Open Access
Issue
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 76, 2021
Article Number 50
Number of page(s) 16
DOI https://doi.org/10.2516/ogst/2021029
Published online 29 June 2021
  • Blunt M.J. (2017) Multiphase flow in permeable media: A pore-scale perspective, Cambridge University Press, Cambridge, UK. [Google Scholar]
  • Rostami P., Sharifi M., Aminshahidy B., Fahimpour J. (2019) The effect of nanoparticles on wettability alteration for enhanced oil recovery: Micromodel experimental studies and CFD simulation, Petrol. Sci. 16, 4, 859–873. [Google Scholar]
  • Palizdan S., Doryani H., Riazi M., Malayeri M.R. (2020) Experimental study of in-situ W/O emulsification during the injection of MgSO4 and Na2CO3 solutions in a glass micromodel, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 75, 87. [Google Scholar]
  • Mahmoodi M., Mahdavi S., James L.A., Johansen T. (2018) A quick method to fabricate large glass micromodel networks, Microsyst. Technol. 24, 5, 2419–2427. [Google Scholar]
  • Chuoke R., Van Meurs P., van der Poel C. (1959) The instability of slow, immiscible, viscous liquid-liquid displacements in permeable media, Trans. AIME 216, 01, 188–194. [Google Scholar]
  • Yi S., Babadagli T., Li H. (2020) Stabilization of nickel nanoparticle suspensions with the aid of polymer and surfactant: Static bottle tests and dynamic micromodel flow tests, Petrol. Sci. 17, 1–11. [Google Scholar]
  • Muraoka M., Yamamoto Y., Tenma N. (2020) Simultaneous measurement of water permeability and methane hydrate pore habit using a two-dimensional glass micromodel, J. Nat. Gas Sci. Eng. 77, 103279. [Google Scholar]
  • Abolhasanzadeh A., Khaz’ali A.R., Hashemi R., Jazini M. (2020) Experimental study of microbial enhanced oil recovery in oil-wet fractured porous media, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 75, 73. [Google Scholar]
  • Meisenheimer D.E., McClure J.E., Rivers M.L., Wildenschild D. (2020) Exploring the effect of flow condition on the constitutive relationships for two-phase flow, Adv. Water Res. 137, 103506. [Google Scholar]
  • Cao S.C., Jung J., Radonjic M. (2019) Application of microfluidic pore models for flow, transport, and reaction in geological porous media: From a single test bed to multifunction real-time analysis tool, Microsyst. Technol. 25, 1–18. [Google Scholar]
  • Lin M., Wang Y., Cao Y., Wang Y., Wang X., Xi K. (2020) Experimental study of the influence of oil-wet calcite cements on oil migration and implications for clastic reservoirs, Mar. Pet. Geol. 118, 104427. [Google Scholar]
  • Song Y., Zhao C., Chen M., Chi Y., Zhang Y., Zhao J. (2020) Pore-scale visualization study on CO2 displacement of brine in micromodels with circular and square cross sections, Int. J. Greenhouse Gas Cont. 95, 102958. [Google Scholar]
  • Sharifipour M., Nakhaee A., Pourafshary P. (2019) Model development of permeability impairment due to clay swelling in porous media using micromodels, J. Pet. Sci. Eng. 175, 728–742. [Google Scholar]
  • Porter M.L., Jiménez-Martínez J., Martinez R., McCulloch Q., Carey J.W., Viswanathan H.S. (2015) Geo-material microfluidics at reservoir conditions for subsurface energy resource applications, Lab. Chip 15, 20, 4044–4053. [Google Scholar]
  • Martel R., Portois C., Robert T., Uyeda M. (2019) Etched glass micromodel for laboratory simulation of NAPL recovery mechanisms by surfactant solutions in fractured rock, J. Contam. Hydrol. 227, 103550. [Google Scholar]
