Heterogeneous Aquifers Research Articles

Effects of calcite reactions on aquifer permeability in high-temperature aquifer thermal energy storage

Abstract High-temperature aquifer thermal energy storage (HT-ATES) in deep aquifers has generated significant interest due to its high storage capacity, compatibility with various renewable energy sources, and utilization of surplus heat from industry. This study introduces a thermo-hydro-geochemical coupled model to address the challenges of aquifer clogging and other damage, subjected to fluid temperature changes. The model is applied to assess changes to aquifer permeability and pumping pressure during water injection at various temperatures and pH conditions. This study also investigates the effect of the heterogeneous permeability distribution on HT-ATES systems. Calcium carbonate precipitation occurs near the injection well. Simulations at different pH levels reveal that the association between changes in pumping pressure and pH follows a parabolic function. Conversely, at the cold well, calcite dissolution rates and pumping pressure changes were found to exhibit a linear correlation with the injection temperature. In heterogeneous aquifers, pumping pressure at the hot well gradually increases with successive cycles, and the magnitude of pumping pressure changes grows as the correlation length increases. The results can be used to estimate permeability and pumping pressure variations near the hot well at the altered pH of the injected fluid. The results also imply a low risk of aquifer damage at the cold well. The saturation isoline map and the correlation functions provided in this study may be useful for optimizing the operating temperatures and design of water treatment measures for improved HT-ATES performance.

Improving the Accuracy of Groundwater Level Forecasting by Coupling Ensemble Machine Learning Model and Coronavirus Herd Immunity Optimizer

Abstract Groundwater levels are under severe pressure globally due to over-extraction, pollution, and climate change necessitating continuous monitoring for sustainable aquifer management. This study introduces a novel ensemble machine learning (En) model that integrates shallow and deep machine learning (ML) models, optimized through the coronavirus herd immunity optimizer (CHIO), for accurate groundwater level forecasting. This En model was applied to the Ergene River Basin, Türkiye, a region facing severe groundwater depletion and contamination due to intensive agricultural and industrial activities. Groundwater level data spanning 1966 to 2023 on a weekly basis from four wells were used, split into 70% for training and 30% for testing under short- and long-term scenarios. Using the partial autocorrelation function and gamma test the best lag numbers were determined for input data, reflecting aquifer heterogeneity. Score analysis, supported by statistical metrics such as the coefficient of determination (R²) and root mean square error (RMSE), was employed alongside visual aids to assess the developed En model performance. Results demonstrated that deep ML models outperformed shallow ML models achieving R² ~ 0.99 and RMSE ~ 0.5 m. The developed En model outperformed all individual ML models, with score values exceeding 200, and its predictions closely aligned with measured water levels during both testing phases. The findings underscored the developed En model’s contribution to achieving sustainable development goals (SDGs) by enhancing water-use efficiency and addressing environmental, economic, and social sustainability challenges. The proposed approach offers a reliable and adaptable solution for groundwater level forecasting, applicable to other aquifers worldwide. Graphical Abstract

Using a Well-Controlled Heterogeneous Permeability Field to Study Its Role on Miscible Density-Driven Convection in Porous Media and the Implications to Geological Carbon Sequestration

Summary In this work, we report on a new experimental method to construct well-controlled heterogeneous permeability fields to study miscible density-driven convection in quasi-2D porous media, which has implications for geological carbon sequestration (GCS) in saline aquifers. Dissolution trapping is a critical CO2 trapping mechanism in GCS, which can be accelerated by miscible density-driven convection. Previous studies on the role of permeability heterogeneity on miscible density-driven convection relied heavily on numerical simulation due to the challenges encountered by conventional experimental methods in the construction of a well-controlled heterogeneous permeability field. To solve this challenge, we developed a 3D-printing-assisted method to construct well-controlled heterogeneous permeability fields. In particular, the borders between different permeability regions in a sand box were extracted with digital image processing and then 3D printed. Silica sands having desired permeability values were placed into the corresponding space in the 3D-printed frame to construct the heterogeneous permeability field in the sand box. Unlike conventional experimental methods that rely on stacking cubic sediment blocks, the 3D-printing-assisted method can print the boundaries between different permeability regions with arbitrary lengths and directions, thereby enabling the construction of smooth boundaries between permeability regions, eliminating preferential flow paths in the orthotropic directions, and ensuring the isotropic properties of the constructed permeability field. We further studied the impact of permeability heterogeneity, characterized by the permeability’s coefficient of variation (COV) and spatial correlation length, on miscible density-driven convection, providing the first laboratory evidence for the role of different combinations of permeability’s COV and spatial correlation length in regulating convective dissolution by the fingering and channeling mechanisms. A high-permeability COV combined with a large spatial correlation length of permeability increases the length scale of the branching at the penetration front and the uncertainty on the dissolution mass flux across the top boundary. More CO2 can be stored in a moderately heterogeneous saline aquifer by convective dissolution than in a homogeneous saline aquifer during the same period of time after the onset of convective dissolution, which is caused by the higher average mass flux in the heterogeneous aquifer. However, the permeability heterogeneity does not further enhance CO2 storage when the saline aquifer is highly heterogeneous. With this work, we also extend the empirical correlation between the Sherwood number and Rayleigh number from homogeneous permeability fields to heterogeneous permeability fields. Keywords miscible density-driven convection, porous media, permeability heterogeneity, 3D printing, geological carbon sequestration

