Solute Reactive Tracers for Hydrogeological Applications: A Short Review and Future Prospects

A modified and rapid method for the single-well push-pull (SWPP) test using SF6, Kr, and uranine tracers

In the present study, a single-well push-pull (SWPP) test was conducted with multi-component tracers, including inert gas (SF₆ and Kr) and uranine (conservative), to understand the volatile/semi-volatile component transport characteristics in the groundwater system. In an SWPP test, it is essential to obtain an initial breakthrough curve (BTC) of the inert gas concentration at the beginning of the pulling stage to analyze the hydraulic properties of the groundwater system. As a result of the SWPP test using a proposed method in this study, physicochemical parameters of the groundwater and BTC of gas tracers and uranine were acquired simultaneously and successfully. In addition, on-site measurements of uranine, pCO₂, and water quality data, such as electrical conductivity (EC), temperature, pH, and dissolved oxygen, were undertaken. Modification of an existing pCO₂ measuring system allowed the gas samples to be collected, transported, and analyzed for inert gas components within a few hours. As a result, reliable and interpretable data with a recovery ratio of 26%, 85%, and 95% for SF_6, Kr, and uranine, respectively, were obtained. The differences in the recovery ratio were utilized to identify the environmental system, whether it contains gas inside the isolated system (closed) or not (open), and to understand plume behavior characteristics in the experimental zone. By applying a two-dimensional advection-dispersion model to the acquired tracer test data and comparing the observed and computed tracer concentrations, helpful information was obtained on the hydraulic and transport characteristics of the targeted zone. This method can be extended to the design of dissolved CO₂ transport monitoring of an aquifer above a CCS site.

Effects of Velocity and Permeability on Tracer Dispersion in Porous Media

During micro-scale tracer flow in porous media, the permeability and fluid velocity significantly affect the fluid dispersion properties of the media. However, the relationships between the dispersion coefficient, permeability, and fluid velocity in core samples are still not clearly understood. Two sets of experiments were designed to study the effects of tracer fluid flow velocity and porous medium permeability on the dispersion phenomenon in a core environment, using natural and sand-filled cores, respectively. From experimental data-fitting by a mathematical model, the relationship between the dispersion coefficient, flow velocity, and permeability was identified, allowing the analysis of the underlying mechanism behind this phenomenon. The results show that a higher volumetric flow rate and lower permeability cause a delay in the tracer breakthrough time and an increase in the dispersion coefficient. The core experimental results show that the dispersion coefficient is negatively correlated with the permeability and positively correlated with the superficial velocity. The corresponding regression equations indicate linear relations between the dispersion coefficient, core permeability, and fluid velocity, resulting from the micron scale of grain diameters in cores. The combination of high velocity and low permeability yields a large dispersion coefficient. The effects of latitudinal dispersion in porous media cannot be ignored in low-permeability cores or formations. These findings can help to improve the understanding of tracer flow in porous media, the design of injection parameters, and the interpretation of tracer concentration distribution in inter-well tracer tests.

Quantifying Optically Derived Two-Dimensional Wave-Averaged Currents in the Surf Zone

Complex two-dimensional nearshore current patterns are generated by feedbacks between sub-aqueous morphology and momentum imparted on the water column by breaking waves, winds, and tides. These non-stationary features, such as rip currents and circulation cells, respond to changing environmental conditions and underlying morphology. However, using fixed instruments to observe nearshore currents is limiting due to the high costs and logistics necessary to achieve adequate spatial sampling resolution. A new technique for processing surf-zone imagery, WAMFlow, quantifies fluid velocities to reveal complex, multi-scale (10 s–1000 s meters) nearshore surface circulation patterns. We apply the concept of a wave-averaged movie (WAM) to measure surf-zone circulation patterns on spatial scales of kilometers in the alongshore and 100 s of meters in the cross-shore. The approach uses a rolling average of 2 Hz optical imagery, removing the dominant optical clutter of incident waves, to leave the residual foam or water turbidity features carried by the flow. These residual features are tracked as quasi-passive tracers in space and time using optical flow, which solves for u and v as a function of image intensity gradients in x, y, and t. Surf zone drifters were deployed over multiple days with varying nearshore circulations to validate the optically derived flow patterns. Root mean square error are reduced to 0.1 m per second after filtering based on image attributes. The optically derived patterns captured longshore currents, rip currents, and gyres within the surf zone. Quantifying nearshore circulation patterns using low-cost image platforms and open-source computer vision algorithms presents the potential to further our understanding of fundamental surf zone dynamics.

