About this Research Topic
The development in unconventional oil and gas reservoir has been greatly improved over the past decade worldwide. However, there are still challenges to understand the dynamic multi-scale rock property change and multi-physics (thermal-hydrological-mechanical coupling) fluid flow behavior. Given the inherent multi-scale nature of the unconventional rock structure, strong heterogeneity, and complex rock-fluid interaction in confined space, advances in multi-scale characterization and modeling techniques are needed. The last 10 years have seen significant advances in experimental measurement and theoretical approaches of reservoir characterization and flow transport at the pore, Darcy, and field scales during the development in unconventional oil and gas reservoir.
The emerging new theoretical approaches mainly include digital rock at the pore scale, deep learning-driven geophysical modeling, upscaling technique, and multi-scale computation technique while experimental measurements mainly include nano-scale 3D imaging, microscale 4D in situ synchrotron X-ray tomographic microscopy, and centimeter-scale core scale measurement method at high temperature, high-pressure condition. These advancements have allowed the geoscience community to gain unprecedented insights into the geochemical, geomechanical, and geostatistical property of unconventional oil and gas reservoir. The purpose of this research topic is to explore the advances in multi-scale multi-physics geophysical modeling and fluid transport in unconventional oil and gas reservoir based on the above-mentioned advancements as well as to pinpoint the characteristics and variables that influence and control unconventional rock property.
This research topic will collect comprehensive review papers and research articles of any scientific work and fundamental study for “Advances in multi-scale multi-physics geophysical modeling and fluid transport in unconventional oil and gas reservoir”. It will cover topics of interest that include, but are not limited to, the following:
· Digital rock physics application in unconventional oil and gas reservoir
· Pore structure characterization
· Multi-scale geophysical modeling
· Fluid transport mechanism in unconventional oil and gas reservoir
· CO2 storage and CO2 enhanced recovery mechanism
· Deep learning driven modeling in unconventional oil and gas reservoir
The emerging new theoretical approaches mainly include digital rock at the pore scale, deep learning-driven geophysical modeling, upscaling technique, and multi-scale computation technique while experimental measurements mainly include nano-scale 3D imaging, microscale 4D in situ synchrotron X-ray tomographic microscopy, and centimeter-scale core scale measurement method at high temperature, high-pressure condition. These advancements have allowed the geoscience community to gain unprecedented insights into the geochemical, geomechanical, and geostatistical property of unconventional oil and gas reservoir. The purpose of this research topic is to explore the advances in multi-scale multi-physics geophysical modeling and fluid transport in unconventional oil and gas reservoir based on the above-mentioned advancements as well as to pinpoint the characteristics and variables that influence and control unconventional rock property.
This research topic will collect comprehensive review papers and research articles of any scientific work and fundamental study for “Advances in multi-scale multi-physics geophysical modeling and fluid transport in unconventional oil and gas reservoir”. It will cover topics of interest that include, but are not limited to, the following:
· Digital rock physics application in unconventional oil and gas reservoir
· Pore structure characterization
· Multi-scale geophysical modeling
· Fluid transport mechanism in unconventional oil and gas reservoir
· CO2 storage and CO2 enhanced recovery mechanism
· Deep learning driven modeling in unconventional oil and gas reservoir
Keywords: unconventional rock property, reservoir characterization, fluid flow, multi-physics transport, unconventional reservoir, multi scale geologic modeling, deep learning
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