The precise evaluation of subsurface geological conditions is essential for sustainable utilization and management of underground energy resources. Due to exhausted reserves in shallow depths, future energy resources exploration has prompted to greater depths, which increases the occurrence of complicated geological deformations. A variety of geophysical, geotechnical, and geological investigations and workflows have been coupled with analytical and numerical modeling schemes to address subsurface geological conditions for assessing geological disasters. However, understanding deformation mechanisms becomes more challenging, resulting from enormous heterogeneities in the subsurface, rapid changes in rheological properties, and complex stress-states. These methods have yielded the range and size of stress concentration zones in rock mass and destressed zones.
With decades of development in measurement technologies and advanced modeling workflows, great efforts have been devoted to enhancing the accuracy of evaluating and predicting these complex geological deformations, with a strong focus on bridging the knowledge gap between available data and precise geological models. Improving the accuracy of extant measurement and modeling methods facilitates better quantification of geological deformations associated with subsurface excavation and safe-yield of deeply buried energy resources. Therefore, it entails an adequate integrated approach to characterize and quantify uncertain geological conditions that would lead to substantial societal risks.
Geophysical methods have been widely employed in practice for understanding subsurface geological conditions in sedimentary basins, petroleum systems, and underground exploration. Particularly, seismological and seismo-acoustic, electromagnetic, electrical resistivity observations and seismic measurements in the form of profiling play a pivotal role in assessing subsurface geological conditions. Despite the applications of these aforementioned high-end technologies in monitoring and early-warning of dynamic geological disasters (DGDs), it is still difficult to realize precise identification and classification of disaster risks due to the technology backwardness in information identification, data mining, and data processing. Rapid dynamic monitoring, multi-dimensional intelligent analysis, and comprehensive early-warning of DGDs is thus the key prerequisite for effective disaster prevention and control. In this regard, this Research Topic aims to present and disseminate latest advances in the evaluation, projection, and prevention of DGDs through novel geophysical workflows, intelligent schemes, and numerical modeling approaches. Topics of interest for publication include, but are not limited to:
• Induced seismicity
• Risk assessment and quantification
• Analytical schemes and numerical modeling
• Processing and interpretation workflows of geophysical data
• Fractures/faults/lineaments mapping associated with underground excavation
The precise evaluation of subsurface geological conditions is essential for sustainable utilization and management of underground energy resources. Due to exhausted reserves in shallow depths, future energy resources exploration has prompted to greater depths, which increases the occurrence of complicated geological deformations. A variety of geophysical, geotechnical, and geological investigations and workflows have been coupled with analytical and numerical modeling schemes to address subsurface geological conditions for assessing geological disasters. However, understanding deformation mechanisms becomes more challenging, resulting from enormous heterogeneities in the subsurface, rapid changes in rheological properties, and complex stress-states. These methods have yielded the range and size of stress concentration zones in rock mass and destressed zones.
With decades of development in measurement technologies and advanced modeling workflows, great efforts have been devoted to enhancing the accuracy of evaluating and predicting these complex geological deformations, with a strong focus on bridging the knowledge gap between available data and precise geological models. Improving the accuracy of extant measurement and modeling methods facilitates better quantification of geological deformations associated with subsurface excavation and safe-yield of deeply buried energy resources. Therefore, it entails an adequate integrated approach to characterize and quantify uncertain geological conditions that would lead to substantial societal risks.
Geophysical methods have been widely employed in practice for understanding subsurface geological conditions in sedimentary basins, petroleum systems, and underground exploration. Particularly, seismological and seismo-acoustic, electromagnetic, electrical resistivity observations and seismic measurements in the form of profiling play a pivotal role in assessing subsurface geological conditions. Despite the applications of these aforementioned high-end technologies in monitoring and early-warning of dynamic geological disasters (DGDs), it is still difficult to realize precise identification and classification of disaster risks due to the technology backwardness in information identification, data mining, and data processing. Rapid dynamic monitoring, multi-dimensional intelligent analysis, and comprehensive early-warning of DGDs is thus the key prerequisite for effective disaster prevention and control. In this regard, this Research Topic aims to present and disseminate latest advances in the evaluation, projection, and prevention of DGDs through novel geophysical workflows, intelligent schemes, and numerical modeling approaches. Topics of interest for publication include, but are not limited to:
• Induced seismicity
• Risk assessment and quantification
• Analytical schemes and numerical modeling
• Processing and interpretation workflows of geophysical data
• Fractures/faults/lineaments mapping associated with underground excavation
