Carl Heiland Lecture Series

A Complex Ice Flow History in Northern Greenland Inferred from Novel Ice Penetrating Radar Data

Nicholas Holschuh
Amherst College

In person: HH 202; Zoom webinar link: https://mines.zoom.us/j/95432461641

Abstract

Radio-echo sounding data from some of the earliest geophysical surveys in Greenland captured anomalous structures deep within the Greenland ice sheet. There has been active debate about how these structures form, with most studies assuming they comprise deformed, meteoric (i.e., glacial) ice. But these studies were only informed by observations of structure geometry from radar. In this talk, I will demonstrate some of the advanced imaging capabilities of modern ice-penetrating radar, now capable of capturing the 3D-scattering distribution from dielectric contrasts within the Greenland Ice Sheet. These new data show that many (but not all) of the previously identified structures appear to be capped by debris, scattering radio waves in a way that is qualitatively different from typical glacial layering. I will use these data to challenge existing models of structure formation, and identify new questions about how ice, rock, and water interact at the base of glaciers.

Speaker Bio

Dr. Nick Holschuh is an assistant professor of geology at Amherst College. His primary research interest is in improving our understanding of the physics of glacier sliding using observational geophysics. That work has taken him to Antarctica four times, most recently to Thwaites Glacier, where he has used ice-penetrating radar, active and passive seismic techniques, and gravimetry to measure the glacier subsurface.

How Observations Improve Models of Iceberg Calving

Dr. Joanna Millstein
Colorado School of Mines

In-person: BE 243; Zoom link: https://mines.zoom.us/j/95432461641

Abstract

Fractures in glacier ice, from crevasses at the glacier surface to icebergs calving at the continent’s edge, compromise the structural stability of glaciers and ice sheets, contributing to their mass loss. The current mechanical understanding of fracture initiation and propagation in glaciers is notably lacking in observationally validated and empirically derived models, largely due to a scarcity of data over relevant spatial and temporal scales. Here, I will describe two interconnected research projects that strive to reconcile the limited understanding of fracture propagation with the need for realistic numerical models of ice sheet change. The first project analyzes major Antarctic calving events through four decades of observational iceberg data, employing extreme value theory to develop a statistical model. Our statistical model captures the stochastic nature of iceberg calving and establishes recurrence intervals over which we expect to see icebergs of varying sizes. The second project implements this framework within the Community Ice Sheet Model (CISM), a numerical framework designed for simulating large-scale ice sheet dynamics. By integrating physics-based calving criteria with a stochastic parameterization, the model successfully reproduces observed patterns of sudden change in Antarctica’s ice sheets. These complementary approaches establish an exciting path for determining and assessing future changes to the Antarctic ice sheet.

Dr. Joanna Millstein is a Postdoctoral Fellow in Geophysics at Mines. Her research investigates the rheology, fracture, and stability of glacier ice and ice sheets. She uses observational data to derive statistical and mechanical models that describe the physical processes of ice. When she isn’t working with the Mines Glaciology Laboratory in the Green Center, she is an instructor for an Arctic Geophysics field course at The University Centre in Svalbard.

Beyond Resolution: A Quest to Make Digital Rock Physics Relevant for Seismic Interpretation

Dr. Stanislav Glubokovskikh
Lawrence Berkeley National Laboratory

In-person: HH 202; Zoom link: https://mines.zoom.us/j/95432461641

Abstract

The main goal of rock physics lies in linking pore-scale characteristics measured in the lab to geophysical observations in the field. Unfortunately, rock physicists are often constrained to simple data fitting, relying on overly simplified models. High-resolution rock imaging was once viewed as a breakthrough that could fix that. However, studies have shown a persistent mismatch between digital rock physics estimates and measured rock stiffness. The limitations stem from both insufficient resolution and the small sample sizes of these images. Also, we lack the necessary properties at that scale to perform reliable simulations.

