Data-driven Assessment and Optimization of High-temperature Aquifer Thermal Energy Storage in Depleted Clastic Hydrocarbon Reservoirs
  • Metaadatok
Tartalom: https://doktori.bibl.u-szeged.hu/id/eprint/13021/
Archívum: SZTE Doktori Értekezések Repozitórium
Gyűjtemény: Tudományterületek = Természettudományok: Földtudományok
Típus = Disszertáció
Cím:
Data-driven Assessment and Optimization of High-temperature Aquifer Thermal Energy Storage in Depleted Clastic Hydrocarbon Reservoirs
Létrehozó:
Abdulhaq Hawkar
Dátum:
2026
Téma:
01.05.06.01. Geológia, tektonika, vulkanológia
02.14.03.17.01. Geotermia
Tartalmi leírás:
This dissertation develops an integrated, uncertainty-aware, data-driven framework to assess, design, and optimize high-temperature aquifer thermal energy storage (HT-ATES) in depleted clastic hydrocarbon reservoirs, using Hungary’s Pannonian Basin as a representative testbed. The research combines probabilistic multi-criteria decision analysis (MCDA–AHP) with geostatistical simulation to screen and rank suitable storage zones under subsurface uncertainty, then applies coupled groundwater-flow and heat-transport numerical modelling (MODFLOW–MT3DMS) to quantify thermal plume evolution, recovery efficiency, and breakthrough risks in heterogeneous reservoirs. To scale evaluation and optimization, supervised machine-learning surrogates (e.g., Random Forest) are trained on simulation ensembles to rapidly predict thermal performance across large well inventories, while a hybrid workflow (e.g., XGBoost with spatial residual correction) delineates 3D sand-channel architecture and flow-zone connectivity to support well placement and thermal-breakthrough prevention. Together, the results show that repurposing depleted reservoirs and legacy well infrastructure can provide practical seasonal heat-storage solutions for district-heating and industrial applications, enabling faster, lower-cost deployment pathways that support decarbonization and energy-security goals.
Nyelv:
magyar
magyar
angol
Típus:
Disszertáció
NonPeerReviewed
Formátum:
text
text
Azonosító:
Abdulhaq Hawkar Data-driven Assessment and Optimization of High-temperature Aquifer Thermal Energy Storage in Depleted Clastic Hydrocarbon Reservoirs. Doktori értekezés, Szegedi Tudományegyetem (2000-). (2026)
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