What do you mean by false positive

Misunderstandings regarding the term "false positive" present a significant hurdle to broad adoption of eDNA monitoring methods. Here, we identify three challenges to clear communication of false-positive error between scientists, managers, and the public. The first arises from a failure to distinguish between false-positive eDNA detection at the sample level and false-positive inference of taxa presence at the site level. The second is based on the large proportion of false positives that may occur when true-positive detections are likely to be rare, even when rates of contamination or other error are low. And the third misunderstanding occurs when conventional species detection approaches, often based on direct capture, are used to confirm eDNA approaches without acknowledging or quantifying the conventional approach's detection probability. The solutions to these issues include careful and consistent communication of error definitions, managing expectations of error rates, and providing a balanced discussion not only of alternative sources of species DNA, but also of the detection limitations of conventional methods. We argue that the benefit of addressing these misunderstandings will be increased confidence in the utility of eDNA methods and, ultimately, improved resource management using eDNA approaches. The term false positive is often misused in eDNA research and natural resource management. There are issues of scale of inference, the base rate fallacy, and confirmation errors using conventional methods of detection. We offer a perspective to guide discussions of errors in species detection.

Well-defined poly(ethylene glycol) polymers as non-conventional reactive tracers of colloidal transport in porous media

HYPOTHESIS

A prominent fraction of mobile organic matter in natural aqueous soil solutions is formed by molecules in sizes that seamlessly exceed the lower end of what is defined as a colloid. The hydrodynamics and the functional diversity of these molecules result in a transport behavior that is fundamentally different from smaller compounds. However, there is a lack of "reactive tracers" that allow for the study of colloidal transport phenomena appropriately. We hypothesize that tailor-made and well-defined synthetic polymers can overcome this limitation.

EXPERIMENTS

We prepared and characterized the hydrodynamic properties of water-soluble poly(ethylene glycol)s (PEG) and studied their adsorption to mixtures of quartz, illite, and goethite in batch and column experiments.

FINDINGS

We used this information to independently predict the transport of PEG with striking agreement to the observed mean breakthrough times in all porous media. As PEG transport can be comprehensively and quantitatively reconstructed, we conclude that functionalized PEGs are promising candidates to be used as tailorable and non-toxic tracers available in the size range of natural organic (macro-)molecules.

Nonlinear Autoregressive Neural Networks to Predict Hydraulic Fracturing Fluid Leakage into Shallow Groundwater

Hydraulic fracturing of horizontal wells is an essential technology for the exploitation of unconventional resources, but led to environmental concerns. Fracturing fluid upward migration from deep gas reservoirs along abandoned wells may pose contamination threats to shallow groundwater. This study describes the novel application of a nonlinear autoregressive (NAR) neural network to estimate fracturing fluid flow rate to shallow aquifers in the presence of an abandoned well. The NAR network is trained using the Levenberg–Marquardt (LM) and Bayesian Regularization (BR) algorithms and the results were compared to identify the optimal network architecture. For NAR-LM model, the coefficient of determination (R2) between measured and predicted values is 0.923 and the mean squared error (MSE) is 4.2 × 10−4, and the values of R2 = 0.944 and MSE = 2.4 × 10−4 were obtained for the NAR-BR model. The results indicate the robustness and compatibility of NAR-LM and NAR-BR models in predicting fracturing fluid flow rate to shallow aquifers. This study shows that NAR neural networks can be useful and hold considerable potential for assessing the groundwater impacts of unconventional gas development.