Abstract
Underground Hydrogen Storage (UHS) has received significant attention over the past few years as hydrogen seems well-suited for adjusting seasonal energy gaps.
We present an integrated reservoir-well model for “Viking A″ the depleted gas field in the North Sea, as a potential site for UHS. Our findings show that utilizing the integrated model results in more reasonable predictions as the gas composition changes over time. Sensitivity analyses show that the lighter the cushion gas, the more production can be obtained. However, the purity of the produced hydrogen will be affected to some extent, which can be enhanced by increasing the fill-up period and the injection rate. The results also show that even though hydrogen diffuses into the reservoir and mixes up with the native fluids (mainly methane), the impact of hydrogen diffusion is marginal. All these factors will potentially influence the project's economics.
We present an integrated reservoir-well model for “Viking A″ the depleted gas field in the North Sea, as a potential site for UHS. Our findings show that utilizing the integrated model results in more reasonable predictions as the gas composition changes over time. Sensitivity analyses show that the lighter the cushion gas, the more production can be obtained. However, the purity of the produced hydrogen will be affected to some extent, which can be enhanced by increasing the fill-up period and the injection rate. The results also show that even though hydrogen diffuses into the reservoir and mixes up with the native fluids (mainly methane), the impact of hydrogen diffusion is marginal. All these factors will potentially influence the project's economics.
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 19160-19171 |
| Seitenumfang | 12 |
| Fachzeitschrift | International Journal of Hydrogen Energy |
| Jahrgang | 48.2023 |
| Ausgabenummer | 50 |
| DOIs | |
| Publikationsstatus | Elektronische Veröffentlichung vor Drucklegung. - 24 Feb. 2023 |
Bibliographische Notiz
Funding Information:The authors gratefully acknowledge Computer Modeling Group (CMG) for providing the CoFlow license for the present work. We also would like to thank Faraj Zarei and Reza Malakooti for their generous and continuous support during the first author's thesis.
Publisher Copyright:
© 2023 The Author(s)
UN SDGs
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