Numerical simulation of thermal effects on seawater intrusion management by coastal cutoff walls.

Numerical simulation of thermal effects on seawater intrusion management by coastal cutoff walls.

Characterization of Hydraulic Parameters via Sensitivity Maps for Frequency‐Based Oscillatory Pumping in 2D, Confined, Weakly Heterogeneous Aquifers

AbstractMulti‐frequency oscillatory pumping, in which the groundwater is extracted during a half period, and then reinjected, has recently been used to characterize aquifer heterogeneity. After the initial transition time, a steady periodic head can be observed at the observation well with constant amplitude and phase shift. However, the efficacy of utilizing multiple frequencies to enhance parameter estimation in hydraulic tomography is debatable. Most studies suggest that using multiple frequencies in joint inversion can gradually improve aquifer imaging. However, some researchers argue that additional frequencies add little to the resolution of hydraulic properties. This raises the question: how much non‐redundant information do multiple frequencies provide? In this study, we derive closed‐form analytical sensitivity maps (i.e., Fréchet kernels) of oscillatory pumping in 2D, unbounded, confined weakly heterogeneous aquifers by the sensitivity equation. It is found that the sensitivity maps of amplitude or phase shift are very similar to the sensitivity of drawdown to hydraulic parameters in constant‐rate pumping. Fréchet kernels indicate that multi‐frequency information, much like multi‐time information, can be instrumental for hydrogeological parameter inversion. According to the Fréchet kernels and their derivatives, we propose a method to select the optimal observation frequency, that is, the distance between the observation well and the pumping well is converted to frequency based on the hydraulic background values. Finally, we compare the effectiveness of single‐frequency and multi‐frequency observations in inverse transmissivity and storativity modeling using the iterative ensemble smoother. The results show that multi‐frequency oscillatory pumping can better characterize aquifer heterogeneity than a single frequency.

Variations in vulnerability across aquifer layers in a heterogeneous aquifer system

Variations in vulnerability across aquifer layers in a heterogeneous aquifer system

Mobilization of DNAPL lenses in heterogeneous aquifers using shear-thinning PEO polymers: Experimental and numerical study.

Mobilization of DNAPL lenses in heterogeneous aquifers using shear-thinning PEO polymers: Experimental and numerical study.

Coupled wellbore-aquifer numerical analysis of underground performance of compressed air energy storage in heterogeneous aquifers

Coupled wellbore-aquifer numerical analysis of underground performance of compressed air energy storage in heterogeneous aquifers

Electrochemical reduction for chlorinated hydrocarbons contaminated groundwater remediation: Mechanisms, challenges, and perspectives.

Electrochemical reduction for chlorinated hydrocarbons contaminated groundwater remediation: Mechanisms, challenges, and perspectives.

Long-term prediction for karst spring discharge and petroleum substances concentration based on the combination of LSTM and Transformer models.

Long-term prediction for karst spring discharge and petroleum substances concentration based on the combination of LSTM and Transformer models.

Investigation of the hydraulic conductivity and advancement rule in an annular effective heterogeneous aquifer around an injection single well

Investigation of the hydraulic conductivity and advancement rule in an annular effective heterogeneous aquifer around an injection single well

Classification of groundwater source protection areas in heterogeneous aquifers in plain areas based on Monte Carlo method

Classification of groundwater source protection areas in heterogeneous aquifers in plain areas based on Monte Carlo method

Using Advective Transport Phenomena to Account for Uncertainty of Conductivity in Monitoring Design.

