Jie Bao

Evaluating the impact of aquifer layer properties on geomechanical response during CO2 geological sequestration

Numerical models play an essential role in understanding the facts of carbon dioxide (CO2) geological sequestration in the life cycle of a storage reservoir. We present a series of test cases that reflect a broad and realistic range of aquifer reservoir properties to systematically evaluate and compare the impacts on the geomechanical response to CO2 injection. In this study, a coupled hydro-mechanical model was applied to simulate the sequestration process, and a quasi-Monte Carlo sampling method was employed to efficiently sample the value of aquifer properties and geometry parameters. Through quantitative sensitivity analysis, the impacts of all the input parameters are ranked. Aquifer permeability was found to be of significant importance to the geomechanical response to the injection. To study the influence of uncertainty of the permeability distribution in the aquifer, an additional series of tests is presented, based on a default permeability distribution site sample with various distribution deviations generated by the Monte Carlo sampling method. The results of the test series show that the uncertainty of permeability distributions significantly affect the displacement and possible failure zone.

Smoothed particle hydrodynamics continuous boundary force method for Navier-Stokes equations subject to a Robin boundary condition

A Robin boundary condition for the Navier-Stokes equations is used to model slip conditions at the fluid-solid boundaries. A novel continuous boundary force (CBF) method is proposed for solving the Navier-Stokes equations subject to the Robin boundary condition. In the CBF method, the Robin boundary condition is replaced by the homogeneous Neumann boundary condition and a volumetric force term added to the momentum conservation equation.Smoothed particle hydrodynamics (SPH) method is used to solve the resulting Navier-Stokes equations. We present solutions for two- and three-dimensional flows subject to various forms of the Robin boundary condition in domains bounded by flat and curved boundaries. The numerical accuracy and convergence are examined through comparison of the SPH-CBF results with the solutions of finite difference or finite-element method. Considering the no-slip boundary condition as a special case of the slip boundary condition, we demonstrate that the SPH-CBF method accurately describes both the no-slip and slip conditions.

Soil moisture estimation using tomographic ground penetrating radar in a MCMC–Bayesian framework

AbstractIn this study, we focus on a hydrogeological inverse problem specifically targeting monitoring soil moisture variations using tomographic ground penetrating radar (GPR) travel time data. Technical challenges exist in the inversion of GPR tomographic data for handling non-uniqueness, nonlinearity and high-dimensionality of unknowns. We have developed a new method for estimating soil moisture fields from crosshole GPR data. It uses a pilot-point method to provide a low-dimensional representation of the relative dielectric permittivity field of the soil, which is the primary object of inference: the field can be converted to soil moisture using a petrophysical model. We integrate a multi-chain Markov chain Monte Carlo (MCMC)–Bayesian inversion framework with the pilot point concept, a curved-ray GPR travel time model, and a sequential Gaussian simulation algorithm, for estimating the dielectric permittivity at pilot point locations distributed within the tomogram, as well as the corresponding geostatistical parameters (i.e., spatial correlation range). We infer the dielectric permittivity as a probability density function, thus capturing the uncertainty in the inference. The multi-chain MCMC enables addressing high-dimensional inverse problems as required in the inversion setup. The method is scalable in terms of number of chains and processors, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. The proposed inversion approach can successfully approximate the posterior density distributions of the pilot points, and capture the true values. The computational efficiency, accuracy, and convergence behaviors of the inversion approach were also systematically evaluated, by comparing the inversion results obtained with different levels of noises in the observations, increased observational data, as well as increased number of pilot points.n