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At least 163 records · Page 9

Characterizing the uppermost 100 m structure of the San Jacinto fault zone southeast of Anza, California, through joint analysis of geological, topographic, seismic and resistivity data

We present results from complementary geological, topographic, seismic and electrical resistivity surveys at the Sagebrush Flat (SGB) site along the Clark fault (CF) strand of the San Jacinto fault zone trifurcation area southeast of Anza, California. Joint interpretation of these data sets, each with unique spatiotemporal sensitivities, allow us to better characterize the shallow (<100 m) fault zone at this structurally complex site. Geological mapping at the surface shows the CF has three main subparallel strands within a <100 m zone with varying degrees of rock damage. These strands intersect units of banded gneiss and tonalite, and various sedimentary units. Near the surface, the weathered but more intact tonalite and gneiss to the southwest have relatively high VP. The low-lying flat sedimentary basins around the two southwestern-most CF strands and elevated damaged gneiss to the northeast have lowest VP <500 m s–1. The high relief of the northeast gneiss unit may in part be explained by its extensive damage and inferred increased relative rock uplift. Resistivity imaging shows the unconsolidated dry basin sediments (maximum >1300 Ohm.m) contrasted against the compacted fine-grained (potentially wet) materials within the CF core and the Bautista Formation (minimum <40 Ohm.m), which is slightly elevated above the flat basins. The inverse relationship between VP (increases) and resistivity (decreases) in the uppermost ~15 m can be characterized as log–log linear with slopes of –2.6 to –4. At depths >30 m, the velocity heterogeneity near the surface merges into larger-scale structures that are generally slower on the northeast side of the CF core compared to the southwest side (as much as ~40 per cent reduction in average VP). A previous study revealed a 20–37 per cent variability in peak ground velocities across the SGB site from local earthquakes. The upper end of that range is associated with the near-surface unconsolidated sedimentary basins and northeast damaged gneiss unit. Preliminary analysis of time-dependent topography mostly shows effects of changing vegetation and anthropogenic activity.

Geochemistry & Geophysics↗

Non-LTE analysis of extremely helium-rich stars. The hot sdO stars LSE 153, 259 and 263

Results of a non-LTE fine analysis based mainly on high-resolution CASPEC spectra for three extremely helium-rich sdO stars are discussed in order to explain hydrogen deficiency in single stars. High temperature (Teff = 70,000 to 75,000 K) and a position in the log Teff - log g diagram were found close to the Eddington limit. Various abundance estimates are derived for hydrogen (upper limits only), carbon, nitrogen, and magnesium. Hydrogen is reduced to less than 10 percent by number in LSE 153 and LSE 263, and to less than 5 percent in LSE 259. The hydrogen deficiency is accompanied by nitrogen- and carbon-enrichment in LSE 153 and LSE 259 only. In LSE 263, carbon is depleted by about 1 dex. Stellar masses obtained by assuming that a core mass-luminosity relation holds for these stars, were found to be in the range 0.6-0.9 solar mass, yielding luminosities log L/L:solar = 3.7-4.5. Two of the program stars (LSE 153 and 259) appear to be possible successors of the R CrB and helium B stars, whereas the third star (LSE 263) displays a much lower carbon content in its photosphere making it an exceptional case among the known hydrogen deficient stars.

Husfeld, D.↗

Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2

The project Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2 is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Los Angeles Basin presents an opportunity for large-scale geologic CO2 storage. Due to its large population and historical and geologic setting as one of the most prolific oil and gas producing basins in the United States, the region is home to more than 12 major power plants and oil refineries that produce more than 5 million metric tons of fossil fuel-related CO2 emissions each year. GeoMechanics Technologies worked to characterize the Pliocene and Miocene sediments in the Wilmington Graben, offshore of Los Angeles, California, for high-volume CO2 storage. The Graben is located offshore of the Los Angeles and Long Beach Harbor area, making it accessible yet geologically isolated from the nearby Wilmington oilfield and onshore areas. These sediments span more than 5,000 feet of vertical interval with an estimated storage resource of more than 100 million metric tons of CO2. The project team analyzed and interpreted existing geologic data within the region, including detailed exploration well log data and 2-D and 3-D seismic data. New seismic lines were acquired to fill in current data gap areas and two new characterization wells were drilled and logged. This information was integrated with existing geologic interpretations for adjacent onshore areas to help characterize optimal areas for CO2 storage and seals to safely store CO2. Integrated 3-D geologic and geomechanical models for the Wilmington Graben were developed to simulate the fate and transport of injected CO2 in the subsurface and to assess risks. This project contributed to the understanding of injectivity, containment mechanisms, rate of dissolution and mineralization, and storage capacity of the Wilmington Graben and associated analogous basins. This effort also provided greater insight into the potential for offshore geologic formations to safely and permanently store CO2.