We present an on-going effort to make digital rock physics useful for seismic interpretation. Rather than attempting to directly resolve invisible regions of rock and relying on poorly constrained properties of its constituents, we solve an inverse modeling problem. Specifically, we examine the stress sensitivity of ultrasonic measurements under varying pore space saturation. When integrated with advanced image analysis and petrophysical characterization, these measurements enable the simultaneous inversion of both mineral and contact stiffness. This workflow requires some non-trivial tricks in computational imaging and modeling. In the end, we discuss broader implications of the proposed workflow for seismic monitoring of geological carbon sequestration and hydrogen storage.

Speaker Bio

Dr. Stanislav Glubokovskikh is an Earth Staff Scientist at Lawrence Berkeley National Laboratory. His work focuses on developing innovative techniques to image subsurface, supporting its safer, more efficient use. Stanislav’s research spans from the fundamental study of fluid/rock interactions at the mineral-grain scale to the development of hybrid sensing arrays for reservoir-scale reservoir monitoring, to modeling-driven data assimilation across sedimentary basins of hundreds of kilometers.

Integrated Approaches to Rock Physics and Sustainable Geoenergy Futures

Dr. Paul Selvadurai
Swiss Seismological Service, Department of Earth and Planetary Sciences, ETH Zurich

In-person: HH 202; Zoom link: https://mines.zoom.us/j/95432461641

Abstract

To meet increasing global energy demands, we need to ensure the sustainable use of subsurface resources. This requires deep understanding of the complex geophysical processes linked to the evolution of the rock fabric, stress conditions and rheology, and their influence of rock deformation and fluid transport properties. I employ a holistic bottom-up approach in which small-scale laboratory experiments are conducted and insight is applied to larger-scale studies in various collaborative underground rock laboratories.
We have developed a methodology to study seismic and aseismic cracking of rocks (damage) providing a novel view of pre-failure inelastic deformation/seismicity patterns in rocks. This has also led to the characterization of stress and fluid-rock interactions and localization of deformation (strain) with seismicity (acoustic emissions) under realistic subsurface conditions. Using these experimental observations, we build statistical and numerical models that inform new theories needed to assess safe patterns of deformation at larger geologic scales. My research addresses induced seismicity—a currently unpredictable consequence of human activity posing a significant risk to society. I will discuss established frameworks that forecast risk, and describe how advances in our understanding at smaller scales can improve these assessments.

Speaker Bio

Dr. Paul Selvadurai is a rock physicist focusing on earthquake physics, mechanics of fractured porous media, mineral and rock physics, and seismology. HIs research bridges geophysics and geomechanics by investigating the mechanisms that influence the dynamics of Earth deformation. He approaches problems as an experimentalist and supports his understanding with theoretical, statistical, and computational models. This allows him to study a variety of problems related to rock failure and rheology, as well as the physico-chemical and mechanical processes governing the evolution of porosity and permeability in stressed geomaterials.

The Rock-Physics of Geo-Fluids

Nicola Tisato
University of Texas-Austin

In-person: HH202; Zoom link: https://mines.zoom.us/j/95432461641

Abstract: The energy sector has long relied on subsurface exploration, with reservoir fluids playing a fundamental role in ensuring resources. Today, and likely in the future, exploiting the subsurface will be increasingly vital for advancing an energy landscape driven by emerging technologies that address the challenges of the climate crisis, such as geothermal, carbon capture utilization and sequestration (CCUS), and hydrogen storage. Therefore, enhancing our understanding of geologic processes by improving our geophysical toolkit is essential for implementing these innovations and boosting resilience. Here, I present scientific results that offer valuable insights for advancing subsurface imaging, monitoring, and exploration. In particular, I will showcase a combination of theoretical work with laboratory and numerical experiments investigating how multiphase fluids – e.g., CO₂ or hydrogen bubble-bearing brines – influence seismic wave propagation in reservoirs. I will also present novel rock physics experiments paired with micro-computed tomography (CT) imaging, revealing how the dissolution and precipitation of minerals in ultramafic rocks control their physical properties during carbon sequestration.

