2026/07/01 by Mariana Teixeira de Azevedo, Alexsandro S. E. da Cruz, Alexsandro S. E. Cruz +7
Engineering · Medicine · Physics and Astronomy · #Advanced MRI Techniques and Applications #Hydrocarbon exploration and reservoir analysis #NMR spectroscopy and applications
paper · pdf · doi:10.1007/s00723-026-01845-9
openalex publication_date 2026/07/01 · openalex created_date 2026/07/02 · openalex updated_date 2026/07/30
Abstract Accurate quantification of multiphase fluid saturations in reservoir rocks remains a central challenge in petrophysics, with direct implications for hydrocarbon recovery optimization. Here, we present an integrated methodology that combines high-field nuclear magnetic resonance (NMR) imaging with relaxation-based contrast to quantify oil and water distributions in synthetic porous media. Controlled porous samples were fabricated by sintering soda–lime glass microspheres with defined grain sizes (75–125 \upmu \text m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>μ</mml:mi> <mml:mtext>m</mml:mtext> </mml:mrow> </mml:math> , 150–212 \upmu \text m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>μ</mml:mi> <mml:mtext>m</mml:mtext> </mml:mrow> </mml:math> , 250–300 \upmu \text m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>μ</mml:mi> <mml:mtext>m</mml:mtext> </mml:mrow> </mml:math> ) and saturated with known oil–water proportions. Chemical shift contrast was employed to distinguish fluid phases, while transverse relaxation ( T2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>T</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:math> ) measurements revealed distinct signal decay behaviors that enabled robust grayscale differentiation in high-field NMR images. A custom image-analysis software was developed to extract intensity histograms from T2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>T</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:math> -weighted images, allowing pixel-level quantification of each fluid phase. Across all tested samples, the methodology achieved an average quantification error below 10%, demonstrating its robustness and potential as a non-invasive approach for fluid characterization in reservoir analogs, with relevance to reservoir characterization, enhanced oil recovery, and environmental applications.