3D Variational Analysis In Subsurface Contaminant Transport Model

Modeling of contaminant transport in a subsurface environment by a numerical model deviates from the real world environment because of the highly heterogeneous nature of the subsurface environment. In this study, the data assimilation techniques are integrated with the numerical model and are applied to the subsurface environment to predict the contaminant transport. The Forward Time Center Space (FTCS) model is used as a numerical approach to solve the classical advection-dispersion-reaction transport equation and the Kalman Filter, Ensemble Kalman Filter (EnKF) and 3D Variational (3DVAR) analysis are used for data assimilation purpose. A hybrid scheme, termed as EnKF-3DVAR is developed using EnKF and 3DVAR analysis. The EnKF is a Monte Carlo based sequential data assimilation technique that divides the state vector into N number of ensembles rather than computing one state vector. The 3DVAR analysis uses the EnKF mean state vector as the background state and uses a cost function to find out an optimal estimate of that EnKF mean state vector. The simulation is run using an ensemble size of 100 members. A Root Mean Square Error (RMSE) profile is used to evaluate the prediction accuracy of the models. This study shows that state predictions are better for both the EnKF and EnKF- 3DVAR when compared to those of the numerical and KF solutions

3D Variational Analysis In Subsurface Contaminant Transport Model

Modeling of contaminant transport in a subsurface environment by a numerical model deviates from the real world environment because of the highly heterogeneous nature of the subsurface environment. In this study, the data assimilation techniques are integrated with the numerical model and are applied to the subsurface environment to predict the contaminant transport. The Forward Time Center Space (FTCS) model is used as a numerical approach to solve the classical advection-dispersion-reaction transport equation and the Kalman Filter, Ensemble Kalman Filter (EnKF) and 3D Variational (3DVAR) analysis are used for data assimilation purpose. A hybrid scheme, termed as EnKF-3DVAR is developed using EnKF and 3DVAR analysis. The EnKF is a Monte Carlo based sequential data assimilation technique that divides the state vector into N number of ensembles rather than computing one state vector. The 3DVAR analysis uses the EnKF mean state vector as the background state and uses a cost function to find out an optimal estimate of that EnKF mean state vector. The simulation is run using an ensemble size of 100 members. A Root Mean Square Error (RMSE) profile is used to evaluate the prediction accuracy of the models. This study shows that state predictions are better for both the EnKF and EnKF- 3DVAR when compared to those of the numerical and KF solutions

Use of groundwater lifetime expectancy for the performance assessment of a deep geologic waste repository: 1. Theory, illustrations, and implications

Long-term solutions for the disposal of toxic wastes usually involve isolation of the wastes in a deep subsurface geologic environment. In the case of spent nuclear fuel, if radionuclide leakage occurs from the engineered barrier, the geological medium represents the ultimate barrier that is relied upon to ensure safety. Consequently, an evaluation of radionuclide travel times from a repository to the biosphere is critically important in a performance assessment analysis. In this study, we develop a travel time framework based on the concept of groundwater lifetime expectancy as a safety indicator. Lifetime expectancy characterizes the time that radionuclides will spend in the subsurface after their release from the repository and prior to discharging into the biosphere. The probability density function of lifetime expectancy is computed throughout the host rock by solving the backward-in-time solute transport adjoint equation subject to a properly posed set of boundary conditions. It can then be used to define optimal repository locations. The risk associated with selected sites can be evaluated by simulating an appropriate contaminant release history. The utility of the method is illustrated by means of analytical and numerical examples, which focus on the effect of fracture networks on the uncertainty of evaluated lifetime expectancy.Comment: 11 pages, 8 figures; Water Resources Research, Vol. 44, 200

Application of coupled-wave Wentzel-Kramers-Brillouin approximation to ground penetrating radar

This paper deals with bistatic subsurface probing of a horizontally layered dielectric half-space by means of ultra-wideband electromagnetic waves. In particular, the main objective of this work is to present a new method for the solution of the two-dimensional back-scattering problem arising when a pulsed electromagnetic signal impinges on a non-uniform dielectric half-space; this scenario is of interest for ground penetrating radar (GPR) applications. For the analytical description of the signal generated by the interaction of the emitted pulse with the environment, we developed and implemented a novel time-domain version of the coupled-wave Wentzel-Kramers-Brillouin approximation. We compared our solution with finite-difference time-domain (FDTD) results, achieving a very good agreement. We then applied the proposed technique to two case studies: in particular, our method was employed for the post-processing of experimental radargrams collected on Lake Chebarkul, in Russia, and for the simulation of GPR probing of the Moon surface, to detect smooth gradients of the dielectric permittivity in lunar regolith. The main conclusions resulting from our study are that our semi-analytical method is accurate, radically accelerates calculations compared to simpler mathematical formulations with a mostly numerical nature (such as the FDTD technique), and can be effectively used to aid the interpretation of GPR data. The method is capable to correctly predict the protracted return signals originated by smooth transition layers of the subsurface dielectric medium. The accuracy and numerical efficiency of our computational approach make promising its further development

The WISDOM Radar: Unveiling the Subsurface Beneath the ExoMars Rover and Identifying the Best Locations for Drilling

The search for evidence of past or present life on Mars is the principal objective of the 2020 ESA-Roscosmos ExoMars Rover mission. If such evidence is to be found anywhere, it will most likely be in the subsurface, where organic molecules are shielded from the destructive effects of ionizing radiation and atmospheric oxidants. For this reason, the ExoMars Rover mission has been optimized to investigate the subsurface to identify, understand, and sample those locations where conditions for the preservation of evidence of past life are most likely to be found. The Water Ice Subsurface Deposit Observation on Mars (WISDOM) ground-penetrating radar has been designed to provide information about the nature of the shallow subsurface over depth ranging from 3 to 10 m (with a vertical resolution of up to 3 cm), depending on the dielectric properties of the regolith. This depth range is critical to understanding the geologic evolution stratigraphy and distribution and state of subsurface H2O, which provide important clues in the search for life and the identification of optimal drilling sites for investigation and sampling by the Rover's 2-m drill. WISDOM will help ensure the safety and success of drilling operations by identification of potential hazards that might interfere with retrieval of subsurface samples

Parsimonious numerical modelling of deep geothermal reservoirs

Numerical modelling has been undertaken to help improve understanding of a deep geothermal system being considered for development in the vicinity of Eastgate (Weardale, County Durham, UK). A parsimonious numerical modelling approach is used, which allows the possibility to develop a workable formal framework, rigorously testing evolving concepts against data as they become available. The approach used and results presented in this study are valuable as a contribution to a wider understanding of deep geothermal systems. This modelling approach is novel in that it utilises the mass transport code MT3DMS as a surrogate representation for heat transport in mid-enthalpy geothermal systems. A three-dimensional heat transport model was built, based on a relatively simple conceptual model. Results of simulation runs of a geothermal production scenario have positive implications for a working geothermal system at Eastgate. The Eastgate Geothermal Field has significant exploitation potential for combined heat and power purposes; it is anticipated that this site could support several tens of megawatts of heat production for direct use and many megawatts of electrical power using a binary power plant