Prediction of some in situ tracer tests with sorbing tracers using independent data

https://doi.org/10.1016/S0169-7722(02)00123-7Get rights and content

Abstract

Some recent converging tracer tests with sorbing tracers at the Äspö Hard Rock Laboratory in Sweden, the TRUE tests, have been predicted using only laboratory data and hydraulic data from borehole measurements. No model parameters were adjusted to obtain a better fit with the experiments. The independent data were fracture frequency and transmissivity data obtained in the field and laboratory data on sorption and matrix diffusion.

Transmissivity measurements in five boreholes in the rock volume containing the region surrounding the injection and collection points show that there is a high frequency of water conducting fractures. Of 162 packed off sections with 0.5 m packer distances, 112 were found to have a transmissivity above the detection limit. The specific flow-wetted surface (FWS) of the rock mass could be estimated from these data. The transmissivities were found to be reasonably well described by a lognormal distribution. Laboratory data on diffusion and sorption properties together with the hydraulic data were used to “predict” the residence time distribution (RTD) of the sorbing tracers. The results were compared with the experimental breakthrough curves.

In these experiments, the water residence time is very small compared to the residence time of the sorbing tracers due to their diffusion and sorption within the rock matrix. We thus could neglect the influence of the water residence time in our predictions. Therefore, no information on water residence times or on “dispersion” was needed. The dispersion of the sorbing tracers is caused by the different sorbing tracer residence times in different pathways. The sorbing tracer residence time is determined by the ratio of flowrate to the flow-wetted surface in the different pathways and not by the water residence time.

Assuming a three-dimensional flow pattern and using the observed fracture frequency and flowrate distribution, breakthrough curves for three strongly sorbing tracers were predicted. Only the laboratory data, the transmissivity measurements and the pumping flowrate were used in the predictions. No information on the water residence time as obtained by the nonsorbing tracers was used. The predictions were surprisingly accurate.

Section snippets

Introduction and background

In many instances, we wish to predict the migration behaviour of solutes over times and distances longer than what can be measured by experiments. A robust method that is based on the most important processes and mechanisms would then be useful. Such a method would have to rely on independently measured data on rock properties and on the solute interaction mechanisms.

Many different processes and mechanisms influence transport of solutes with the flowing water in fractured rocks. The

Model concepts

The flow is conceived as taking place in a three-dimensional network of channels that intersect at irregular intervals. At the intersections, the waters mix and then redistribute to those channels that carry the water from the intersection to the next. Each channel has a volume and a flow-wetted surface (FWS). The FWS is the surface over which a sorbing solute must pass in order to enter into the micropores of the rock. The magnitude of the FWS that the water flow “sees” is obviously one key

The Äspö TRUE experiments

Converging flow tracer tests were performed in water-saturated, fractured crystalline rock. The distance from injection points to pumping point was about 5 m. The injection flowrate was about 600 times smaller than the pumping flowrate. Sorbing, as well as nonsorbing tracers, were injected as a mixture. Extensive hydraulic tests were performed in the fracture and also in the surrounding rock mass. Laboratory measurements were made to determine matrix diffusion, porosities and sorption

Data used

Matrix diffusion coefficients and porosities were obtained from laboratory measurement reported in Byegård et al. (1998). Sorption data were taken from the same source but were reevaluated for the sorbing tracers to account for the experiments that were performed over only 2 weeks and equilibrium was not reached during this time. The method is described in Neretnieks (2002).

Transmissivity data for the rock mass surrounding the experimental region were taken from the Sicada database. One hundred

Simulations of the sorbing tracer tests

Consider a spherical volume of rock into which water flows from the surface of the rock towards its centre. This is depicted in Fig. 1. In the sphere, there is a multitude of fractures. The number of fractures is obtained from the fracture frequency observed in the boreholes surrounding the experimental site. The water collected in the pumping section in the centre of the sphere has flown through the three-dimensional network of fractures in the rock.

For any tracer injection point at a given

Sensitivity analysis

The two main parameters that influence the residence time distribution of the sorbing tracers in our model are one group that contains the FWS, sorption and diffusion data, and one parameter that pertains to the variability of the flowrates in the channels. We chose the most strongly sorbing tracer, Cs, for the sensitivity analysis. The group of parameters that governs the matrix diffusion effects in the model isGq=LWqεpDpRwhereR=1+1−εpεpKdρL and W are the length and width of the channels,

Discussion and conclusions

An attempt was made to predict the RTDs for some strongly sorbing tracers in a fractured crystalline rock. A three-dimensional channel network model with essentially only the following two processes that influence the RTD was used. Matrix diffusion from the water flowing in the channels over the FWS is the interaction mechanism between solute and rock, and a random variation of flowrates in the different channels gives the influence of the variations in flowrates.

Laboratory data and hydraulic

Acknowledgements

The Swedish Nuclear Fuel and Waste Management Company, SKB, has supported this work.

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