Nuclear Magnetic Resonance Imaging of Groundwater Flow within Centimeter-Scale Macroporosity of the Biscayne Aquifer of Southeast Florida

In this study, we use an innovative, non-invasive technology, nuclear magnetic resonance imaging (NMRI), to visualize the direction and magnitude of ground water flow in field samples of late Pleistocene limestone of the Biscayne aquifer. One set of NMRI experiments investigates the migration of freshwater into the matrix of permeable (gas minipermeameter mean 10^-13.5 m² on four samples) and porous (mean of 44%, on four samples) peloid-oöid grainstone initially saturated with heavy-water (D₂O). In a second set of experiments, the focus of this abstract, we use phase-encoded, stimulated-echo imaging to map the advective velocity of water flowing at two rates of specific discharge (0.025 and 0.013 cm/s) through a 10-cm diameter cylindrical, epoxy-resin model. The model interior accurately reproduces a well-connected maze of ichnologically influenced, centimeter-scale, touching-vug macroporosity common within preferred flow zones in parts of the Biscayne aquifer.

Results of the velocity experiments at both values of specific discharge reveal select macropores with concentrated flow. The average axial components of velocity (0.016 cm/s and 0.04 cm/s) are in the range of advective flow expected in the Biscayne aquifer. Maximum Reynolds number (Re) values in the low and high specific discharge experiments are 15 and 30, respectively. Average values of Re are much lower, ranging between 1 and 6. These low Re values indicate laminar flow conditions in the model. Two further observations point to laminar flow conditions: 1) virtually all values of the axial component of velocity are positive, there are no eddies; and 2) the axial component of the velocity field is proportional between the two values of specific discharge. Exponential functions fit the distributions of the axial velocity. Distributions of the transverse component of velocity are symmetric and appear to fit a Cauchy rather than a Gaussian function.