Numerical simulation of a comparative study on heat extraction from Soultz-sous-For\^ets geothermal field using supercritical carbon dioxide and water as a working fluid

Geothermal energy is an infinite energy source for the present human society. Energy extraction from the deep subsurface requires engineering using a working fluid that circulates between well doublet. Due to its thermal properties, CO2 is an ideal option as a heat transfer fluid. By using CO2, working fluid loss is an advantage compared to other working fluids. This study developed a field-scale hydro-thermal model to examine the heat extraction potential from Soultz-sous-For\^ets with CO2 as the working fluid. Results are compared for the same scenario with water as the working fluid. A better understanding of the heat extraction mechanism is established by considering the reservoir response and the wellbore heat exchange. Sensitivity analyses are performed for different injection temperatures and flow rates for 50 years. Results show that the wellbore effect is multiple times higher than the reservoir response to the production temperature. Furthermore, lowering the injection temperature eventuates to a smaller temperature reduction at the subsurface, enhancing the overall heat extraction potential with a minor impact on thermal breakthrough. The cold region developed around the injection wellbore may affect the production fluid temperature due to its proximity to the production wellbore. To reach higher heat extraction efficiency, it is essential to use sufficient wellbore spacing. CO2 can be used as working fluid for over 50 years as it does not show significant thermal breakthrough and temperature plume evolution in the reservoir under studied conditions. CO2 shows lower temperature reduction for all injection rates and temperatures for 50 years of operation.Comment: 17 pages, 8 figure

CO₂ geological sequestration in heterogeneous binary media: Effects of geological and operational conditions

    Realistic representation of subsurface heterogeneity is essential to better understand and effectively predict the migration and trapping patterns of carbon dioxide (CO2 ) during geological carbon sequestration (GCS). Many candidate aquifers for GCS have sedimentary architectures which reflect fluvial deposition, where coarser-grained facies with higher-permeability (e.g., sandstone) are juxtaposed within finer-grained facies with lower-permeability (e.g., shale). Because the subsurface is difficult to access and sample, geostatistical methods are often used to model the spatial distribution of geological facies across different scales. We use a transition-probability based approach to simulate heterogeneous systems with binary facies distributions and the resulting petrophysical properties at the field scale. The approach produces heterogeneity fields which honor observable and physical facies attributes (e.g., volumetric proportions, mean lengths, and juxtapositional tendencies). Further, we use the associated facies-dependent properties for both relative permeability and capillary pressure relations and their hysteretic behavior. Heterogeneous facies models are used to investigate the sensitivity of different trapping mechanisms (i.e., dissolution, residual trapping) as well as CO2 plume dynamics to variability in (1) the spatial organization and connectivity of sedimentary facies types; (2) aquifer temperature; (3) CO2 injection period; (4) perforation length; and (5) the level of impurity, represented here as methane (CH4 ) present in injected CO2 streams. Model results show that the magnitudes of residual and solubility trapping are reduced by increasing the percentage and degree of connectivity of high-permeability facies. An increase in aquifer temperature leads to a decrease in residual trapping and an increase in solubility trapping. Results also reveal that for a given volume of injected CO2 , shorter injection times yield higher total amounts of trapped CO2 . Similarly, wells perforated over a shorter thickness of the aquifer contribute to an increase in both residual and solubility trapping. We also find that increased CH4 concentrations in the injected CO2 streams decrease residual trapping while increasing solubility trapping. This effect is more pronounced at shallower depths, where the pressure and temperature of the aquifer are lower.Cited as: Ershadnia, R., Wallace, C.D., Soltanian, M.R. CO2 geological sequestration in heterogeneous binary media: Effects of geological and operational conditions. Advances in Geo-Energy Research, 2020, 4(4): 392-405, doi: 10.46690/ager.2020.04.0

Influence of Streambed Heterogeneity on Hyporheic Flow and Sorptive Solute Transport

The subsurface region where river water and groundwater actively mix (the hyporheic zone) plays an important role in conservative and reactive solute transport along rivers. Deposits of high-conductivity (K) sediments along rivers can strongly control hyporheic processes by channeling flow along preferential flow paths wherever they intersect the channel boundary. Our goal is to understand how sediment heterogeneity influences conservative and sorptive solute transport within hyporheic zones containing high- and low-K sediment facies types. The sedimentary architecture of high-K facies is modeled using commonly observed characteristics (e.g., volume proportion and mean length), and their spatial connectivity is quantified to evaluate its effect on hyporheic mixing dynamics. Numerical simulations incorporate physical and chemical heterogeneity by representing spatial variability in both K and in the sediment sorption distribution coefficient ( K d ). Sediment heterogeneity significantly enhances hyporheic exchange and skews solute breakthrough behavior, while in homogeneous sediments, interfacial flux and solute transport are instead controlled by geomorphology and local-scale riverbed topographies. The hyporheic zone is compressed in sediments with high sorptive capacity, which limits solute interactions to only a small portion of the sedimentary architecture and thus increases retention. Our results have practical implications for groundwater quality, including remediation strategies for contaminants of emerging concern

An integrated inversion framework for heterogeneous aquifer structure identification with single-sample generative adversarial network

Versión aceptada de https://doi.org/10.1016/j.jhydrol.2022.127844[Abstract:] Generating reasonable heterogeneous aquifer structures is essential for understanding the physicochemical processes controlling groundwater flow and solute transport better. The inversion process of aquifer structure identification is usually time-consuming. This study develops an integrated inversion framework, which combines the geological single-sample generative adversarial network (GeoSinGAN), the deep octave convolution dense residual network (DOCRN), and the iterative local updating ensemble smoother (ILUES), named GeoSinGAN-DOCRN-ILUES, for more efficiently generating heterogeneous aquifer structures. The performance of the integrated framework is illustrated by two synthetic contaminant experiments. We show that GeoSinGAN can generate heterogeneous aquifer structures with geostatistical characteristics similar to those of the training sample, while its training time is at least 10 times faster than that of typical approaches (e.g., multi-sample-based GAN). The octave convolution layer and multi-residual connection enable the DOCRN to map the heterogeneity structures to the state variable fields (e.g., hydraulic head, concentration distributions) while reducing the computational cost. The results show that the integrated inversion framework of GeoSinGAN and DOCRN can effectively and reasonably generate the heterogeneous aquifer structures.This work was funded by the National Key R&D Program of China (No.2018YFC1800904), the National Natural Science Foundation of China [NSFC: 41772253, 41972249], Jilin University through an innovation project awarded to the corresponding author [45119031A035], JLU Science and Technology Innovative Research Team [JLUSTIRT 2019TD-35] and partially supported by the Graduate Innovation Fund of Jilin University awarded to the first author (101832020CX233). Additional funding was provided by the Project (No. QQHR-2016-06) of Groundwater Quality Evaluation in Central City of Tsitsihar, Heilongjiang Province, China. We thank the ILUES and ConSinGAN developers for sharing their codes (https://github.com/cics-nd/cnn-inversion; https://github.com/tohinz/ConSinGAN). The geologic data used to represent permeability map distribution can be found in http://www.trainingimages.org. The authors would finally like to thank the two anonymous reviewers and the Editors for their constructive comments to improve the paper.China. National Key R&D Program of China; 2018YFC1800904China. National Natural Science Foundation of China; 41772253China. National Natural Science Foundation of China; 41972249China. Jilin University; 45119031A035China. JLU Science and Technology Innovative Research Team; JLUSTIRT 2019TD-35China. Graduate Innovation Fund of Jilin University; 101832020CX233China. Groundwater Quality Evaluation in Central City of Tsitsihar, Heilongjiang Province; QQHR-2016-0