Current Funded Projects

BIGDATA: Collaborative Research: IA: F: Fractured Subsurface Characterization Using High Performance Computing & Guided by Big Data (Funded by NSF)

Natural fractures act as major heterogeneity in the subsurface that control flow and transport of subsurface fluids and chemical species. Their importance cannot be underestimated, because their transmissivity may result in undesired migration during geologic sequestration of CO2, they strongly control heat recovery from geothermal reservoirs, and they may lead to induced seismicity due to fluid injection into the subsurface. Advanced computational methods are critical to design subsurface processes in fractured media for successful environmental and energy applications. This project will address the following key BIG data and computer science challenges: (1) Computation of seismic wave propagation in fractured media; (2) BIG data analytics for inferring fracture characteristics; (3) High Performance Computation of flow and transport in fractured media; and (4) Integration of data from disparate sources for risk assessment and decision-making. Successful completion of tasks addressing these challenges will enable design of technologies for addressing key societal issues such as safe energy extraction from the surface, long-term sequestration of large volumes of greenhouse gases and safe storage of nuclear waste in the subsurface. The project will provide interdisciplinary training for a team of graduate students and postdoctoral fellows. Outreach to high schools teachers and minorities through a planned workshop will inspire interest in environmental green-engineering, mathematics, and computational science. Numerous applications will benefit from the proposed research, including Computer and Information Science and Engineering (CISE), Geosciences (GEO), and Mathematical and Physical Sciences (MPS).

The proposed research will emphasize high performance computation (HPC) approaches for characterizing fractures using large subsurface seismic data sets, BIG data analytics for extraction of fracture related information from seismic inversion results and long-duration dynamic data, and advanced computational approaches for modeling flow, transport, and geomechanics in fractured subsurface systems. The specific objectives are to:

  • Develop an efficient forward modeling algorithm for seismic wave propagation in fractured media using efficient computational schemes implemented on graphics processor units (GPUs).
  • Compute flow and transport in fractured media using an efficient computational scheme implemented on GPUs such as mimetic finite differences.
  • Perform efficient multiphysics simulation of flow and geomechanics in fractured media.
  • Integrate information from time-lapse seismic inversion and flow/transport simulation using novel statistical schemes.
  • Joint inversion of seismic and fluid flow data and uncertainty quantification using efficient computational schemes.
  • Develop and deploy a scalable hybrid-staging based substrate that can support targeted workflows using staging-based in-situ/in-transit approaches.

Computational Models for Evaluating Long Term CO2 Storage in Saline Aquifers (funded by NSF and KAUST through the Academic Excellence Alliance Program)

Geologic sequestration is a proven means of permanent CO2 greenhouse gas storage, but it is difficult to design and manage such efforts. Predictive computational simulation may be the only means to account for the lack of complete characterization of the subsurface environment, the multiple scales of the various interacting processes, the large areal extent of saline aquifers, and the need for long time predictions. This proposal will investigate high fidelity multiscale and multiphysics algorithms necessary for simulation of multiphase flow and transport coupled with geochemical reactions and related mineralogy, and geomechanical deformation in porous media to predict changes in rock properties during sequestration. The work will result in a prototypical computational framework with advanced numerical algorithms and underlying technology for research in CO2 applications, which has been validated and verified against field-scale experimental tests. The multidisciplinary research team has expertise in (1) applied mathematics and computational science, (2) computer science and engineering, (3) compositional modeling and CO2 injection processes, and (4) CO2 demonstration sites. In each of the third and fourth years of the project, we will host a two-day workshop for high school teachers, advanced high school students, and undergraduate students with an interest in high school teaching. We will provide training in the use of a sophisticated groundwater simulator, to be used as a tool to engage and pique the interest of high schoolers, perhaps leading some to careers in mathematics, the sciences, and interdisciplinary work. In addition, two postdoctoral students and roughly two graduate students will be supported throughout the project.

Center for Frontiers of Subsurface Energy Security (funded by DOE)

Currently mankind extracts most of the fuel for the global economy from underground. The byproducts of consuming this fuel enter the atmosphere or remain on the surface. This situation is no longer tenable. A critical step toward future energy systems will be the ability to cycle fuel byproducts back to their original home: the Earth’s subsurface. Applications of this concept include storing CO2 in deep geologic formations and securing radioactive materials in appropriately engineered repositories. Our goal is to fill gaps in the knowledge base so that subsurface storage schemes are reliable from the moment they open. Two scientific Grand Challenges, which will be investigated in this project, contribute to the gap between forecast and outcome in geologic systems. First, byproduct storage schemes will operate in a far-from-equilibrium state. Second, it is difficult to explain the emergence of patterns and other manifestations of correlated phenomena across length and time scales.

