Artificial Intelligence in Geosciences focuses on the application of machine learning and deep learning techniques to analyze and interpret diverse geoscience data. This includes tasks such as mapping groundwater potential, downscaling temperature data, segmenting land cover, predicting geotechnical parameters, interpolating ore grades, and reconstructing seismic data. The journal also covers the use of AI for predicting rainfall, analyzing land surface temperature, and identifying cracks in rock surfaces. Furthermore, it explores AI applications in reservoir characterization, seismic impedance inversion, and earthquake early warning systems.
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Publication & Citation Trend
Articles published
Times cited
2020
2021
2022
2023
2024
2025
2026
Source: OpenAlex · Note: citations accumulate over time so older years appear higher
SJR Quartile by Discipline
Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.
Earth and Planetary Sciences (miscellaneous)Q1
Artificial IntelligenceQ2
Computers in Earth SciencesQ2
Control and Systems EngineeringQ2
Subject Classification
Web of Science Categories
Geosciences, Multidisciplinary
Scopus Categories
Earth and Planetary Sciences (miscellaneous)Control and Systems EngineeringArtificial IntelligenceComputers in Earth Sciences
Research Topics (OpenAlex)
Seismic Imaging and Inversion TechniquesHydrocarbon exploration and reservoir analysisHydraulic Fracturing and Reservoir AnalysisGeochemistry and Geologic MappingSeismic Waves and AnalysisReservoir Engineering and Simulation MethodsSeismology and Earthquake StudiesDrilling and Well EngineeringMineral Processing and Grindingearthquake and tectonic studies