Literature DB >> 28294224

Creation of a dual-porosity and dual-depth micromodel for the study of multiphase flow in complex porous media.

Wonjin Yun1, Cynthia M Ross, Sophie Roman, Anthony R Kovscek.   

Abstract

Silicon-based microfluidic devices, so-called micromodels in this application, are particularly useful laboratory tools for the direct visualization of fluid flow revealing pore-scale mechanisms controlling flow and transport phenomena in natural porous media. Current microfluidic devices with uniform etched depths, however, are limited when representing complex geometries such as the multiple-scale pore sizes common in carbonate rocks. In this study, we successfully developed optimized sequential photolithography to etch micropores (1.5 to 21 μm width) less deeply than the depth of wider macropores (>21 μm width) to improve the structural realism of an existing single-depth micromodel with a carbonate-derived pore structure. Surface profilimetry illustrates the configuration of the dual-depth dual-porosity micromodel and is used to estimate the corresponding pore volume change for the dual-depth micromodel compared to the equivalent uniform- or single-depth model. The flow characteristics of the dual-depth dual-porosity micromodel were characterized using micro-particle image velocimetry (μ-PIV), relative permeability measurements, and pore-scale observations during imbibition and drainage processes. The μ-PIV technique provides insights into the fluid dynamics within microfluidic channels and relevant fluid velocities controlled predominantly by changes in etching depth. In addition, the reduction of end-point relative permeability for both oil and water in the new dual-depth dual-porosity micromodel compared to the equivalent single-depth micromodel implies more realistic capillary forces occurring in the new dual-depth micromodel. Throughout the imbibition and drainage experiments, the flow behaviors of single- and dual-depth micromodels are further differentiated using direct visualization of the trapped non-wetting phase and the preferential mobilization of the wetting phase in the dual-depth micromodel. The visual observations agree with the relative permeability results. These findings indicate that dual-porosity and dual-depth micromodels have enhanced physical realism that is pertinent to oil recovery processes in complex porous media.

Entities:  

Year:  2017        PMID: 28294224     DOI: 10.1039/c6lc01343k

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  5 in total

1.  Characterization of wax valving and μPIV analysis of microscale flow in paper-fluidic devices for improved modeling and design.

Authors:  Emilie I Newsham; Elizabeth A Phillips; Hui Ma; Megan M Chang; Steven T Wereley; Jacqueline C Linnes
Journal:  Lab Chip       Date:  2022-07-12       Impact factor: 7.517

2.  Investigating low salinity waterflooding via glass micromodels with triangular pore-throat architectures.

Authors:  Yafei Liu; Erica Block; Jeff Squier; John Oakey
Journal:  Fuel (Lond)       Date:  2020-09-30       Impact factor: 6.609

3.  Fabrication of a 3D Multi-Depth Reservoir Micromodel in Borosilicate Glass Using Femtosecond Laser Material Processing.

Authors:  Ebenezer Owusu-Ansah; Colin Dalton
Journal:  Micromachines (Basel)       Date:  2020-12-06       Impact factor: 2.891

4.  Oil Displacement in Calcite-Coated Microfluidic Chips via Waterflooding at Elevated Temperatures and Long Times.

Authors:  Duy Le-Anh; Ashit Rao; Amy Z Stetten; Subhash C Ayirala; Mohammed B Alotaibi; Michel H G Duits; Han Gardeniers; Ali A AlYousef; Frieder Mugele
Journal:  Micromachines (Basel)       Date:  2022-08-14       Impact factor: 3.523

5.  Toward Reservoir-on-a-Chip: Rapid Performance Evaluation of Enhanced Oil Recovery Surfactants for Carbonate Reservoirs Using a Calcite-Coated Micromodel.

Authors:  Wonjin Yun; Sehoon Chang; Daniel A Cogswell; Shannon L Eichmann; Ayrat Gizzatov; Gawain Thomas; Naimah Al-Hazza; Amr Abdel-Fattah; Wei Wang
Journal:  Sci Rep       Date:  2020-01-21       Impact factor: 4.379

  5 in total

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