  • Watson F., Maes J., Geiger S., Mackay E., Singleton M., McGravie T., Anouilh T., Jobe T.D., Zhang S., Agar S., Ishutov S. (2019) Comparison of flow and transport experiments on 3D printed micromodels with direct numerical simulations, Transp. Porous Media 129, 2, 449–466. [Google Scholar]
  • Aziz R., Niasar V., Erfani H., Martínez-Ferrer P.J. (2020) Impact of pore morphology on two-phase flow dynamics under wettability alteration, Fuel 268, 117315. [Google Scholar]
  • Song W., de Haas T.W., Fadaei H., Sinton D. (2014) Chip-off-the-old-rock: The study of reservoir-relevant geological processes with real-rock micromodels, Lab. Chip 14, 22, 4382–4390. [Google Scholar]
  • Tanino Y., Zacarias-Hernandez X., Christensen M. (2018) Oil/water displacement in microfluidic packed beds under weakly water-wetting conditions: Competition between precursor film flow and piston-like displacement, Exp. Fluids 59, 2, 35. [Google Scholar]
  • Zhang Y., Sanati-Nezhad A., Hejazi S. (2018) Geo-material surface modification of microchips using Layer-By-Layer (LbL) assembly for subsurface energy and environmental applications, Lab. Chip 18, 2, 285–295. [Google Scholar]
  • Singh R., Sivaguru M., Fried G.A., Fouke B.W., Sanford R.A., Carrera M., Werth C.J. (2017) Real rock-microfluidic flow cell: A test bed for real-time in situ analysis of flow, transport, and reaction in a subsurface reactive transport environment, J. Contam. Hydrol. 204, 28–39. [Google Scholar]
  • Teimouri A., Sadeghnejad S., Dehaghani A.H.S. (2020) Investigation of acid pre-flushing and pH-sensitive microgel injection in fractured carbonate rocks for conformance control purposes, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 75, 52. [Google Scholar]
  • Pratama R.A., Babadagli T. (2020) Wettability state and phase distributions during steam injection with and without chemical additives: An experimental analysis using visual micromodels, SPE Reserv. Eval. Eng. 23, 1133–1149. [Google Scholar]
  • Tahir M., Hincapie R.E., Gaol C.L., Säfken S., Ganzer L. (2020) Flow dynamics of sulfate-modified water/polymer flooding in micromodels with modified wettability, Appl. Sci. 10, 9, 3239. [Google Scholar]
  • Song W., Kovscek A.R. (2016) Direct visualization of pore-scale fines migration and formation damage during low-salinity waterflooding, J. Nat. Gas Sci. Eng. 34, 1276–1283. [Google Scholar]
  • Zhang Y., Yesiloz G., Sharahi H.J., Khorshidian H., Kim S., Sanati-Nezhad A., Hejazi S.H. (2019) Geomaterial-functionalized microfluidic devices using a universal surface modification approach, Adv. Mater. Interf. 6, 23, 1900995. [Google Scholar]
  • Hull C.W. (1984) Apparatus for production of three-dimensional objects by stereolithography. United States Patent, Appl., No. 638905, Filed. [Google Scholar]
  • Sing S.L., Tey C.F., Tan J.H.K., Huang S., Yeong W.Y. (2020) 3D printing of metals in rapid prototyping of biomaterials: Techniques in additive manufacturing, in: Rapid prototyping of biomaterials, Elsevier, Amsterdam, pp. 17–40. [Google Scholar]
  • Yadav D.K., Srivastava R., Dev S. (2020) Design & fabrication of ABS part by FDM for automobile application, Mater. Today Proc. 26, 2089–2093. [Google Scholar]
  • Shahrubudin N., Lee T., Ramlan R. (2019) An overview on 3D printing technology: Technological, materials, and applications, Procedia Manuf. 35, 1286–1296. [Google Scholar]
  • Craveiro F., Nazarian S., Bartolo H., Bartolo P.J., Duarte J.P. (2020) An automated system for 3D printing functionally graded concrete-based materials, Addit. Manuf. 33, 101146. [Google Scholar]