Collaborative Research: Error Estimation, Data Assimilation and Uncertainty Quantification for Multiphysics and Multiscale Processes in Geological Media (funded by NSF)

The application of high performance computing to model subsurface processes occurring over multiple spatial and temporal scales is a science grand challenge that has important implications to society at large. Research on this grand challenge is at the confluence of advanced mathematics, computer science, fluid and solid mechanics and applied probability and statistics. We propose a fresh new perspective by investigating and formulating rigorous error estimators for the numerical schemes employed to model multiphysics, multiscale processes in subsurface media. These error estimators when coupled with advanced computational methods can significantly speed up the task of uncertainty assessment and feedback control of subsurface processes. We also propose to develop a uncertainty quantification scheme that will utilize the error estimators and rigorous quantification of prior geologic uncertainty. Underlying the computational and uncertainty quantification schemes will be a computer framework that rigorously takes into account the dynamic and complex communication and coordination patterns resulting from multiphysics, multinumerics, multiscale and multidomain couplings. In addition, we will investigate realistic physical models such a carbon sequestration in saline aquifers with real field data from the Cranfield Mississippi demonstration site.The project will result in a prototypical computational framework with advanced numerical algorithms and underlying technology for research in CO2 applications, which has been validated and verified against field-scale experimental tests. The multidisciplinary research team has expertise in (1) applied mathematics and computational science, (2) solid and fluid mechanics, (3) computer science and engineering, (4) parameter estimation and uncertainty quantification, and (5) analysis of field data.This project will support the education of an interdisciplinary work force effective in merging computation and experimental results. The ultimate transformative goal is to achieve predictive and decisional simulations, in which engineers reliably predict, control, and manage human interaction with geosystems.

Multiscale Modeling and Simulation of Multiphase Flow Coupled with Geomechanics (funded by DOE)

This is a proposal to develop algorithms that will enable scientists and engineers to readily model complex flow processes in porous media taking into account the accompanying deformations of the porous solids. Fluid motion and solid deformation are inherently coupled, but current major commercial packages for multiphase flow in porous media only model porous flow while solid deformation is normally integrated into a study in an ad hoc manner or must be included through complex iterations between one software package that models fluid flow and a separate package that models solid deformations. There are numerous field applications that would benefit from a better understanding and integration of porous flow and solid deformation. Important applications in the geosciences include enivronmental cleanup, petroleum production, solid waste disposal, and carbon sequestration, while similar issues arise in the biosciences and chemical sciences as well. Examples of field applications include surface subsidence, pore collapse, cavity generation, hydraulic fracturing, thermal fracturing, wellbore collapse, sand production, fault activation, and disposal of drill cuttings. The above phenomena entail both economic as well as environmental concerns. For example, surface subsidence related to both consolidation of surface layers and fluid withdrawals from oil and gas reservoirs have had a significant impact in the greater Houston area over the last century and have resulted in destruction to infrastructure, buildings and private homes. Subsidence caused by oil and gas production also has been an issue of substantial economic importance in the North Sea oil fields. In some cases multi-billion dollar adjustments have been required to production platforms due to the response to unexpected subsidence of the sea floor driven by oil production.Another important related class of problems involves CO2 sequestration, which is proposed as a key strategy for mitigating climate change driven by high levels of anthropogenic CO2 being added to the atmosphere. In a CO2 sequestration project, fluid is injected into a deep subsurface reservoir (rather than being produced or extracted), so that inflation of the reservoir leads to uplift displacement of the overlying surface. As long as a CO2 sequestration site is removed from faults, this uplift is several centimeters, while its wavelength is in tens of kilometers, so that the uplift poses little danger to buildings and infrastructure. Nevertheless the uplift displacements are of great interest for non-intrusive monitoring of CO2 sequestration. Indeed, uplift can be measured with a sub-millimeter precision using Interferometric Synthetic Aperture Radar (InSAR) technology. [166] The feasibility of this approach has been established by measuring the uplift displacements over the first commercial scale CO2 sequestration project conducted by BP in Salah Algeria. [166, 150] In contrast, intrusive monitoring via drill holes bored into the reservoir is expensive, with costs of several million dollars per well. Furthermore, such wells are the most likely pathway for future leakage of sequestered CO2 back into the atmosphere. Of course, if a CO2 sequestration site is close to a fault, one should be concerned about triggering instability leading to large surface displacements that may result in significant losses.