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Professor Azevedo is passionate about solving problems that include environmental, technical, economic, and policy issues, where traditional engineering approaches play an important role but cannot provide a complete answer. In particular, she is interested in assessing how energy systems are likely to evolve, which requires comprehensive knowledge of the technologies that can address future energy needs and the decision-making process followed by various agents in the economy.
Dr. Battiato's research and scholarly interests include energy and environment (battery systems; superhydrophobicity and drag reduction; carbon sequestration); multiscale, mesoscale and hybrid simulations (multiphase and reactive transport processes); effective medium theories; perturbation methods, homogenization and upscaling.
Sally Benson (Leave of Absence at OSTP)
Director, Precourt Institute for Energy and Professor of Energy Resources Engineering and Senior Fellow at the Precourt Institute for Energy
Dr. Benson is the co-director of Stanford's Precourt Institute for Energy and the director of the Global Climate and Energy Project (GCEP). A Professor in the Department of Energy Resources Engineering in the School of Earth, Energy & Environmental Sciences, she studies technologies and pathways to reducing greenhouse gas emissions. A ground water hydrologist and reservoir engineer, Benson has conducted research to address a range of issues related to energy and the environment. Her research interests include geologic storage of CO2 in deep underground formations, technologies and energy systems for a low-carbon future, and geotechnical instrumentation for subsurface characterization and monitoring.
Dr. Brandt is an Associate Professor in the Department of Energy Resources Engineering, Stanford University. His research focuses on reducing the greenhouse gas impacts of energy production and consumption, with a focus on fossil energy systems. Research interests include life cycle assessment of petroleum production and natural gas extraction. A particular interest is in unconventional fossil fuel resources such as oil sands, oil shale and hydraulically fractured oil and gas resources. He also researches computational optimization of emissions mitigation technologies, such as carbon dioxide capture systems. Dr. Brandt received his PhD from the Energy and Resources Group, UC Berkeley.
Otto N. Miller Professor in Earth Sciences
Dr. Durlofsky co-directs the Stanford Smart Fields Consortium and the Reservoir Simulation Research industrial affiliates programs. His research involves a range of topics related to modeling, history matching, and optimizing subsurface flow processes, particularly oil and gas production and geological carbon storage operations. These optimization problems may entail, for example, the determination of the optimal number, type and placement of wells, along with their operational settings. Dr. Durlofsky’s research group treats optimization and history-matching both separately and in combination (in the latter case it is a “closed-loop”problem). These applications typically require large numbers of flow simulations, and this can result in extreme computational demands. The group’s current work is addressing this issue through the development of very fast deep-learning-based and reduced-order “surrogate” models, which can be used to replace many of the full-order numerical simulations. Recent work along these lines includes the development of POD-TPWL reduced-order numerical models, and the E2C deep-learning-based surrogate model. Related work entails the development of geological-parameterization techniques suitable for use in history matching (most recently CNN-PCA. Additional areas of interest include data-space inversion for predicting flow behavior based only on prior-model simulations and observed data (posterior/history-matched models are not constructed), multifidelity methods for uncertainty quantification, and modeling and upscaling of flow in fractured reservoirs. Dr. Durlofsky is also active in the area of energy systems optimization, where the goal may be, for example, to determine the optimal design and operation of integrated fossil-renewable electricity generation facilities.
Thomas Davies Barrow Professor in the School of Earth, Energy & Environmental Sciences and Senior Fellow at the Precourt Institute for Energy
Prof. Horne's research focuses on the matching of models to various classes of reservoir responses. These "inverse problems" seek the values of unknown reservoir parameters by inference rather than direct measurement, often with the use of machine learning approaches. Typical problems are: tracer analysis of fractures, computer-aided well test analysis, production schedule optimization, and data analytics of long-term production records. In addition to this general class of problem, Prof. Horne has a specific interest in geothermal reservoir engineering, and the multiphase flow of fluids through porous materials and fractures. Research groups in which he is active include: Stanford Geothermal Program, SUPRI-D, SUPRI-Tides and Smartfields.
Keleen and Carlton Beal Professor of Petroleum Engineering and Senior Fellow at the Precourt Institute for Energy
Prof. Kovscek and his research team study recovery of unconventional hydrocarbon resources in combination with methods for mitigating carbon emissions from fossil fuels including geological sequestration of greenhouse gases. They use advanced imaging and microscopy techniques to examine coupled transport, chemical, and physical processes in porous media from the nanometer to the meter scale with the aim of applying mechanistic understanding to reduce negative impacts. Physical observations, obtained mainly from laboratory and field measurements, are interwoven with theory. Prof. Kovscek leads the Center for Mechanistic Control of Unconventional Formations (CMC-UF), directs the Enhanced Recovery affiliates program (SUPRI-A), and codirects the Center for Carbon Storage (SCCS).