  • Dmitriev A.Y., Zagidulin R., Mitroshkina T. (2020) Special aspects of quality assurance in the design, manufacture, testing of aerospace engineering products, in: IOP Conference Series: Materials Science and Engineering, IOP Publishing, Bristol, UK. [Google Scholar]
  • Dang W., Ma B., Li B., Huan Z., Ma N., Zhu H., Chang J., Xiao Y., Wu C. (2020) 3D printing of metal-organic framework nanosheets-structured scaffolds with tumor therapy and bone construction, Biofabrication 12, 2, 025005. [Google Scholar]
  • Ishutov S., Jobe T.D., Zhang S., Gonzalez M., Agar S.M., Hasiuk F.J., Watson F., Geiger S., Mackay E., Chalaturnyk R. (2018) Three-dimensional printing for geoscience: Fundamental research, education, and applications for the petroleum industry, AAPG Bull. 102, 1, 1–26. [Google Scholar]
  • Wu T., Zhao H., Xu Q., Zhao Y. (2020) Optimal analysis of material ratio for artificial rock by 3D printing technique, Geomech. Geoeng. 15, 1–9. [Google Scholar]
  • Li H., Zhang T. (2019) Imaging and characterizing fluid invasion in micro-3D printed porous devices with variable surface wettability, Soft Matter 15, 35, 6978–6987. [Google Scholar]
  • Shallan A.I., Smejkal P., Corban M., Guijt R.M., Breadmore M.C. (2014) Cost-effective three-dimensional printing of visibly transparent microchips within minutes, Anal. Chem. 86, 6, 3124–3130. [Google Scholar]
  • Ishutov S. (2017) 3D printing porous proxies as a new tool for laboratory and numerical analyses of sedimentary rocks, PhD Dissertation, Iowa State University, Geological and Atmospheric Sciences Department. [Google Scholar]
  • Perras M.A., Vogler D. (2019) Compressive and tensile behavior of 3D-Printed and natural sandstones, Trans. Porous Media 129, 2, 559–581. [Google Scholar]
  • Hodder K.J., Nychka J.A. (2019) Silane treatment of 3D-printed sandstone models for improved spontaneous imbibition of water, Trans. Porous Media 129, 2, 583–598. [Google Scholar]
  • Kong L., Ostadhassan M., Li C., Tamimi N. (2018) Pore characterization of 3D-printed gypsum rocks: a comprehensive approach, J. Mater. Sci. 53, 7, 5063–5078. [Google Scholar]
  • Kong L., Ostadhassan M., Li C., Tamimi N. (2017) Rock physics and geomechanics of 3-D printed rocks, in: 51st US Rock Mechanics/Geomechanics Symposium, American Rock Mechanics Association. [Google Scholar]
  • Kong L., Ostadhassan M., Li C., Tamimi N. (2018) Can 3-D printed gypsum samples replicate natural rocks? An experimental study, Rock Mech. Rock Eng. 51, 10, 3061–3074. [Google Scholar]
  • Kong L., Ostadhassan M., Hou X., Mann M., Li C. (2019) Microstructure characteristics and fractal analysis of 3D-printed sandstone using micro-CT and SEM-EDS, J. Pet. Sci. Eng. 175, 1039–1048. [Google Scholar]
  • Almetwally A., Jabbari H. (2019) Development of novel workflow to replicate pore network of porous core samples through 3D printing technology, in: 53rd US Rock Mechanics/Geomechanics Symposium, American Rock Mechanics Association. [Google Scholar]
  • Almetwally A., Jabbari H. (2020) Experimental investigation of 3D printed rock samples replicas, J. Nat. Gas Sci. Eng. 76, 103192. [Google Scholar]
  • Song R., Peng J., Sun S., Wang Y., Cui M., Liu J. (2020) Visualized experiments on residual oil classification and its influencing factors in waterflooding using micro-computed tomography, J. Energy Resour. Technol. 142, 8, 083003. [Google Scholar]
  • Hasiuk F.J. (2019) Testing bulk properties of powder-based 3D-printed reservoir rock proxies, Trans. Porous Media 129, 2, 501–520. [Google Scholar]
