Abstract: Wyoming has long been known for its wealth of dinosaur remains, and among its most famous fossils date from the end of the Cretaceous period. North America’s largest carnivorous dinosaur, Tyrannosaurus, was found in Wyoming, and the first dinosaur found in Wyoming, the horned Triceratops, dates from the Late Cretaceous as well. This presentation will highlight some of Wyoming’s more interesting Late Cretaceous dinosaur species, and touch on how anatomists, palaeontologists and artists can work together to reconstruct the appearance of the living animal. Finally, we’ll have a look at how the study of sediments and plant fossils can provide clues about the landscape and flora of the dinosaurs’ environment, and allow us to visualize the world in which they lived.  

Bio: Russell J. Hawley is the Education Specialist at the Tate Geological Museum at Casper College in Wyoming, where he gives tours and produces artwork for museum displays. He also contributes a palæontology question and answer column to the museum newsletter. Russell has worked at the museum since 1997 and has been digging up fossils in Wyoming since 1990. He illustrated Islands in the Cosmos: the Evolution of Life on Land by Palæontologist Dr. Dale Russell. His one-man art show, ‘A Thousand Unnamed Worlds,’ was on display for a year at the Wyoming State Museum in Cheyenne.  

Accelerating Sweet-Spot Identification in the Mowry Shale Through Mineralogical and Geochemical Integration

Abstract

Identifying productive sweet spots in unconventional shale reservoirs requires a robust understanding of geochemistry, mineralogical variability and its influence on mechanical behavior and hydraulic fracturing potential. A central objective of this work is the development of methods that rapidly access critical subsurface information while reducing analytical time and complexity. To accelerate mineralogical characterization, a mineralogy-based brittleness index is employed to link compositional variability to hydraulic fracturing potential. In parallel, a machine-learning workflow has been developed that converts optical microscope images into quantitative mineral maps, enabling both bulk and spatial mineralogical assessment without reliance on time-intensive analytical techniques. The representative elementary area (REA) required to capture representative bulk mineralogy in the Mowry Shale has also been identified, substantially reducing micro X-ray fluorescence (µXRF) scanning time while preserving compositional representativeness. Geochemical parameters, including organic richness and thermal maturity, are incorporated into the sweet-spot quality model using similarly rapid approaches. Raman spectroscopy is applied as a fast, non-destructive method to assess thermal maturity, providing timely maturity estimates without extensive sample preparation. In clay-rich intervals of the Mowry Shale, conventional organic matter preparation workflows can be slowed by the strong presence of Bentonite. To address this limitation, electrostatic isolation of organic matter was developed and applied firsthand as a faster and safer alternative to traditional acid digestion, enabling efficient access to organic matter for characterization while minimizing chemical handling and preparation time. Ongoing efforts continue to refine and validate this workflow. Collectively, these integrated mineralogical, geochemical, and data-driven approaches demonstrate how rapid-access characterization methods can streamline sweet-spot identification and improve decision-making in heterogeneous unconventional shale systems.

Tarek Ismail Bio

Tarek Ismail is a petroleum engineer and research assistant specializing in unconventional shale characterization, with a focus on integrating geochemistry, mineralogy, and data-driven workflows for reservoir evaluation. His work emphasizes the development of faster, safer, and more scalable methods for assessing organic content, thermal maturity, and mechanical properties in clay-rich shale systems, particularly the Mowry Shale of the Powder River Basin. His research includes electrostatic isolation of organic matter, machine-learning based mineral mapping from optical imagery, and optimization of micro-XRF workflows through minimum representative area analysis. He actively collaborates with academic and government research institutions and has published peer-reviewed work on innovative shale characterization methodologies.