<p>Low saline water flooding (LSWF) is a promising enhanced oil recovery (EOR) technique in petroleum engineering, offering a sustainable alternative to chemical EOR by targeting residual oil with minimal chemical use. However, the role of ion concentrations in influencing oil recovery remains insufficiently understood, creating a critical gap in LSWF optimization. This study addresses this gap by employing Sobol’ analysis, a global sensitivity analysis technique, to evaluate the impact of ion concentrations on oil recovery. Sobol’ analysis is applied over 81,920 samples for 2.3 pore volume injected (PVI) to assess the effects of multiphase fluid flow coupled with a reactive transport model. The results reveal that <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq1.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="40" /> </InlineMediaObject> <EquationSource Format="TEX">$[\text {Na}^+]$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">[</mo> <msup> <mtext>Na</mtext> <mo>+</mo> </msup> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq2.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="49" /> </InlineMediaObject> <EquationSource Format="TEX">$[\text {Mg}^{2+}]$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">[</mo> <msup> <mtext>Mg</mtext> <mrow> <mn>2</mn> <mo>+</mo> </mrow> </msup> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation>, and <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq3.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="46" /> </InlineMediaObject> <EquationSource Format="TEX">$[\text {Ca}^{2+}]$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">[</mo> <msup> <mtext>Ca</mtext> <mrow> <mn>2</mn> <mo>+</mo> </mrow> </msup> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation> significantly influence oil recovery, with strong interactions between <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq4.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="40" /> </InlineMediaObject> <EquationSource Format="TEX">$[\text {Na}^+]$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">[</mo> <msup> <mtext>Na</mtext> <mo>+</mo> </msup> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq5.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="46" /> </InlineMediaObject> <EquationSource Format="TEX">$[\text {Ca}^{2+}]$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">[</mo> <msup> <mtext>Ca</mtext> <mrow> <mn>2</mn> <mo>+</mo> </mrow> </msup> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation>, as well as <InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq6.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="46" /> </InlineMediaObject> <EquationSource Format="TEX">$[\text {Ca}^{2+}]$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">[</mo> <msup> <mtext>Ca</mtext> <mrow> <mn>2</mn> <mo>+</mo> </mrow> </msup> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq7.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="49" /> </InlineMediaObject> <EquationSource Format="TEX">$[\text {Mg}^{2+}]$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">[</mo> <msup> <mtext>Mg</mtext> <mrow> <mn>2</mn> <mo>+</mo> </mrow> </msup> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation>. Among all, <InlineEquation ID="IEq8"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq8.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="40" /> </InlineMediaObject> <EquationSource Format="TEX">$[\text {Na}^+]$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">[</mo> <msup> <mtext>Na</mtext> <mo>+</mo> </msup> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation> exhibits the highest Sobol’ first-order value, indicating its dominant role in recovery variation. Temporal analysis further suggests that interactive effects outweigh individual contributions. To manage uncertainties, cumulative probability values (<InlineEquation ID="IEq9"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq9.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="24" /> </InlineMediaObject> <EquationSource Format="TEX">$\hbox {P}_{{10}}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mtext>P</mtext> <mn>10</mn> </msub> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq10"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq10.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="24" /> </InlineMediaObject> <EquationSource Format="TEX">$\hbox {P}_{{50}}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mtext>P</mtext> <mn>50</mn> </msub> </math></EquationSource> </InlineEquation>, and <InlineEquation ID="IEq11"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12665_2025_12194_Article_IEq11.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="24" /> </InlineMediaObject> <EquationSource Format="TEX">$\hbox {P}_{{90}}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mtext>P</mtext> <mn>90</mn> </msub> </math></EquationSource> </InlineEquation>) are employed for optimization, minimizing variability in recovery predictions. Finally, this research provides a toolkit for evaluating ion interactions and optimizing LSWF, underscoring the role of ionic concentrations in sensitivity analysis, supporting decision making and risk assessment in upstream applications.</p>

Assessing ion interactions in low saline water flooding of sandstone reservoirs: numerical approach

期刊论文
发表日期：

2025年3月28日

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Viswakanth Kandala,
Suresh Kumar Govindarajan

摘要

Low saline water flooding (LSWF) is a promising enhanced oil recovery (EOR) technique in petroleum engineering, offering a sustainable alternative to chemical EOR by targeting residual oil with minimal chemical use. However, the role of ion concentrations in influencing oil recovery remains insufficiently understood, creating a critical gap in LSWF optimization. This study addresses this gap by employing Sobol’ analysis, a global sensitivity analysis technique, to evaluate the impact of ion concentrations on oil recovery. Sobol’ analysis is applied over 81,920 samples for 2.3 pore volume injected (PVI) to assess the effects of multiphase fluid flow coupled with a reactive transport model. The results reveal that $[\text {Na}^+]$ $[{Na}^{+}]$ , $[\text {Mg}^{2+}]$ $[{Mg}^{2 +}]$ , and $[\text {Ca}^{2+}]$ $[{Ca}^{2 +}]$ significantly influence oil recovery, with strong interactions between $[\text {Na}^+]$ $[{Na}^{+}]$ and $[\text {Ca}^{2+}]$ $[{Ca}^{2 +}]$ , as well as $[\text {Ca}^{2+}]$ $[{Ca}^{2 +}]$ and $[\text {Mg}^{2+}]$ $[{Mg}^{2 +}]$ . Among all, $[\text {Na}^+]$ $[{Na}^{+}]$ exhibits the highest Sobol’ first-order value, indicating its dominant role in recovery variation. Temporal analysis further suggests that interactive effects outweigh individual contributions. To manage uncertainties, cumulative probability values ( $\hbox {P}_{{10}}$ $P_{10}$ , $\hbox {P}_{{50}}$ $P_{50}$ , and $\hbox {P}_{{90}}$ $P_{90}$ ) are employed for optimization, minimizing variability in recovery predictions. Finally, this research provides a toolkit for evaluating ion interactions and optimizing LSWF, underscoring the role of ionic concentrations in sensitivity analysis, supporting decision making and risk assessment in upstream applications.