Professor (Research) of Energy Resources Engineering and, by courtesy, of Geophysics, and Geological Sciences
The focus of Dr. Mukerji’s multi-disciplinary research, with students and colleagues, has been on integrating rock physics, spatial data science and wave propagation physics, and their broad applications in reservoir characterization, stochastic geomodeling, subsurface uncertainty quantification, and time-lapse seismic monitoring. He uses theoretical, computational, and machine learning methods, to discover and understand fundamental relations between geophysical data and reservoir properties, to quantify uncertainty in subsurface models, and to address value of information for decision making under uncertainty. He co-directs the Stanford Center for Earth Resources Forecasting (SCERF), the Stanford Rock Physics and Borehole Geophysics (SRB) and Stanford Basin and Petroleum System Modeling (BPSM) research groups.
Dr. Onori's research and interests include Modeling, control and optimization of dynamic systems; Model-based control in advanced propulsion systems; Energy management control and optimization in HEVs and PHEVs; Energy storage systems- Li-ion and PbA batteries, Supercapacitors; Battery aging modeling, state of health estimation and life prediction for control; and Damage degradation modeling in interconnected systems.
Dr. Tartakovsky's research and interests include:
Environmental fluid mechanics - subsurface flow and contaminant transport, multiphase flow, groundwater hydrology, reservoir simulations, well hydraulics, surface-water/groundwater interactions, inverse modeling, subsurface imaging, decisions under uncertainty, geothermal energy.
Applied and computational mathematics - Mathematical modeling of complex systems (electrochemistry for energy storage, design of nano-porous materials), uncertainty quantification, probabilistic risk assessment, stochastic partial differential equations, hybrid numerical algorithms, spatial statistics, data assimilation.
Biomedical modeling - Blood flow, microcirculation, intracellular and intercellular transport, bioinformatics, computational cell biology, hemodynamics, chemotaxis.
Department Chair, Professor
Dr. Tchelepi is interested in numerical simulation of flow and transport processes in natural porous media. Application areas include reservoir simulation and subsurface CO2 sequestration. Current research activities include (1) modeling unstable miscible and immiscible flow in heterogeneous formations, (2) developing multiscale formulations and scalable solution algorithms for multiphase flow in large-scale subsurface systems, and (3) developing stochastic formulations for quantification of the uncertainty associated with predictions of flow and transport in large subsurface formations.
Active Emeritus Faculty
Otto N. Miller Professor in the School of Earth, Energy & Environmental Sciences, Professor Emeritus
The overall goal of Dr. Aziz's research is the development of robust and reliable models for predicting performance of hydrocarbon reservoirs (including shale oil and gas) and CO2 sequestration operations. Over the years he has been involved with the development of four different industrial consortia dealing with different aspects of this problem. The first was on reservoir simulation (SUPRI-B), the second on data integration (SCRF), the third on advanced wells (SUPRI-HW), and the most recent one on Smart Fields (SFC). Underlying his research is the desire to understand mechanisms involved during the flow of complex mixtures in porous rocks and in pipes, and efficient modeling of these processes on computers. While he is no longer directly involved with SCERF and we have merged SUPRI-HW with other programs, he co-directs the other two consortia. All are highly successful and have led to a number of developments and innovations that have found important applications in industry.
Senior Associate Dean for Educational Affairs, Professor of ERE, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Civil and Environmental Engineering, Professor Emerita
Dr. Gerritsen's interests are in computational mathematics and fluid dynamics. A large part of her work is on understanding and simulating complicated fluid flow problems, for example thermal processes in the subsurface. She is also active in numerical analysis, mostly in the design of stable and accurate numerical PDE solvers, and increasingly in data science. In her most recent large project, Margot and collaborators use computational tools and data science approaches to study wildland fires and wildland fire mitigation. Margot teaches courses in both energy related topics (reservoir simulation, energy, and the environment) in the Energy Resources Engineering Department and computational mathematics, including data science, through the Institute for Computational and Mathematical Engineering (ICME). She is the co-founder and director of the global Women in Data Science conference, podcast and outreach program (widsconference.org).
Keleen and Carlton Beal Professor in Petroleum Engineering, Professor Emeritus
Dr. Orr and his students work to understand the physical mechanisms that control flow of multiphase, multicomponent fluids in the subsurface, using a combination of experiments and theory. The theory part includes numerical simulation of flow in heterogeneous porous rocks and coal beds, often using streamline approaches, and it also involves solving by analytical methods the differential equations that describe the interactions of complex phase equilibrium and flow (porous rocks containing more than one flowing phase can sometimes act like a chromatograph, separating components as they flow). The experiments are used to test how well the models describe reality. Applications of this work range from enhanced oil and gas recovery to geologic storage of carbon dioxide (to reduce greenhouse gas emissions) to the transport of contaminants in aquifers.
This is not a comprehensive list of ERE faculty. Additional faculty listings are available here.