Multiscale Characterization and Quantification of Arsenic Mobilization and Attenuation During Injection of Treated Coal Seam Gas Coproduced Water into Deep Aquifers

Abstract

Coal seam gas production involves generation and management of large amounts of co‐produced water. One of the most suitable methods of management is injection into deep aquifers. Field injection trials may be used to support the predictions of anticipated hydrological and geochemical impacts of injection. The present work employs reactive transport modeling (RTM) for a comprehensive analysis of data collected from a trial where arsenic mobilization was observed. Arsenic sorption behavior was studied through laboratory experiments, accompanied by the development of a surface complexation model (SCM). A field‐scale RTM that incorporated the laboratory‐derived SCM was used to simulate the data collected during the field injection trial and then to predict the long‐term fate of arsenic. We propose a new practical procedure which integrates laboratory and field‐scale models using a Monte Carlo type uncertainty analysis and alleviates a significant proportion of the computational effort required for predictive uncertainty quantification. The results illustrate that both arsenic desorption under alkaline conditions and pyrite oxidation have likely contributed to the arsenic mobilization that was observed during the field trial. The predictive simulations show that arsenic concentrations would likely remain very low if the potential for pyrite oxidation is minimized through complete deoxygenation of the injectant. The proposed modeling and predictive uncertainty quantification method can be implemented for a wide range of groundwater studies that investigate the risks of metal(loid) or radionuclide contamination.

Conceptual Model of Arsenic Mobility in the Shallow Alluvial Aquifers Near Venice (Italy) Elucidated Through Machine Learning and Geochemical Modeling

“…We adopted a surface complex model (SCM) to provide a mechanistic quantification of As adsorption behavior as a function of the dissolved As concentration and speciation and the solution pH. The SCM considers the influence of competing ions such as phosphate or bicarbonate as well as the density of adsorption sites on the host minerals, mainly the HFOs ( Rathi et al, 2017). Sorption and desorption of As to reactive surfaces were therefore simulated through a set of surface complexation reactions for As(III) and As(V) based on the surface sorption sites defined for HFOs, the primary expected sorption sites for As.…”

“…Identifying a valid site‐specific conceptual model able to describe As mobility in groundwater is fundamental for many purposes related to As risk management. This includes the setup of process‐based geochemical models (e.g., Appelo & Postma, 2005; Gao et al, 2020; Jakobsen et al, 2018; Michael & Khan, 2016; Postma et al, 2007; Rathi et al, 2017; Rotiroti et al, 2014) predicting the spatial and temporal scales of occurrence of As concentrations in groundwater (e.g., predicting where As concentrations exceed the 10 μg/L recommended by World Health Organization [WHO]).…”

Assessing and Managing Large‐Scale Geochemical Impacts From Groundwater Replenishment With Highly Treated Reclaimed Wastewater

“…The aforementioned cases also highlight that the planning and implementation of MAR schemes requires a thorough, site-specific geochemical understanding, as well as the necessary tools for predicting the potential for groundwater quality risks and identifying technical options to mitigate these risks. Such a site-specific understanding is typically developed by a combination of hydrogeological and geochemical characterization activities (e.g., Rathi et al, 2017), laboratory tests (e.g., Fakhreddine et al, 2015;Schafer et al, 2018) and short-term field injection trials (e.g., Seibert et al, 2014Seibert et al, , 2016, or push-pull tests (e.g., Fakhreddine et al, 2020;Prommer et al, 2018;Rathi et al, 2017). Short-term field experiments can often provide some early warning signs of geochemical disequilibrium, and the interpretation of these results can be used to identify the geochemical mechanisms that control the water quality evolution as the injectant migrates through the native aquifer sediments (Rathi et al, 2017).…”

“…Such a site-specific understanding is typically developed by a combination of hydrogeological and geochemical characterization activities (e.g., Rathi et al, 2017), laboratory tests (e.g., Fakhreddine et al, 2015;Schafer et al, 2018) and short-term field injection trials (e.g., Seibert et al, 2014Seibert et al, , 2016, or push-pull tests (e.g., Fakhreddine et al, 2020;Prommer et al, 2018;Rathi et al, 2017). Short-term field experiments can often provide some early warning signs of geochemical disequilibrium, and the interpretation of these results can be used to identify the geochemical mechanisms that control the water quality evolution as the injectant migrates through the native aquifer sediments (Rathi et al, 2017). Additionally, the mechanistic understanding derived from the field experiment can be used to modify the AWT process to enhance the geochemical compatibility between the injectant and the aquifer sediments (Prommer et al, 2018).…”

Unraveling biogeochemical complexity through better integration of experiments and modeling

“…However, in recent years heuristic algorithms, such as particle swarm optimization (PSO), 35 have shown great promise in being a good compromise between being able to obtain the global solution to highly nonlinear inverse problems but at a computational expense much less than MCMC methods. 18,19,[21][22][23]32,[36][37][38][39][40] However, it is important to note that, like the Levenberg-Marquardt-type methods, such heuristic methods do not necessarily provide an immediate nonlinear estimation of parameter uncertainty.…”