Engineering practice in monitoring design aims at the optimum number of observation wells needed to assess the growth of a contaminated volume groundwater, the plume. Available methodologies rely on a combination of a numerical groundwater transport model, GIS-techniques and an optimization technique and require a relative huge amount of data and computer resources. The method of advective transport phenomena enables to calculate the longitudinal and vertical growth of a contaminant plume along the flow path by simple analytic expressions using only three stochastic parameters, the log conductivity variance and the horizontal and vertical characteristic lengths, that together describe the heterogeneity of the aquifer. In previous work, the calculated plume growth has been verified in 12 large experiments all over the world. The method is used to investigate the relationship between uncertainty in the conductivity variation and the plume growth by calculation of the spreading of water particles in a vertical section along the traveled path. In a very heterogeneous aquifer, virtually all water particles spread forward about equally generating a limited forward growth compared to the traveled distance that is not sensitive to uncertainty in the conductivity. In a nearly homogenous aquifer, only a part of the water particles is spread forward, which is repeated at different depths along the traveled path causing significant uncertainty in the position and length of the plume growth. Therefore, an observation network should be designed more densely in a homogeneous aquifer than in a heterogeneous one. A calculation tool is provided.

A numerical investigation of the effects of model parameterization on the delineation of source protection zones under uncertainty.

Source protection zone delineation has evolved over the past decades from fixed radius or analytical and numerical methods which do not consider uncertainty, to more complex stochastic numerical approaches. In this paper we explore options for delineating a source protection zone, while considering the inherent uncertainty involved in characterizing hydraulic conductivity. We consider a representative pumping well in an unconfined alluvial aquifer under steady-state flow conditions, with the hydraulic conductivity distribution inferred from borehole lithology data in the West Melton area near Christchurch, New Zealand. Lithologies are categorized according to their inferred hydraulic flow and transport properties, using two to four hydrofacies groupings. Probabilistic source protection zones are determined for alternative lithology categorization scheme and hydrofacies conductivity parameterization methods. Results show that the choice of calibration method significantly impacts the delineated source protection zone. In heterogeneous aquifers, the degree of protection offered by deeper pumping wells may be overstated, and forward particle tracking proved more comprehensive than backward tracking due to the complexity of flow paths near the well screen. Simple models, such as homogeneous models, require upscaled parameters to effectively represent aquifer heterogeneity, providing insights into how simplified source protection zone delineation could be made more robust in highly heterogeneous contexts.

Pore-scale visualization of LNAPL displacement by chemical agents in heterogeneous groundwater system.

Pore-scale visualization of LNAPL displacement by chemical agents in heterogeneous groundwater system.

Hydrochemical facies distribution, controlling mechanisms and natural background concentrations of major pollutants in Ganga-Yamuna interfluve aquifer, India.

Hydrochemical facies distribution, controlling mechanisms and natural background concentrations of major pollutants in Ganga-Yamuna interfluve aquifer, India.

Mapping 2D Hydraulic Tomography: Comparison of Deep Learning Algorithm and Quasi‐Linear Geostatistical Approach

ABSTRACTIn this study, we conduct a comparative analysis of the Quasi‐Linear Geostatistical Approach (QLGA) and deep learning algorithms for 2D hydraulic tomography underground, exploiting synthetic and real hydraulic head data from field settings. The hydraulic dataset is derived from multiple pumping tests at the Hydroscan observatory in Normandy, aiming to map the transmissivity heterogeneity of the gravel aquifer along the Seine riverbanks, which is critical for understanding and optimising hydrological processes. Two distinct inversion methodologies are addressed to decipher the piezometric data: a process‐based approach—QLGA—widely recognised for its effectiveness in depicting aquifer hydraulic properties, and a data‐driven approach based on Convolutional Neural Networks (CNNs). The QLGA method relies on iterative linearisation with calculations of the Jacobian matrix to minimise an objective function, while the CNN approach directly approximates operators through a novel circular architecture that allows for determining heterogeneity and evaluating its response within a single solver. Results from both methods demonstrate their efficacy in capturing subsurface heterogeneity where the resolution of local details is constrained by the limited number of piezometric measurements. While QLGA achieves a better fit between simulated and observed data, the CNN method effectively handles complex features while reducing smoothing in inversion solutions. When applied to real cases, both methods show strong agreement with observations from synthetic studies, emphasising their accuracy and comparability. The choice between QLGA and deep learning approaches thus depends on problem‐specific requirements, data availability, and interpretability needs, providing valuable insights for advanced subsurface characterisation.

