Three papers are presented, applying computational fluid dynamics methods to fluid flows in the geosciences. In the first paper, a numerical method is developed for single phase potential flow in the subsurface. For a class of monotonically advancing flows, the method provides a computational savings as compared to classical methods and can be applied to problems such as forced groundwater recharge. The second paper investigates the shear stress reducing action of an erosion control roughness array. Incompressible Naiver-Stokes simulations are performed for multiple wind angles to understand the changing aerodynamics of individual and grouped roughness elements. In the third paper, a 1D analytical flow model is compared with multiphase Navier-Stokes simulations in a parabolic fissure. Sampling the numerical results allows the isolation of flow factors such as surface tension, which are difficult to measure in physical experiments.

Reservoir characterization is one of the most important problems in petroleum engineering. It involves forward reservoir modeling that predicts the fluid behavior in the reservoir and inverse problem that calibrates created reservoir models with given data. In this dissertation, we focus on two problems in the field of reservoir characterization: depth of investigation in heterogeneous reservoirs, and history matching and uncertainty quantification of channelized reservoirs. The concept of depth of investigation is fundamental to well test analysis. Much of the current well test analysis relies on analytical solutions based on homogeneous or layered reservoirs. However, such analytic solutions are severely limited for heterogeneous and fractured reservoirs, particularly for unconventional reservoirs with multistage hydraulic fractures. We first generalize the concept to heterogeneous reservoirs and provide an efficient tool to calculate drainage volume using fast marching methods and estimate pressure depletion based on geometric pressure approximation. The applicability of proposed method is illustrated using two applications in unconventional reservoirs including flow regime visualization and stimulated reservoir volume estimation. Due to high permeability contrast and non-Gaussianity of channelized permeability field, it is difficult to history match and quantify uncertainty of channelized reservoirs using traditional approaches. We treat facies boundaries as level set functions and solve the moving boundary problem (history matching) with the level set equation. In addition to level set methods, we also exploit the problem using pixel based approach. The reversible jump Markov Chain Monte Carlo approach is utilized to search the parameter space with flexible dimensions. Both proposed approaches are demonstrated with two and three dimensional examples.

Extracting surfaces, representing boundaries of objects of interest, from volumetric images, has important applications in various scientific domains, from medicine to geology. In this thesis, I introduce novel mathematical, computational, and algorithmic machinery for extraction of sheet-like surfaces (with boundary), whose boundary is unknown a-priori, a particularly important case in applications that has no convenient methods. This case of a surface with boundaries has applications in extracting faults (among other geological structures) from seismic images in geological applications. Another application domain is in the extraction of structures in the lung from computed tomography (CT) images. Although many methods have been developed in computer vision for extraction of surfaces, including level sets, convex optimization approaches, and graph cut methods, none of these methods appear to be applicable to the case of surfaces with boundary. The novel methods for surface extraction, derived in this thesis, are built on the theory of Minimal Paths, which has been used primarily to extract curves in noisy or corrupted images and have had wide applicability in 2D computer vision. This thesis extends such methods to surfaces, and it is based on novel observations that surfaces can be determined by extracting topological structures from the solution of the eikonal partial differential equation (PDE), which is the basis of Minimal Path theory. Although topological structures are known to be difficult to extract from images, which are both noisy and discrete, this thesis builds robust methods based on Morse theory and computational topology to address such issues. The algorithms have run-time complexity O(NlogN), less complex than existing approaches. The thesis details the algorithms, theory, and shows an extensive experimental evaluation on seismic images and medical images. Experiments show out-performance in accuracy, computational speed, and user convenience compared with related state-of-the-art methods. Lastly, the thesis shows the methodology developed for the particular case of surfaces with boundary extends to surfaces without boundary and also surfaces with different topologies, such as cylindrical surfaces, both important cases for many applications in medical image analysis.

The performance prediction of solid propellant rocket motor depends on the calculation of internal aerodynamics of the motor through its operational life. In order to obtain the control volume, in which the solutions will be carried out, a process called &ldquo / grain burnback calculation&rdquo / is required. During the operation of the motor, as the interface between the solid and gas phases moves towards the solid propellant in a direction normal to the surface, the combustion products are generated and added into the control volume. This phenomenon requires handling of moving boundaries as the solution proceeds. In this thesis, Fast Marching Method is implemented to the problem of grain burnback. This method uses the upwinding nature of the propellant interface motion and solves the Eikonal type equations on a fixed three-dimensional tetrahedron mesh. The control volume is coupled to a one-dimensional and a three-dimensional Euler aerodynamic solver in order to obtain the performance of the engine. The speed by which the interface moves depends on the static pressure on the surface of the propellant and comes from the solver. Therefore an iterative method has been proposed between the interface capturing algorithms and the flow solver. Both of the calculation results, which are obtained from one-dimensional and three-dimensional solvers are compared with actual rocket firing data and validated.