Effects of mudcake on the measurement of fluid flow properties using borehole acoustic waves

1994 ◽  
Author(s):  
Xiao Ming Tang
Keyword(s):  
Fluid Flow ◽  
Acoustic Waves ◽  
Flow Properties

Two-phase fluid flow properties of cataclastic fault rocks: Implications for CO2 storage in saline aquifers

Geology ◽  
2012 ◽  
Vol 40 (1) ◽  
pp. 39-42 ◽  
Author(s):  
Christian Tueckmantel ◽  
Quentin J. Fisher ◽  
Tom Manzocchi ◽  
Sergey Skachkov ◽  
Carlos A. Grattoni
Keyword(s):  
Fluid Flow ◽  
Co2 Storage ◽  
Saline Aquifers ◽  
Flow Properties ◽  
Two Phase ◽  
Fault Rocks ◽  
Phase Fluid

scholarly journals Pore-network modeling and determination of rock and two-phase fluid flow properties

2021 ◽  
Vol 143 (3) ◽  
pp. 106-114
Author(s):  
Zh.K. Akasheva ◽  
◽  
D.A. Bolysbek ◽  
B.K. Assilbekov ◽  
A.K. Yergesh ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Network Modeling ◽  
Pore Network ◽  
Flow Properties ◽  
Two Phase ◽  
Pore Network Modeling ◽  
Phase Fluid

scholarly journals Combined numerical and experimental study of microstructure and permeability in porous granular media

2020 ◽  
Author(s):  
Philipp Eichheimer ◽  
Marcel Thielmann ◽  
Wakana Fujita ◽  
Gregor J. Golabek ◽  
Michihiko Nakamura ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Numerical Simulations ◽  
Granular Media ◽  
Large Scale ◽  
Earth Science ◽  
Numerical Models ◽  
Effective Porosity ◽  
Flow Properties ◽  
Wide Range ◽  
Flow Through

Abstract. Fluid flow on different scales is of interest for several Earth science disciplines like petrophysics, hydrogeology and volcanology. To parameterize fluid flow in large-scale numerical simulations (e.g. groundwater and volcanic systems), flow properties on the microscale need to be considered. For this purpose experimental and numerical investigations of flow through porous media over a wide range of porosities are necessary. In the present study we sinter glass bead media with various porosities. The microstructure, namely effective porosity and effective specific surface, is investigated using image processing. We determine flow properties like hydraulic tortuosity and permeability using both experimental measurements and numerical simulations. By fitting microstructural and flow properties to porosity, we obtain a modified Kozeny-Carman equation for isotropic low-porosity media, that can be used to simulate permeability in large-scale numerical models. To verify the modified Kozeny-Carman equation we compare it to the computed and measured permeability values.

Tomographic Techniques for Measuring Fluid Flow Properties

2002 ◽  
Vol 67 (7) ◽  
pp. 2718-2724 ◽  
Author(s):  
Y.J. Choi ◽  
K.L. Mccarthy ◽  
M.J. Mccarthy
Keyword(s):  
Fluid Flow ◽  
Flow Properties

Heat Transfer and Fluid Flow in Sintered Metallic Fiber Structures

2010 ◽  
Vol 638-642 ◽  
pp. 1884-1889 ◽  
Author(s):  
Olaf Andersen ◽  
Jens Meinert
Keyword(s):  
Heat Transfer ◽  
Fluid Flow ◽  
Heat Storage ◽  
Short Fiber ◽  
Analytical Models ◽  
Flow Properties ◽  
Metal Fiber ◽  
Open Cell ◽  
Sintered Metal ◽  
Inner Surface

Sintered metal fiber structures show a favourable ratio between pressure drop and inner surface area. Their exclusively open-cell morphology makes them well suited for heat transfer or temporary heat storage applications. Recently, highly conductive sintered metal fiber structures were successfully prepared from melt extracted aluminum alloy fibers. The heat conduction and fluid flow properties of metallic sintered short fiber structures were determined experimentally and compared with simple analytical models. It was found that equations taken from the available literature yield good approximations to the experimental results.

scholarly journals Learning The Fluid/Flow Properties Using Microfluidics

2019 ◽  
Vol 215 ◽  
pp. 10002
Author(s):  
Pooria Hadikhani ◽  
Navid Borhani ◽  
S. Mohammad H. Hashemi ◽  
Demetri Psaltis
Keyword(s):  
Neural Networks ◽  
Fluid Flow ◽  
Microfluidic Device ◽  
Flow Rate ◽  
Deep Neural Networks ◽  
Good Accuracy ◽  
Flow Properties ◽  
Flow Rates

Deep neural networks (DNN) are employed to measure the flow rate and the concentration of the liquid using the images of the droplets in a microfluidic device. The trained networks are able to measure flow rates and concentrations with good accuracy.

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