1999
DOI: 10.1023/a:1006690700000
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Cited by 34 publications
(6 citation statements)
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“…8,9 These particles are exogenous particles generated by the fluid in the injection circuit and endogenous or in situ particles which coat the rock matrix like clays and other minerals. 10 These particles can be deposited in the reservoir and may consequently lead to a decrease of the reservoir permeability around the injection wells, and affect the injectivity of these wells. 11,12 During the injection at an imposed flow rate, this may lead to an increase of the injection pressure beyond the capacity of the pumps.…”
Section: Introductionmentioning
confidence: 99%
“…8,9 These particles are exogenous particles generated by the fluid in the injection circuit and endogenous or in situ particles which coat the rock matrix like clays and other minerals. 10 These particles can be deposited in the reservoir and may consequently lead to a decrease of the reservoir permeability around the injection wells, and affect the injectivity of these wells. 11,12 During the injection at an imposed flow rate, this may lead to an increase of the injection pressure beyond the capacity of the pumps.…”
Section: Introductionmentioning
confidence: 99%
“…Such a model, originally developed by Fatt [26] to predict multiphase flow properties in porous media, describes the porosity as a network of pores connected by channels. During the last decades, it has been extensively used and extended by petrophysicists in various situations: capillarity and multiphase flow through porous media [27][28][29][30][31], pore evolution and changes in petrophysical properties due to particle capture [32], filtration combustion [33], mineral dissolution and precipitation caused by CO 2 sequestration [34] and adsorption/reaction processes [35]. Recently, Varloteaux et al [36] studied the reactive transport in porous media using a PNM.…”
Section: Introductionmentioning
confidence: 99%
“…Ref. [17][18][19][20][21][22][23]). In this study we characterize the statistical properties of burst sizes by experimentally generating long time series.…”
mentioning
confidence: 99%