Publications
Listed below are publication products directly associated with the Geology, Energy & Minerals Science Center:
Filter Total Items: 1164
Mapping multivariate ore occurrence data with correspondence analysis
Correspondence analysis is a multivariate method that can be applied to mineral abundance data. Ore mineral assemblages from broadly underutilized prospect and occurrence data can be treated as geochemical anomalies, projected to low-dimensional space, and returned into map view. This approach could have applications for mineral prospectivity mapping and delineation of permissive areas during mi
Authors
Joshua Mark Rosera
Realizations
In statistics, a realization is an observed value of a random variable (Gubner 2006). In mathematical geology, the most important realizations are those in the form of maps of spatially correlated regionalized variables.Spatial description of random variables within complex domains and making certain decisions about those require complete knowledge of the attribute of interest at each point in spa
Authors
C. Özgen Karacan
Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska
Mineralogical and geochemical studies of interbedded black and gray mudstones in the Triassic part of the Triassic-Jurassic Otuk Formation (northern Alaska) document locally abundant barite and pyrite plus diverse redox signatures. These strata, deposited in an outer shelf setting at paleolatitudes of ~45 to 60°N, show widespread sedimentological evidence for bioturbation. Barite occurs preferenti
Authors
John F. Slack, Ryan J. McAleer, Wayne (Pat) Shanks, Julie A. Dumoulin
Hydrous pyrolysis of New Albany Shale: A study examining maturation changes and porosity development
The characterization of nanoscale organic structures has improved our understanding of porosity development within source-rock reservoirs, but research linking organic porosity evolution to thermal maturity has generated conflicting results. To better understand this connection, an immature (0.25% solid bitumen reflectance; BRo) sample of the New Albany Shale was used in four isothermal hydrous py
Authors
Brett J. Valentine, Paul C. Hackley, Javin J. Hatcherian
Machine learning can assign geologic basin to produced water samples using major ion geochemistry
Understanding the geochemistry of waters produced during petroleum extraction is essential to informing the best treatment and reuse options, which can potentially be optimized for a given geologic basin. Here, we used the US Geological Survey’s National Produced Waters Geochemical Database (PWGD) to determine if major ion chemistry could be used to classify accurately a produced water sample to a
Authors
Jenna L. Shelton, Aaron M. Jubb, Samuel Saxe, Emil D. Attanasi, Alexei Milkov, Mark A Engle, Philip A. Freeman, Christopher Shaffer, Madalyn S. Blondes
Compositional evolution of organic matter in Boquillas Shale across a thermal gradient at the single particle level
The molecular composition of petroliferous organic matter and its compositional evolution throughout thermal maturation provides insight for understanding petroleum generation. This information is critical for understanding hydrocarbon resources in unconventional reservoirs, as source rock organic matter is highly dispersed, in contact with the surrounding mineral matrix, and may occur as multiple
Authors
Justin E. Birdwell, Aaron M. Jubb, Paul C. Hackley, Javin J. Hatcherian
National assessment of helium resources within known natural gas reservoirs
Using available data, the U.S. Geological Survey estimated that 306 billion cubic feet of recoverable helium is presently within the known geologic natural gas reservoirs of the United States.
Authors
Sean T. Brennan, Jennifer L. Rivera, Brian A. Varela, Andy J. Park
Zirconium-bearing accessory minerals in UK Paleogene granites: Textural, compositional, and paragenetic relationships
The mineral occurrences, parageneses, textures, and compositions of Zr-bearing accessory minerals in a suite of UK Paleogene granites from Scotland and Northern Ireland are described. Baddeleyite, zirconolite, and zircon, in that sequence, formed in hornblende + biotite granites (type 1) and hedenbergite–fayalite granites (type 2). The peralkaline microgranite (type 3) of Ailsa Craig contains zirc
Authors
Harvey E. Belkin, Ray MacDonald
Frequency distribution
Given a numerical dataset, a frequency distribution is a summary displaying fluctuations of an attribute within the range of values. In contrast to an analytical probability distribution, a frequency distribution always deals with empirically observed values (Everitt and Skondall 2010). In general, the larger the number of values, the more useful is the frequency distribution relative to listing a
Authors
Ricardo A. Olea
Revisiting the declustering of spatial data with preferential sampling
Preferential sampling is a form of data collection that may significantly distort the histogram and the semivariogram of spatially correlated data. Typical situations are a higher sampling density at high-valued areas favorable for mining, and highly contaminated areas in need of environmental remediation. Multiple statistical procedures are devoted to obtaining representative statistics, whose ma
Authors
Ricardo A. Olea
Meter-scale lithofacies cycle and controls on variations in oil saturation, Wolfcamp A, Delaware and Midland Basins
Typical meter-scale lithofacies cycles from the Wolfcamp A in the Delaware and Midland Basins comprise basal carbonate facies overlain by calcareous or siliceous mudrocks. Siliceous mudstones are the most organic-rich facies with high total organic carbon (TOC > 3 wt. %), whereas thin carbonate beds have the lowest organic matter (OM) content among the lithofacies present (TOC TOC, programmed pyro
Authors
Tongwei Zhang, Qilong Fu, Xun Sun, Paul C. Hackley, Lucy Tingwei Ko, Deyong Shao
Random variable
A random variable is a function that assigns a value in a sample space to an element of an arbitrary set (James 1992; Pawlowsky-Glahn et al. 2015). It is a model for a random experiment: the arbitrary set is an abstraction of the experimental conditions, the values taken by the random variable are in the sample space, and the function itself models the assignment of outcomes, thus also describing
Authors
Ricardo A. Olea