The Effects of Xanthan Gum as a Synergistic Delivery Reagent on Perchloroethylene Remediation in Lower-Permeability Zones of Aquifers

Treating contamination plumes in relatively lower-permeability zones (LPZs) presents a significant challenge for injection-based remediation due to aquifer heterogeneity. Currently, xanthan gum, as a co-remediation agent, has been confirmed to enhance the removal efficiency of contaminants in these zones. However, its associated effects on plume migration remain to be clarified. This study revealed the mechanisms by which xanthan addition enhances the removal rate of perchloroethylene (PCE), as well as its effects on plume migration. The results demonstrated that the injection of xanthan induces adverse migration of contamination plumes. A nonlinear relationship was observed between xanthan concentration, injection rate, and remediation performance. Within the studied range (0 g/L–0.8 g/L; 10 mL/min–40 mL/min), an optimal xanthan concentration (0.8 g/L) and injection rate (25 mL/min) were identified, at which the PCE removal efficiency was significantly improved, and the contamination plume migration was effectively inhibited. For combinations of porous media with a lower permeability contrast, adding xanthan led to better performance. To provide a comprehensive assessment of the remediation performance, four key indicators were proposed: remediation measurement factor, PCE removal rate, sweeping uniformity, and injection pressure. The results identified the optimal remediation conditions: M-F combination with the lowest permeability contrast (4.9), 0.4 g/L xanthan, and an injection rate of 25 mL/min. These findings contribute valuable insights for the formulation of more efficient remediation strategies.

Determining Robust Optimal Pumping Solutions in a Heterogeneous Coastal Aquifer Using a Robust Decision-Making Approach and Bargaining Theory to Resolve Multiple Sources of Uncertainty

Determining Robust Optimal Pumping Solutions in a Heterogeneous Coastal Aquifer Using a Robust Decision-Making Approach and Bargaining Theory to Resolve Multiple Sources of Uncertainty

Earth recharge model with crossover behaviors: application of piecewise differentiation

The estimation of groundwater recharge is usually done with direct or indirect measurement techniques that are site-specific and derived primarily from flux measurements that due to the flexibility and uncertainty associated with heterogeneous systems has a high margin of error. Fractional derivatives, which are used to reflect the geological heterogeneity and fluid viscoelasticity, may be introduced to solve this challenge. Here, we develop sensitivity analyses to model groundwater recharge in a two-layer (homogeneous upper and highly heterogeneous lower) shallow unconfined aquifer system. The bottom of the model showed a non-Darcian fracture and matrix flow, and associated flow deviation, while the top of the model represented a uniform high-permeability and high-porosity layer, typical for calcite-rich areas. The EARTH model is the governing equation of the system, analytically solved through the use of Laplace and inverse Laplace transforms. A new multi-layer aquifer model for the spatial-parameter, temporal-parameter groundwater flow model established in Earthlab. The model features later flow, gradual layer transitions and appropritate boundary conditions. It also considers evapotranspiration and seasonal recharge, providing a better model for groundwater behavior in heterogeneous aquifer systems. A fractional-order differential equation is proposed to describe recharge dynamics for the homogeneous upper layer and a classical integer-order differential equation for the heterogeneous lower layer with non-Darcy flow. This work applies Caputo and Atangana-Baleanu fractional derivatives to investigate crossover behaviors in the system. The results show unique long-tail exponential growth structures in the homogeneous layer and crossover behaviors at early times that depend on the operator. In contrast, despite the scale invariance property of the Caputo derivative, the Atangana-Baleanu derivative detects alpha-to-alpha crossovers, stressing its ability to reproduce early-time behavior. This study presents a powerful solution for describing groundwater recharge in dual-layered aquifer systems by coupling a fractional differentiation model with the extended Mittag–Leffler law, providing a new insight into understanding heterogeneous and homogeneous formations. This approach may be cross-validated with field data and will provide more evidence for capillary-dominated flow, using fractional derivatives to model subsurface flow.