Reactive Transport Process of Earthquake-induced Hydrochemical Changes in Guanding Thermal Spring,Western Sichuan,China

Earthquake-related hydrochemical changes in thermal springs have been widely observed;however,quantitative modeling of the reactive transport process is absent.In the present study,we apply reactive transport simulation to capture the hydrochemical responses in a thermal spring following the Wenchuan Ms 8.0 and Lushan Ms 7.0 earthquakes.We first constrain deep reservoir geothermal fluid compositions and temperature by multicomponent geothermometry,and then a reactive geochemical transport model is constructed to reproduce the hydrochemical evolution process.The results show that the recharge from the shallow aquifer increases gradually until it reaches a peak because of the permeability enhancement caused by the Lushan earthquake,which may be the mechanism to explain the earthquake-related hydrochemical responses.In contrast to the postseismic effect of the Wenchuan earthquake,the chemical evolution can be considered as hydrochemical anomalies related to the Lushan earthquake.This study proves that the efficient simulation of reactive transport processes is useful for investigating earthquake-related signals in hydrochemical time series.

An artificial-neural-network-based surrogate modeling workflow for reactive transport modeling

Process-based reactive transport modeling(RTM)integrates thermodynamic and kinetically controlled fluid-rock interactions with fluid flow through porous media in the subsurface and surface environment.RTM is usually conducted through numerical programs based on the first principle of physical processes.However,the calculation for complex chemical reactions in most available programs is an iterative process,where each iteration is in general computationally intensive.A workflow of neural networkbased surrogate model as a proxy for process-based reactive transport simulation is established in this study.The workflow includes(1)base case RTM design,(2)development of training experiments,(3)surrogate model construction based on machine learning,(4)surrogate model validation,and(5)prediction with the calibrated model.The training experiments for surrogate modeling are generated and run prior to the predictions using RTM.The results show that the predictions from the surrogate model agree well with those from processes-based RTM but with a significantly reduced computational time.The well-trained surrogate model is especially useful when a large number of realizations are required,such as the sensitivity analysis or model calibration,which can significantly reduce the computational time compared to that required by RTM.The benefits are(1)it automatizes the experimental design during the sensitivity analysis to get sufficient numbers and coverage of the training cases;(2)it parallelizes the calculations of RTM training cases during the sensitivity analysis to reduce the simulation time;(3)it uses the neural network algorithm to rank the sensitivity of the parameters and to search the optimal solution for model calibration.

Reactive Transport Modeling of Long-Term CO2 Sequestration Mechanisms at the Shenhua CCS Demonstration Project,China

Carbon dioxide injection into deep saline aquifers results in a variety of strongly coupled physical and chemical processes. In this study, reactive transport simulations using a 2-D radial model were performed to investigate the fate of the injected CO2, the effect of CO2-water-rock interactions on mineral alteration, and the long-term CO2 sequestration mechanisms of the Liujiagou Formation sandstone at the Shenhua CCS（carbon capture and storage） pilot site of China. Carbon dioxide was injected at a constant rate of 0.1 Mt/year for 30 years, and the fluid flow and geochemical transport simulation was run for a period of 10 000 years by the TOUGHREACT code according to the underground conditions of the Liujiagou Formation. The results show that different trapping phases of CO2 vary with time. Sensitivity analyses indicate that plagioclase composition and chlorite presence are the most significant determinants of stable carbonate minerals and CO2 mineral trapping capacity. For arkosic arenite in the Liujiagou Formation, CO2 can be immobilized by precipitation of ankerite, magnesite, siderite, dawsonite, and calcite for different mineral compositions, with Ca（2＋）, Mg（2＋）, Fe（2＋） and Na＋ provided by dissolution of calcite, albite（or oligoclase） and chlorite. This study can provide useful insights into the geochemistry of CO2 storage in other arkosic arenite（feldspar rich sandstone） formations at other pilots or target sites.

Simulation of transport mechanism of radium isotopes in aquifer on the southern coast of Laizhou Bay

Naturally occurring radium(^(223)Ra,^(224)Ra,^(226)Ra,and^(228)Ra)isotopes have been widely applied as geochemical tracers in marine environments,especially when estimating the submarine groundwater discharge(SGD).In this sense,the influencing factors and transport mechanism of radium isotope activity in aquifers can be key information for SGD estimation.This work evaluates the adsorption/desorption behavior of^(224)Ra and^(226)Ra in the solid-liquid phase through a leaching experiment and analysis of field data.The results suggested that radium isotope activity was positively correlated with salinity and grain size,in the case of abundant sediments.Through ion analysis,we found that the ions(Na^(+),Ca^(2+),Mg^(2+),and Ba^(2+))exchanged with radium isotopes in the process of transport.A 1-D reactive transport model was established to simulate the transport process of radium isotope in aquifers.The model successfully simulated the variation of radium isotope desorption activity with salinity and was subsequently verified in the field.This study contributes to the understanding of the geochemical behavior of radium isotopes in aquifers and provides guidance for selecting a suitable groundwater endmember in SGD estimation.

