With the rapid consumption of fossil fuels, unconventional resources including shale gas, tight sand, and gas hydrate are becoming increasingly important. Governments, industries, and scholars have been trying their best to exploit unconventional resources. However, mineralogy, pore space, fluid storage and migration are far more complicated than for conventional oil and gas reservoirs. In this regard, advanced laboratory and downhole measurements, as well as novel petrophysical and formation evaluation methods have been developed to characterize unconventional resources in recent years. Also, machine learning aided logging information processing and interpretation provides new solutions for better understanding unconventional resources.
Great efforts have been made for the evaluation and characterization of unconventional resources. This Research Topic aims to provide a platform for petrophysicists and geophysicists to convey their recent key findings related to petrophysical properties and evaluation methods of unconventional resources. We welcome contributions addressing (1) advanced petrophysical experiment methods; (2) novel applications of advanced downhole measurements; (3) new rock physical models; (4) pore structure characterization and description; (5) data integration methods; (6) reservoir parameter evaluation, including porosity, permeability, and saturation; and (7) machine learning and artificial intelligence in geophysical data and applications.
Specific themes include, but are not limited to:
• Petrophysical experiments and data processing methods
• Reservoir description and pore structure characterization
• Downhole geophysical measurements and formation evaluation
• Geomechanics, fluid flow and transport
• Shale oil and shale gas reservoir evaluation
• Applications of machine learning and artificial intelligence in unconventional resources
With the rapid consumption of fossil fuels, unconventional resources including shale gas, tight sand, and gas hydrate are becoming increasingly important. Governments, industries, and scholars have been trying their best to exploit unconventional resources. However, mineralogy, pore space, fluid storage and migration are far more complicated than for conventional oil and gas reservoirs. In this regard, advanced laboratory and downhole measurements, as well as novel petrophysical and formation evaluation methods have been developed to characterize unconventional resources in recent years. Also, machine learning aided logging information processing and interpretation provides new solutions for better understanding unconventional resources.
Great efforts have been made for the evaluation and characterization of unconventional resources. This Research Topic aims to provide a platform for petrophysicists and geophysicists to convey their recent key findings related to petrophysical properties and evaluation methods of unconventional resources. We welcome contributions addressing (1) advanced petrophysical experiment methods; (2) novel applications of advanced downhole measurements; (3) new rock physical models; (4) pore structure characterization and description; (5) data integration methods; (6) reservoir parameter evaluation, including porosity, permeability, and saturation; and (7) machine learning and artificial intelligence in geophysical data and applications.
Specific themes include, but are not limited to:
• Petrophysical experiments and data processing methods
• Reservoir description and pore structure characterization
• Downhole geophysical measurements and formation evaluation
• Geomechanics, fluid flow and transport
• Shale oil and shale gas reservoir evaluation
• Applications of machine learning and artificial intelligence in unconventional resources
