Events

Bureau of Economic Geology Seminar Series

DeFord Lecture | Peter DeCelles

Why the Central Andes are Larger than the Himalaya by Dr. Peter DeCelles, University of Arizona

Abstract: The Central Andean and Himalayan orogenic belts provide an ideal natural experiment to test the potential role of climate in controlling orogeny. Approximately equal in age and along-strike length, both orogenic wedges are forming in plate-marginal convergent tectonic settings: The Andes in a retroarc setting and the Himalaya in a collisional setting against the Tibetan backstop. The Central Andes orogenic wedge is volumetrically and aerially nearly twice as large as the Himalayan orogenic wedge, despite the Himalaya having accommodated at least three times more tectonic shortening. The Himalaya exports at least four times more sediment owing to much greater erosion rates as signified by widespread Cenozoic metamorphic rocks and very young (<10 Ma) low-temperature thermochronologic ages. The Central Andes are thermochronologically old (mostly 20-100 Ma), have no exposures of Cenozoic metamorphic rocks, and are mantled by volcanic and sedimentary rocks, attesting to shallow, slow erosion. The most likely culprit for this situation is the greater intensity of the Indian Monsoon relative to the South American Monsoon since Oligocene time. When viewed as an orogenic wedge that has developed largely after formation of the Tibetan orogenic collage, the Himalaya is neither the largest nor hottest among Earth’s orogens.

UTIG Seminar Series: Tim Grow, Hess Corporation

Speaker: Tim Grow, Hess Corporation

Host: Ian Norton

Title: Magmatic margins, ridge jumps and isochrons – a refined tectonic model of the Gulf of Mexico

Abstract:  A newly refined and updated PaleoGIS spatial-tectonic model for opening the Gulf of Mexico (GOM) was developed based on reevaluation of geophysical datasets/findings from previous studies.  It incorporates the counterclockwise rotation of the Mayan Block in the Jurassic (Pindell & Dewey, 1982; Pindell, 1985), plates that deform to permit spatial variations in crustal stretching and the hypothesis that the GOM is a backarc basin (Stern & Dickinson, 2010).  Key findings are: (1) extensive areas of the northern GOM are floored by magmatic and/or oceanic crust; (2) a series of ridge jumps (common to back arc settings, Magni et al., 2021) facilitates opening; (3) the northern, southern and eastern margins of the GOM are magma rich, whereas the western transform margin is magma poor; (4) magnetic  isochrons in the late Callovian and early Tithonian govern the reconstruction; and (5) the Chiapas Massif restores back to the Rio Grande embayment.  The refined model implies that areas of the GOM floored with attenuated continental crust are much more restricted than most other models indicate, and that oceanic crust began forming in the northern GOM as early as the Toarcian (175 Ma).  The oceanic domain is proximal to the Louisiana coastline.  Apart from the western transform margin, the GOM continental margins are characterized by highly attenuated continental crust with significant addition of magmatic material emplaced during the final breakup prior to oceanic accretion.  The model also suggests that the Mayan Block and Chiapas Massif were two distinct crustal blocks until the Toarcian (180 Ma).  At that point they are coupled and slowly drifted south together until oceanic accretion ceased in the Tithonian (145 Ma).

AI-Enabled Geoscience Workflows Symposium

Join the investigators at the Bureau of Economic Geology (BEG) and the Jackson School of
Geosciences, along with thought leaders at Geophysical Insights, to learn how machine
learning and deep learning (AI) technologies are transforming geoscience workflows. This
half-day symposium focuses on leveraging AI technology for subsurface analysis and
characterization. Presenters will share both theory and practice, complemented by ample
case studies showing practical results in conventional and unconventional geologic settings.

Geophysical Insights, a leading Houston-based company specializing in AI software for
seismic analysis, has donated multiple licenses of their Paradise® AI workbench software to
the Jackson School of Geosciences at The University of Texas at Austin. This grant will equip
undergraduate students, graduate students, and researchers with the latest machine
learning and deep learning technologies in seismic analysis for education and research.

The Paradise AI workbench utilizes cutting-edge machine learning techniques to extract
valuable insights from seismic and well data, surpassing the capabilities of traditional seismic
interpretation tools. This advanced software applies AI algorithms to seismic and well data,
enabling geoscientists and engineers to uncover otherwise hidden patterns and enhance
their research results.