Speaker Bio
Dr. Nicola Tisato is an associate professor at the Department of Earth and Planetary Sciences of The University of Texas at Austin. In 2016, Tisato founded and became the principal investigator of the Rock Deformation Laboratory – a space defined as a “Swiss-army knife” facility where scientists can experiment and test their theories to advance geosciences and unravel our planet’s secrets and potentials. In recent years, researchers at the Rock Deformations Laboratory have focused on issues related to earthquakes, carbon sequestration, attenuation and dispersion of seismic waves, digital rock physics, the dissolution of carbonates, and the formation of caves. Tisato loves mountains, cross-country skiing, and caving.

The Evolution of Seismic Acquisition and Artificial Intelligence

Dave Monk
ACTeQ

In-person: HH 202 ; Zoom link: https://mines.zoom.us/j/95432461641

Abstract

Artificial Intelligence (AI) is viewed by many as having a huge impact on geophysics in general. It is the “lens” of future geophysics. In this presentation I look backwards at the history of seismic acquisition and show how the technology has changed, and I illustrate some of the short comings of commonly used AI systems in use today. While A.I. may be useful in some applications where solutions or answers are not necessarily based on scientific data, some solutions often fall short of being accurate or correct.

Speaker Bio

Dr. Dave Monk holds a PhD in Physics from Nottingham University in the UK, and served as director of geophysics at Apache Corporation, until his retirement in October 2019. Author of more than 200 technical papers, he is a past president of the SEG. He currently serves as a technical advisor for ACTeQ (a seismic survey design software company which he co-founded), GTI (a seismic node manufacturer). He recently took a position on the Board of Directors for DUG, a technology company based in Australia.

Stochastic Control of Natural Resource Operations using Geophysical Measurements and Deep Reinforcement Learning: Fundamental Concepts and a Few Illustrative Examples

Andrei Swidinsky
University of Toronto

In-person: HH 202; Zoom link: https://mines.zoom.us/j/95432461641

Abstract

Stochastic control is concerned with optimal decision-making in the presence of uncertainty. One approach to solving such control problems is deep reinforcement learning (DRL), which, along with supervised and unsupervised learning, is one of the three main categories of machine learning. DRL agents learn optimal behavior through repeated interaction with their surrounding environments, and have achieved human-level performance in challenging domains such as algorithmic trading, navigating self-driving cars and playing classic board & video games. To date, DRL has only been sparingly used for natural resource projects but because applied geophysicists – and more generally, applied geoscientists – acquire data to make various engineering and business decisions, I posit that the machinery of DRL is an ideal match for the exploration, development, production and/or management of subsurface resources.

One key feature that differentiates DRL from other machine learning paradigms is that “time really matters”, meaning that decisions are made on-line according to the current situation (such as each move on a chess board). Various geoscientific applications like geothermal energy production, groundwater management or geological carbon storage can benefit from such on-line sequential decision-making for optimal well placement or flow control, and time-lapse geophysical measurements – like gravity, electromagnetics or seismic – can be key inputs for this process. Likewise, optimal exploration strategies for net-zero technology-enabling commodities such as critical minerals also require sequential decisions concerning what type of data to collect as exploration proceeds. In this talk, I will outline the efforts of GeoDecisions, my research group at the University of Toronto, in applying DRL to subsurface resource problems: first through fundamental concepts and subsequently by a few illustrative optimal control examples.

Speaker Bio

Dr. Andrei Swidinsky completed his undergraduate education in theoretical physics at the University of Guelph, and his graduate studies in geophysics at the University of Toronto. Upon finishing his doctorate in 2011, he spent the following two years as a postdoctoral research fellow at the Helmholtz Centre for Ocean Research Kiel (Geomar). From 2013–2021, Swidinsky was a faculty member at the Colorado School of Mines, Department of Geophysics (as an assistant professor from 2013–2019 and as a tenured associate professor from 2019–2021). Since July 2021, he has been an associate professor and the Teck Chair in Exploration Geophysics at the University of Toronto, Department of Earth Sciences.

Keepers of 3D Knowledge: How do Geophysicists Add Value in the Unconventional World?

