CO₂ plume geothermal systems offer a promising pathway for simultaneous carbon sequestration and renewable energy production, yet their optimization remains computationally prohibitive due to the complexity of coupled multi-phase flow, heat transport, and thermodynamic processes. This study presents a novel framework that integrates Non-isothermal Unsaturated-saturated Flow and Transport modeling with quantum neural network and hybrid quantum-classical ensemble regressors to accelerate CO₂ plume geothermal system design optimization. The methodology employs latin hypercube sampling to generate 1,000 Non-isothermal Unsaturated-saturated Flow and Transport simulations across several parameter spaces, extracting statistical features that undergo rigorous selection through Boruta, Chi-squared, and Pearson correlation algorithms with a standardized weight threshold of higher than 0.75. Two quantum architectures were developed to predict six geothermal variables, including system lifetime, injected, extracted, stored CO₂ mass, cumulative energy recovery and average heat extraction rate within lifetime. The quantum models achieved exceptional accuracy for most variables in the test section, with hybrid quantum-classical ensemble regressors architectures consistently outperforming quantum neural network variants, particularly when combined with boruta feature selection. Two optimization algorithms were employed for CO₂ plume geothermal system design, including moth flame optimization for single objectives and non-dominated sorting genetic algorithm Ⅱ for multi-objective scenarios to find robust optimal solutions based on developed surrogate models for injection overpressure, well spacing near and maximizing thermal energy extraction. The framework transformed a computationally intractable optimization requiring extensive simulation time into a rapid calculation while maintaining prediction accuracy comparable to full-physics models.

Managed Aquifer Recharge (MAR) is a strategic approach to artificially replenishing groundwater supplies and has become an integral component of global water resource management. The number of MAR projects has steadily increased in recent decades, yet many have failed to achieved their intended outcomes, underscoring the complexity of project implementation. This review is dedicated to examine existing research and reports on MAR performance and impacts, aiming to establish objective criteria for gauging the success and identify key factors influencing the effectiveness of MAR project. Five critical performance factors have been identified as major determinants of MAR performance: aquifer transmissivity, vertical permeability, availability of recharge water, recharge water quality, and aquifer thickness, geometry and boundary conditions. These factors are directly related to project success and significantly shape MAR outcomes. In addition, this review explores research-based strategies to improve MAR success, including cutting-edge methodologies, technological innovations, and integrated management approaches to address key challenges. The ultimate goal is to foster more efficient, effective, and sustainable MAR practices, thereby enhancing the resilience and sustainability of water resource management.

Industry-scale hydrogen is mainly produced by steam methane reforming (SMR), which uses natural gas as the feedstock and fuel and co-produces CO₂. This study aims to numerically evaluate hydrogen production by SMR under various reacting conditions. Unlike the previous studies with limited scenarios, the performance of SMR is continuously evaluated in a high-dimensional input-parameter space. The SMR plant including a combustor, a reformer, and a water-gas shifter is modeled in Aspen HYSYS software. The four key parameters, including methane fraction of the feedstock, reformer pressure and temperature, and shifter temperature, are treated uncertain and 50 samples are drawn from a four-dimensional parameter space defined by their ranges. Each sample is input to HYSYS model and mass ratio of each component in product streams is obtained as the output variables. Based on the 50 pairs of input-output data, response surfaces of the outputs are developed to surrogate HYSYS models. The fast response surface models are then used to calculate global sensitivity indices and evaluate SMR processes. Results show the reformer performance is controlled by temperature rather than pressure, and a temperature higher than 900 ${}^{\circ }$C can maximize the reaction rate. The water-gas shifting reaction is inhibited in the reformer but significantly enhanced in the shifter. Hydrogen is mainly produced in the reformer while the major function of the shifter is to convert CO to nontoxic CO₂.

CO₂ circulated geothermal production can be integrated with CO₂ geological sequestration as a utilization method to offset cost. Investigation of heterogeneity impact is limited to CO₂ sequestration and its effect on CO₂ circulation and associated heat recovery is unclear. This study is aimed to improve the understanding of this problem by numerical experiments. A set of spatially correlated heterogeneous porosity fields is generated using a variety of geostatistical parameters, i.e., variance, correlation lengths, anisotropy and azimuth. Heterogeneous fields of intrinsic permeability and initial/residual water saturation are derived from porosity using equations regressed from a field dataset. Twenty combinations of injection pressure and well space obtained by Latin-Hypercube sampling are deployed in each heterogeneous field, generating a suite of numerical geothermal reservoir models. Performance indicators, including lifespan, net stored CO₂, produced heat flux, and total recovered heat energy in lifespan, are calculated from each model simulation. The simulation results suggest that geologic heterogeneity could develop high-permeable CO₂ flow paths, causing bypass of the hot low-permeable zones, shortened lifespan and reduced total recovered heat energy. Depending on the azimuth, anisotropy can create either flow barriers or preferential flow paths, increasing or decreasing heat sweeping efficiency. The relative angle between horizontal wells and the axis of maximum continuity of the heterogeneity can be optimized to maximize heat recovery efficiency. These finds provide useful insights of interplay between geological heterogeneity, well placement and operation of CO₂ circulated geothermal production.