  • Yang W., Zhang D., Lei G. (2020) Experimental study on multiphase flow in fracture-vug medium using 3D printing technology and visualization techniques, J. Pet. Sci. Eng. 193, 107394. [Google Scholar]
  • Donovan K.J. (2019) Microfluidic investigations of capillary flow and surface phenomena in porous polymeric media for 3D printing, PhD Dissertation, Oregon State University, Materials Science Department. [Google Scholar]
  • Ahkami M., Roesgen T., Saar M.O., Kong X.Z. (2019) High-resolution temporo-ensemble PIV to resolve pore-scale flow in 3D-printed fractured porous media, Trans. Porous Media 129, 2, 467–483. [Google Scholar]
  • Moslemipoor A. (2019) Pore Network Modeling (PNM) of vuggy carbonate reservoirs and its validation by experimental data, in: Department of Chemical Engineering, Tarbiat Modares University. [Google Scholar]
  • Moslemipour A., Sadeghnejad S. (2020) Dual-scale pore network reconstruction of vugular carbonates using multi-scale imaging techniques, Adv. Water Resour. 147, 103795. [Google Scholar]
  • Schindelin J., Arganda-Carreras I., Frise E., Kaynig V., Longair M., Pietzsch T., Preibisch S., Rueden C., Saalfeld S., Schmid B., Tinevez J.Y. (2012) Fiji: An open-source platform for biological-image analysis, Nat. Meth. 9, 7, 676–682. [Google Scholar]
  • Esmaeilzadeh S., Salehi A., Hetz G., Olalotiti-lawal F., Darabi H., Castineira D. (2020) Multiscale modeling of compartmentalized reservoirs using a hybrid clustering-based non-local approach, J. Pet. Sci. Eng. 184, 106485. [Google Scholar]
  • Liew A.W.L. (2020) Laser-based 3D printing using bessel beams for tissue engineering applications, PhD Dissertation, Nanyang Technological University, School of Mechanical and Aerospace Engineering. [Google Scholar]
  • Kim B., Kim H., Kim J., Cho C.S., Lee J. (2013) Superhydrophobic polytetrafluoroethylene surface obtained using reactive ion etching and duplication with polydimethylsiloxane mould, Micro Nano Lett. 8, 10, 691–695. [Google Scholar]
  • Steingruber E. (2000) Indigo and indigo colorants, in: Ullmann’s Encyclopedia of Industrial Chemistry, Wiley-VCH, Weinheim, Germany. [Google Scholar]
  • Eghbalzadeh A., Javan M. (2012) Comparison of mixture and VOF models for numerical simulation of air–entrainment in skimming flow over stepped spillways, Procedia Eng. 28, 657–660. [Google Scholar]
  • Hirt C.W., Nichols B.D. (1981) Volume Of Fluid (VOF) method for the dynamics of free boundaries, J. Comput. Phys. 39, 1, 201–225. [Google Scholar]
  • Manninen M., Taivassalo V. (1996) On the mixture model for multiphase flow, VTT Publications 288, Technical Research Center of Finland, Finland. [Google Scholar]
  • Fluent A. (2009) 12.0 Theory guide, Ansys Inc. 5, 5, 15. [Google Scholar]
  • Wang Z., Bovik A.C. (2002) A universal image quality index, IEEE Sig. Proc. Lett. 9, 3, 81–84. [Google Scholar]
  • Okarma K., Fastowicz J., Tecław M. (2016) Application of structural similarity based metrics for quality assessment of 3D prints, in: International Conference on Computer Vision and Graphics, Springer. [Google Scholar]
  • Yuan J., Tian J., Chen C., Chen G. (2020) Experimental investigation of color reproduction quality of color 3D printing based on colored layer features, Molecules 25, 12, 2909. [Google Scholar]
  • Wang Z., Bovik A.C., Sheikh H.R., Simoncelli E.P. (2004) Image quality assessment: From error visibility to structural similarity, IEEE Trans. Image Proc. 13, 4, 600–612. [Google Scholar]

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