geophysicists since 1936, is an archival journal encompassing all aspects of research, exploration, and education in applied geophysics. Geophysics articles, generally more than 275 per year in six issues, cover the entire spectrum of geophysical methods, including seismology, potential fields, electromagnetics, and borehole measurements. Geophysics, a bimonthly, provides theoretical and mathematical tools needed to reproduce depicted work, encouraging further development and research. Geophysics papers, drawn from industry and academia, undergo a rigorous peer-review process to validate the described methods and conclusions and ensure the highest editorial and production quality. Geophysics editors strongly encourage the use of real data, including actual case histories, to highlight current technology and tutorials to stimulate ideas. Some issues feature a section of solicited papers on a particular subject of current interest. Recent special sections focused on seismic anisotropy, subsalt exploration and development, and microseismic monitoring. The PDF format of each Geophysics paper is the official version of record.