Pore-scale imaging of hydrogen displacement and trapping in porous media

Thaysen, Eike Marie; Butler, Ian B.; Hassanpouryouzband, Aliakbar; Freitas, Damien; Alvarez-Borges, Fernando; Krevor, Samuel; Heinemann, Niklas; Atwood, Robert C.; Edlmann, Katriona

doi:10.1016/j.ijhydene.2022.10.153

Cited by 51 publications

(22 citation statements)

References 60 publications

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“…Thaysen et al also observed that snap-off of H 2 clusters in the presence of brine can lead to low recovery of injected H 2 . However, they found that when H 2 was injected into dry rock, 100% recovery was achieved, suggesting that the wettability of the rock may play a significant role in the snap-off phenomenon.…”

Section: Resultsmentioning

confidence: 99%

“…59 Piston-like displacement competes with snap-off as the wetting fluid (brine) displaces the nonwetting phase (H 2 ) in porous media; this process has been identified as the swelling of water in the corner layers of a pore throat during the incursion of brine unto water-wet rocks until the capillary pressure is surpassed. 59 This phenomenon causes the nonwetting phase to be disconnected and the pore throat to be spontaneously filled with water. 59,60 Earlier studies have indicated that the contact angles of the H 2 /brine system on sandstone and quartz substrates were significantly lower than the contact angles of the CO 2 /brine system on sandstone and quartz substrates under similar conditions.…”

Section: Resultsmentioning

confidence: 99%

“…59 This phenomenon causes the nonwetting phase to be disconnected and the pore throat to be spontaneously filled with water. 59,60 Earlier studies have indicated that the contact angles of the H 2 /brine system on sandstone and quartz substrates were significantly lower than the contact angles of the CO 2 /brine system on sandstone and quartz substrates under similar conditions. 26,29,33 This suggests that the surface of sandstone substrates is more strongly water-wet in the presence of H 2 compared to CO 2 .…”

Section: Resultsmentioning

confidence: 99%

“…The brine resides at the pore throats and corners, whereas the H 2 behaved as a nonwetting phase, filling the pore center, signifying a water-wet system . Piston-like displacement competes with snap-off as the wetting fluid (brine) displaces the nonwetting phase (H 2 ) in porous media; this process has been identified as the swelling of water in the corner layers of a pore throat during the incursion of brine unto water-wet rocks until the capillary pressure is surpassed . This phenomenon causes the nonwetting phase to be disconnected and the pore throat to be spontaneously filled with water. , …”

Section: Resultsmentioning

confidence: 99%

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Snap-Off Effects and High Hydrogen Residual Trapping: Implications for Underground Hydrogen Storage in Sandstone Aquifer

Al-Yaseri,

Yekeen,

Al-Mukainah

et al. 2024

Energy Fuels

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Hydrogen (H 2 ) is a promising clean fuel that could replace fossil fuels for the actualization of the net zero carbon energy transition. Underground hydrogen storage (UHS) in sandstone formations is an essential component of the hydrogen economy value chain for achieving large-scale H 2 storage. In this study, snap-off effects and impacts of high hydrogen residual trapping on the viability of UHS in a Gosford sandstone formation were assessed from initial and residual H 2 saturations in the miniature core plugs. The flooded cores were imaged with X-ray microcomputed tomography (μCT) to identify the fluid (brine and H 2 ) distributions in the pore spaces. Results showed the presence of large interconnected stable H 2 clusters after the drainage process, with an initial H 2 saturation of almost 53%, suggesting that hydrogen will occupy more than half of the pore volume during storage. However, several disconnected H 2 ganglia and the snapped-off of H 2 droplets from the pore throats were noticed after the imbibition stage with almost 44% residual H 2 saturations. Such highly residually trapped H 2 in the strongly water-wet Gosford sandstone will be difficult to mobilize, resulting in the possible withdrawal of just 9% stored H 2 . The study suggests that the water-wet system could produce high H 2 residual saturations, which is unfavorable for hydrogen withdrawal and extraction at the peak energy demand period due to disconnection and trapping of the nonwetting phase.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Snap-Off Effects and High Hydrogen Residual Trapping: Implications for Underground Hydrogen Storage in Sandstone Aquifer

Al-Yaseri,

Yekeen,

Al-Mukainah

et al. 2024

Energy Fuels

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“…A better understanding of the drilling operations can be obtained using the performance prediction models and the analysis results from the field observations. − Better and more efficient results can be achieved by changing and modifying the effective drilling parameters . Optimizing drilling operations involves considering a number of variables, including cost, safety, and well completion, but penetration rate (ROP) is one of the key variables. , The prediction of ROP is a key factor in the success of drilling projects and is affected by various factors [e.g.…”

Section: Introductionmentioning

confidence: 99%

Determination of the Rate of Penetration by Robust Machine Learning Algorithms Based on Drilling Parameters

Alavi Nezhad Khalil Abad,

Hazbeh,

Rajabi

et al. 2023

ACS Omega

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Underground resources, particularly hydrocarbons, are critical assets that promote economic development on a global scale. Drilling activities are necessary for the extraction and recovery of subsurface energy resources, and the rate of penetration (ROP) is one of the most important drilling parameters. This study forecasts the ROP using drilling data from three Iranian wells and hybrid LSSVM-GA/PSO algorithms. These algorithms were chosen due to their ability to reduce noise and increase accuracy despite the high level of noise present in the data. The study results revealed that the LSSVM-PSO method has an accuracy of roughly 97% and is more precise than the LSSVM-GA technique. The LSSVM-PSO algorithm also demonstrated improved accuracy in test data, with RMSE = 1.92 and R 2 = 0.9516. Furthermore, it was observed that the accuracy of the LSSVM-PSO model improves and degrades after the 50th iteration, whereas the accuracy of the LSSVM-GA algorithm remains constant after the 10th iteration. Notably, these algorithms are advantageous in decreasing data noise for drilling data.

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