Assessment of the Greenhouse Gas Footprint and Environmental Impact of CO_(2)and O_(2)in situ Uranium Leaching

Under the new development philosophy of carbon peaking and carbon neutrality,CO_(2)and O_(2)in situ leaching(ISL)has been identified as a promising technique for uranium mining in China,not only because it solves carbon dioxide utilization and sequestration,but it also alleviates the environmental burden.However,significant challenges exist in assessment of CO_(2)footprint and water-rock interactions,due to complex geochemical processes.Herein this study conducts a three-dimensional,multicomponent reactive transport model(RTM)of a field-scale CO_(2)and O_(2)ISL process at a typical sandstone-hosted uranium deposit in Songliao Basin,China.Numerical simulations are performed to provide new insight into quantitative interpretation of the greenhouse gas(CO_(2))footprint and environmental impact(SO_(4)^(2–))of the CO_(2)and O_(2)ISL,considering the potential chemical reaction network for uranium recovery at the field scale.RTM results demonstrate that the fate of the CO_(2)could be summarized as injected CO_(2)dissolution,dissolved CO_(2)mineralization and storage of CO_(2)as a gas phase during the CO_(2)and O_(2)ISL process.Furthermore,compared to acid ISL,CO_(2)and O_(2)ISL has a potentially smaller environmental footprint,with 20%of SO_(4)^(2–)concentration in the aquifer.The findings improve our fundamental understanding of carbon utilization in a long-term CO_(2)and O_(2)ISL system and provide important environmental implications when considering complex geochemical processes.

Comparative Study of Acid and Alkaline Stimulants with Granite in an Enhanced Geothermal System

The Enhanced Geothermal System(EGS) is an artificial geothermal system that aims to economically extract heat from hot dry rock(HDR) through the creation of an artificial geothermal reservoir. Chemical stimulation is thought to be an effective method to create fracture networks and open existing fractures in hot dry rocks by injecting chemical agents into the reservoir to dissolve the minerals. Granite is a common type of hot dry rock. In this paper, a series of chemical stimulation experiments were implemented using acid and alkaline agents under high temperature and pressure conditions that mimic the environment of formation. Granite rock samples used in the experiments are collected from the potential EGS reservoir in the Matouying area, Hebei, China. Laboratory experimental results show that the corrosion ratio per unit area of rock is 3.2% in static acid chemical experiments and 0.51% in static alkaline chemical experiments. The permeability of the core is increased by 1.62 times in dynamic acid chemical experiments and 2.45 times in dynamic alkaline chemical experiments. A scanning electron microscope analysis of the core illustrates that secondary minerals, such as chlorite, spherical silica, and montmorillonite, were formed, due to acid-rock interaction with plagioclase being precipitated by alkaline-rock interactions. Masking agents in alkaline chemical agents can slightly reduce the degree of plagioclase formation. A chemical simulation model was built using TOUGHREACT, the mineral dissolution and associated ion concentration variation being reproduced by this reactive transport model.

Groundwater fluoride contamination:A reappraisal

Dissolution of fluorite （CaF2） and/or fluorapatite （FAP） [Cas（PO4）3F], pulled by calcite precipitation, is thought to be the dominant mechanism responsible for groundwater fluoride （F） contamination. Here, one dimensional reactive-transport models are developed to test this mechanism using the published dissolution and precipitation rate kinetics for the mineral pair FAP and calcite. Simulation results correctly show positive correlation between the aqueous concentrations of F and CO2 and negative correlation between F- and Ca^2＋. Results also show that precipitation of calcite, contrary to the present understanding, slows down the FAP dissolution by 10G orders of magnitude compared to the FAP dissolution by hydrolysis. For appreciable amount of fluoride contamination rock-water interaction time must be long and of order 106 years.

A projected Newton algorithm based on chemically allowed interval for chemical equilibrium computations

The chemical equilibrium equations utilized in reactive transport modeling are complex and nonlinear,and are typically solved using the Newton-Raphson method.Although this algorithm is known for its quadratic convergence near the solution,it is less effective far from the solution,especially for ill-conditioned problems.In such cases,the algorithm may fail to converge or require excessive iterations.To address these limitations,a projected Newton method is introduced to incorporate the concept of projection.This method constrains the Newton step by utilizing a chemically allowed interval that generates feasible descending iterations.Moreover,we utilize the positive continuous fraction method as a preconditioning technique,providing reliable initial values for solving the algorithms.The numerical results are compared with those derived using the regular Newton-Raphson method,the Newton-Raphson method based on chemically allowed interval updating rules,and the bounded variable least squares method in six different test cases.The numerical results highlight the robustness and efficacy of the proposed algorithm.

Effect of modeling factors on the dissolution-diffusion-convection process during CO2 geological storage in deep saline formations

It is well known that during CO2 geological storage, density-driven convective activity can significantly accelerate the dissolution of injected CO2 into water. This action could limit the escape of supercritical CO2 from the storage formation through vertical pathways such as fractures, faults and abandoned wells, consequently increasing permanence and security of storage. First, we investigated the effect of numerical perturbation caused by time and grid resolution and the convergence criteria on the dissolution-diffusion-convection （DDC） process. Then, using the model with appropriate spatial and temporal resolution, some uncertainty parameters investigated in our previous paper such as initial gas saturation and model boundaries, and other factors such as relative liquid permeability and porosity modification were used to examine their effects on the DDC process. Finally, we compared the effect of 2D and 3D models on the simulation of the DDC process. The above modeling results should contribute to clear understanding and accurate simulation of the DDC process, especially the onset of convective activity, and the CO2 dissolution rate during the convection-dominated stage.