Publications

Cartwright, Keith C.; Radtke, Gregg A.; Hopkins, Polly L.; Hopkins, Matthew M.

Abstract not provided.

Jove Colon, Carlos F.; Arguello, Jose G.; Hansen, Francis D.; Martinez, Mario J.; Hopkins, Polly L.

Abstract not provided.

Cygan, Randall T.; Hopkins, Polly L.; Greathouse, Jeffery A.; Teich-McGoldrick, Stephanie T.; Martinez, Mario J.; Hansen, Francis D.; Arguello, Jose G.; Sassani, David C.; Weck, Philippe F.

Abstract not provided.

Jones, Reese E.; Shaughnessy, Michael C.; Leonard, Francois L.; Spataru, Dan C.; Beechem, Thomas E.; Yang, Chu-Yeu P.; Zhou, Xiaowang Z.; Hopkins, Polly L.; Medlin, Douglas L.; Cummings, Aron C.

Abstract not provided.

Martinez, Mario J.; Red-Horse, John R.; Carnes, Brian C.; Mesh, Mikhail M.; Field, Richard V.; Davison, Scott M.; Yoon, Hongkyu Y.; Bishop, Joseph E.; Newell, Pania N.; Notz, Patrick N.; Turner, Daniel Z.; Subia, Samuel R.; Hopkins, Polly L.; Moffat, Harry K.; Jove Colon, Carlos F.; Dewers, Thomas D.; Klise, Katherine A.

This document summarizes research performed under the SNL LDRD entitled - Computational Mechanics for Geosystems Management to Support the Energy and Natural Resources Mission. The main accomplishment was development of a foundational SNL capability for computational thermal, chemical, fluid, and solid mechanics analysis of geosystems. The code was developed within the SNL Sierra software system. This report summarizes the capabilities of the simulation code and the supporting research and development conducted under this LDRD. The main goal of this project was the development of a foundational capability for coupled thermal, hydrological, mechanical, chemical (THMC) simulation of heterogeneous geosystems utilizing massively parallel processing. To solve these complex issues, this project integrated research in numerical mathematics and algorithms for chemically reactive multiphase systems with computer science research in adaptive coupled solution control and framework architecture. This report summarizes and demonstrates the capabilities that were developed together with the supporting research underlying the models. Key accomplishments are: (1) General capability for modeling nonisothermal, multiphase, multicomponent flow in heterogeneous porous geologic materials; (2) General capability to model multiphase reactive transport of species in heterogeneous porous media; (3) Constitutive models for describing real, general geomaterials under multiphase conditions utilizing laboratory data; (4) General capability to couple nonisothermal reactive flow with geomechanics (THMC); (5) Phase behavior thermodynamics for the CO2-H2O-NaCl system. General implementation enables modeling of other fluid mixtures. Adaptive look-up tables enable thermodynamic capability to other simulators; (6) Capability for statistical modeling of heterogeneity in geologic materials; and (7) Simulator utilizes unstructured grids on parallel processing computers.

Martinez, Mario J.; Hopkins, Polly L.; Mckenna, Sean A.

Injection of CO2 into formations containing brine is proposed as a long-term sequestration solution. A significant obstacle to sequestration performance is the presence of existing wells providing a transport pathway out of the sequestration formation. To understand how heterogeneity impacts the leakage rate, we employ two dimensional models of the CO2 injection process into a sandstone aquifer with shale inclusions to examine the parameters controlling release through an existing well. This scenario is modeled as a constant-rate injection of super-critical CO2 into the existing formation where buoyancy effects, relative permeabilities, and capillary pressures are employed. Three geologic controls are considered: stratigraphic dip angle, shale inclusion size and shale fraction. In this study, we examine the impact of heterogeneity on the amount and timing of CO2 released through a leaky well. Sensitivity analysis is performed to classify how various geologic controls influence CO2 loss. A 'Design of Experiments' approach is used to identify the most important parameters and combinations of parameters to control CO2 migration while making efficient use of a limited number of computations. Results are used to construct a low-dimensional description of the transport scenario. The goal of this exploration is to develop a small set of parametric descriptors that can be generalized to similar scenarios. Results of this work will allow for estimation of the amount of CO2 that will be lost for a given scenario prior to commencing injection. Additionally, two-dimensional and three-dimensional simulations are compared to quantify the influence that surrounding geologic media has on the CO2 leakage rate.

Hughes, Thomas P.; Hopkins, Matthew M.; Boerner, Jeremiah J.; Crozier, Paul C.; Hooper, Russell H.; Hopkins, Polly L.; Musson, Lawrence M.; Williams, Alan B.

Abstract not provided.

Hopkins, Matthew M.; Hopkins, Polly L.; Hooper, Russell H.; Musson, Lawrence M.; Plimpton, Steven J.; Williams, Alan B.

Abstract not provided.

Notz, Patrick N.; Roach, R.A.; Dion, Kristin D.; Norris, J.T.; Hopkins, Polly L.; Martinez, Mario J.; Robino, Charles V.; Givler, R.C.

Abstract not provided.

Notz, Patrick N.; Dion, Kristin D.; Givler, R.C.; Hopkins, Polly L.; Norris, J.T.; Perricone, Matthew J.; Roach, R.A.; Robino, Charles V.; Tandon, Rajan T.

Abstract not provided.

Martinez, Mario J.; Hopkins, Polly L.; Reeves, Paul C.

This report describes the use of PorSalsa, a parallel-processing, finite-element-based, unstructured-grid code for the simulation of subsurface nonisothermal two-phase, two component flow through heterogeneous porous materials. PorSalsa can also model the advective-dispersive transport of any number of species. General source term and transport coefficient implementation greatly expands possible applications. Spatially heterogeneous flow and transport data are accommodated via a flexible interface. Discretization methods include both Galerkin and control volume finite element methods, with various options for weighting of nonlinear coefficients. Time integration includes both first and second-order predictor/corrector methods with automatic time step selection. Parallel processing is accomplished by domain decomposition and message passing, using MPI, enabling seamless execution on single computers, networked clusters, and massively parallel computers.

Martinez, Mario J.; Hopkins, Polly L.

Abstract not provided.