Geophysics and Geophysical Exploration
Scope & Guideline
Connecting Researchers to Shape the Future of Geophysics
Introduction
Aims and Scopes
- Geophysical Survey Techniques:
The journal emphasizes the development and application of various geophysical survey techniques, including seismic, electromagnetic, and gravity methods, to investigate subsurface features and dynamics. - Machine Learning and Data Analysis:
A significant focus is placed on the integration of machine learning and advanced data analysis techniques to enhance the interpretation of geophysical data, improve inversion algorithms, and facilitate real-time data processing. - Environmental and Resource Management:
Research addressing the exploration and management of natural resources, including carbon capture and storage (CCS) and the detection of subsurface contaminants, is a core area of interest. - Theoretical and Computational Geophysics:
The journal publishes studies that develop theoretical frameworks and computational models for geophysical phenomena, contributing to the foundational understanding of geophysical processes. - Interdisciplinary Approaches:
There is a strong emphasis on interdisciplinary research that connects geophysics with other fields such as geology, environmental science, and engineering, aiming for comprehensive solutions to complex geophysical challenges.
Trending and Emerging
- Deep Learning Applications:
There is a notable increase in research utilizing deep learning techniques for seismic data interpretation, noise suppression, and inversion processes, showcasing the potential of artificial intelligence in enhancing geophysical methodologies. - Environmental Monitoring and Sustainability:
Emerging themes related to environmental monitoring, particularly in the context of carbon capture and storage, reflect a heightened awareness of sustainability challenges and the role of geophysics in addressing them. - Integration of Sensor Technologies:
The introduction of novel sensor technologies, such as cableless seismic data acquisition and unmanned aircraft systems for electromagnetic surveys, indicates a trend towards innovative data collection methods that enhance geophysical exploration. - Physics-informed Machine Learning:
Research focusing on integrating physics-based models with machine learning approaches for geophysical data analysis is gaining traction, suggesting a convergence of traditional geophysical principles with modern computational techniques.
Declining or Waning
- Traditional Induced Polarization Techniques:
Research on conventional methods of induced polarization, including the time-domain approaches, appears to be declining as newer techniques and computational methods gain prominence. - Basic Gravity and Magnetic Studies:
The frequency of publications focused solely on basic gravity and magnetic studies has decreased, suggesting a shift toward more complex and integrated geophysical analysis. - Non-advanced Geophysical Equipment:
There seems to be a waning interest in studies that involve traditional geophysical equipment without advanced technological integration, as the field moves towards more innovative and efficient tools.
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