Sean Bader
EOG Resources

In-person only: HH 202

Abstract

Production from unconventional reservoirs has been a key driver of oil growth in the United States for the last decade. While geophysics and geophysical data have a clear value proposition in higher risk conventional reservoirs, the value geophysicists bring to the table in unconventional projects has been more challenging to define. This is due to an increase in the required level of detail and multidisciplinary data necessary to minimize error, such that our products are useful to drillers and engineers during exploration and horizontal development. Error or uncertainty in structural interpretation, reservoir characterization and microseismic data analysis cannot exist on the hundreds of feet as it has in the past, rather we must drive it down to tens of feet to provide day-to-day value.
This goal may seem impossible given the subseismic scale we are required to operate. However, appropriately placing geophysical data in the context of the geological model and utilizing the plethora of auxiliary data that comes with onshore, unconventional drilling we can drive down towards this goal. Providing clear structural interpretations requires calibrated velocity and anisotropic models for depth migration, quality controlled against independent datasets such as logs, tops and horizontal wells. These models are tested with every well drilled, from spud to production, often hundreds of times per year. In this talk, I will review several challenges posed to geophysicists in the unconventional world and will focus on the value proposition of a detailed structural model, and the downstream effects it has on drilling, completions and production.

Speaker Bio

Sean Bader completed his undergraduate education in geophysics/geophysical engineering at the Colorado School of Mines, and his graduate studies at the University of Texas at Austin. After finishing his Master’s degree in 2018, he started working at EOG Resources in the San Antonio Division focusing on developing the oil window Eagle Ford and Austin Chalk. In 2020, he was transferred to the Corpus Christi Division to work the Dorado, high pressure high temperature, gas asset. In 2022, he was transferred to the Denver Division (returning home) and has spent the last several years working in the Powder River Basin. The opportunity to work on several EOG assets in different structural settings and maturity ranges has helped to round out his skillset as not only a geophysicist, but, also, a development geoscientist.

Erin Wirth

In-person: HH 202; Zoom link: https://mines.zoom.us/j/95432461641

Luca Duranti
Chevron

In-person: HH 202; Zoom link: https://mines.zoom.us/j/95432461641

Meaningful monitoring of Tailings Dams with Distributed Acoustic Sensing

Susanne Ouellet
Lumidas

In-person: HH 202; Zoom link: https://mines.zoom.us/j/95432461641

Abstract

Tailings dams are designed and built to retain waste generated from mining. The safety of tailings dams requires comprehensive monitoring solutions that can detect subtle precursors to potential failure modes. Distributed acoustic sensing (DAS) is an emerging fiber-optic sensing technology providing real-time monitoring capabilities across extensive areas with nanostrain sensitivity. By implementing complementary signal processing algorithms, DAS technology can detect strain, temperature, and seismic perturbations through Rayleigh backscattering of light along tens of kilometers of cable, making it particularly suitable for monitoring dams and auxiliary infrastructure. In 2019, nearly six kilometers of fiber-optic cable were installed at ~1 m depth along an active upstream tailings dam in northern Canada. Energy from the ambient seismic wave field was used with DAS to infer changes in shear wave velocities of up to ~2%, corresponding to springtime thaw and rainfall. In a separate study, we demonstrate how the same technology, with different signal processing techniques, can be used to detect submillimeter near-surface slope displacements, correlating with nearby geotechnical instrumentation. This dual monitoring capability, combined with high spatiotemporal resolution, enables earlier detection of potential instabilities, supporting proactive dam safety management and risk mitigation.

Speaker Bio

Dr. Susanne Ouellet is the founder of Lumidas, a cleantech startup specializing in advanced geotechnical monitoring of critical infrastructure using distributed-fiber-optic sensing technologies. Dr. Ouellet’s research at the University of Calgary focused on advancing tailings dam performance monitoring using DAS. She is a registered professional geotechnical engineer in Alberta with over ten years’ experience in research and consulting. Her background gives her a deep insight into the practical challenges and technological needs of the industry, insights she is now channeling into Lumidas.

iury Simões-Sousa
Woods Hole Oceanographic Institute

In-person: HH 202; Zoom link: https://mines.zoom.us/j/95432461641