Bureau of Economic Geology Seminar Series

DeFord Lecture | Dr. Yangkang Chen

AI for Seismology: How to Make it Work for Daily Operation and Better Science by Yangkang Chen, Bureau of Economic Geology, Jackson School of Geosciences, University of Texas at Austin

Abstract: Artificial intelligence (AI) has witnessed enormous success in a variety of fields, especially in seismology. It has become widely accepted that deep learning (DL) techniques greatly help routine seismic monitoring by enabling more accurate P- and S-wave arrival picking than traditional methods. However, a completely automatic and in-production AI-driven earthquake monitoring framework has not been reported due to concerns about potential false positives using DL pickers. In this talk, I will introduce a novel AI-facilitated real-time earthquake monitoring framework developed from scratch over the past decade. The choice of optimal DL architecture is based on a decade-long iterative refinement of machine learning models and expansion of the training database. This AI system has been deployed in the Texas seismological network (TexNet) for daily operation. For the West Texas area, the seismic monitoring has been relying on our in-house DL model for reporting earthquakes to the public. For earthquakes with a magnitude above two, the picks are further validated by analysts to output the final TexNet catalog. Due to the fast-increasing seismicity caused by continuing oil & gas production in West Texas, this AI-facilitated framework significantly relieves the workload of TexNet analysts. On the other hand, AI techniques open the door to solving many scientific problems in an unprecedented way, including refining deep earth models with enhanced data preconditioning and iterative solvers, understanding the anthropogenic causes of induced earthquakes, and deciphering the earthquake nucleation mechanisms.

14th Annual Student Research Symposium

Each spring semester, Jackson School students present their research in a day-long poster competition. Throughout the day, judges comprised of faculty, research scientists, and industry representatives evaluate the posters. At the closing ceremony, 1^st-, 2^nd-, and 3^rd place poster awards are presented in the following categories: High School, Undergraduate, Master’s and Ph.D. Aspirants., and Ph.D. candidates. The goal of the Symposium is to provide cross-disciplinary collaboration among graduate students, undergraduate students, faculty, and research scientists at the Jackson School.

UTIG Seminar Series: Wenbo Wu, WHOI

Speaker: Wenbo Wu, Woods Hole Oceanographic Institution

Host: Zhe Jia

Title: Remote Sensing of Ocean Temperatures with Seismic-Acoustic Waves

Abstract: The ocean, with its immense heat-storage capacity, absorbs the majority of the excess energy resulting from anthropogenic greenhouse effects, playing a crucial role in regulating global climate and temperature changes. Accurately estimating global ocean temperature changes requires disentangling long-term trends from complex transient ocean dynamics. While increasing observational data has significantly improved the resolution and coverage of global temperature monitoring, fully resolving the long-term and transient signals remains a challenge. Acoustic thermometry, which tracks sound propagation speeds to infer temperature changes, offers a remote sensing tool for monitoring ocean temperatures. Seismic ocean thermometry (SOT), leveraging natural earthquake-generated acoustic waves (T-waves), provides a cost-efficient method to monitor large-scale average ocean temperature changes and transient signals. In this study, we applied SOT to the Indian Ocean and Northwest Pacific, successfully retrieving decadal warming trends and identifying strong transient signals, such as mesoscale eddies and biweekly equatorial waves. These findings demonstrate that SOT effectively complements existing point-based measurement techniques. This talk will also discuss the challenges and opportunities of global SOT in advancing ocean temperature monitoring.

Bureau of Economic Geology Seminar Series

DeFord Lecture | Dr. Nicola Tisato

The Rock-Physics of Geo-Fluids by Dr. Nicola Tisato, Department of Earth and Planetary Sciences, Jackson School of Geosciences, University of Texas at Austin

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. 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.

Bureau of Economic Geology Seminar Series

DeFord Lecture | Dr. Jean Philippe Avouac

Advances in Earthquake Forecasting by Dr. Jean Philippe Avouac, California Institute of Technology

Abstract: Abundant and well documented examples of earthquakes induced by extracting or injecting fluids from the subsurface have provided an opportunity to investigate earthquake physics and test earthquake forecasting models. The presentation will show that spatial and temporal variations of seismicity rate can be predicted well based on stress changes informed by reservoir operations and surface deformation measurements. This modelling framework can be used to mitigate the risk of induced seismicity during CO2 storage of geothermal operations. These progress open avenues for time-dependent probabilistic forecasting of the time, location and magnitude of individual events.

"Love and War: What We Can Learn from Chimpanzees"

What can the social lives of chimps teach us about our own? In the next Hot Science – Cool Talks, primatologists Dr. Aaron Sandel and Isabelle Clark share their first hand accounts of living amongst a chimpanzee social group. Discover how our closest ape relatives navigate social bonds, manage violence, and build connections.

This is a featured event in the 2025 Texas Science Festival. Environmental Science Institute is a proud partner of the Festival, organized by The University of Texas at Austin’s College of Natural Sciences.