.las↗

SN 2022ann: a Type Icn supernova from a dwarf galaxy that reveals helium in its circumstellar environment

Here, we present optical and near-infrared (NIR) observations of the Type Icn supernova (SN Icn) 2022ann, the fifth member of its newly identified class of SNe. Its early optical spectra are dominated by narrow carbon and oxygen P-Cygni features with absorption velocities of ∼800 km s −1 ; slower than other SNe Icn and indicative of interaction with a dense, H/He-poor circumstellar medium (CSM) that is outflowing slower than typical Wolf–Rayet wind velocities of >1000 km s −1 . We identify helium in NIR spectra 2 weeks after maximum and in optical spectra at 3 weeks, demonstrating that the CSM is not fully devoid of helium. Unlike other SNe Icn, the spectra of SN 2022ann never develop broad features from SN ejecta, including in the nebular phase. Compared to other SNe Icn, SN 2022ann has a low luminosity (o-band absolute magnitude of ∼−17.7), and evolves slowly. The bolometric light curve is well-modelled by 4.8 M ⊙ of SN ejecta interacting with 1.3 M ⊙ of CSM. We place an upper limit of 0.04 M ⊙ of 56 Ni synthesized in the explosion. The host galaxy is a dwarf galaxy with a stellar mass of 10 7.34 M ⊙ (implied metallicity of log(Z/Z ⊙ ) ≈ 0.10) and integrated star-formation rate of log (SFR) = −2.20 M ⊙ yr −1 ; both lower than 97 per cent of galaxies observed to produce core-collapse supernovae, although consistent with star-forming galaxies on the galaxy Main Sequence. The low CSM velocity, nickel and ejecta masses, and likely low-metallicity environment disfavour a single Wolf–Rayet progenitor star. Instead, a binary companion is likely required to adequately strip the progenitor and produce a low-velocity outflow.

79 ASTRONOMY AND ASTROPHYSICS↗

A Complete Sample of Hot Post-AGB Stars in Globular Clusters

Ultraviolet images of globular clusters are often dominated by one or two "UV-bright" stars. The most luminous of these are believed to be post-AGB stars, which go through a luminous UV-bright phase as they leave the AGB and move rapidly across the HR diagram toward their final white dwarf state. During the two flights of the ASTRO observatory in 1990 and 1995, the Ultraviolet Imaging Telescope (UIT, Stecher 1997, PASP, 109, 584) was used to obtained ultraviolet (1600 A) images of 14 globular clusters. These images provide a complete census of hot (> 8000 K) post-AGB stars in the observed globular clusters, because the 40' field of view of UIT is large enough to image the entire population of most Galactic globulars, and because the dominant cool star population is suppressed in ultraviolet images, allowing UV-bright stars to be detected into the cluster core. We have begun a program of optical and STIS ultraviolet spectroscopy to determine the fundamental stellar parameters (\log L, T_eff, \log g) of all the hot post-AGB candidates discovered on the UIT images. Among the goals of our program are to test theoretical post-AGB lifetimes across the HR diagram, and to estimate the mass of the currently forming white dwarfs in globular clusters. Two trends are already apparent in our survey. First, the UV-selected sample has removed a bias against the detection of the hottest post-AGB stars, and resulted in the discovery of five cluster post-AGB stars with Teff > 50,000 K. Second, most of the new discoveries have been lower luminosity (2.5 $<$\log L $<$ 3.0) than expected for stars which leave the AGB during the thermally pulsating phase.

Landsman, W.↗

Porous Colloidal Nanoparticles as Injectable Multimodal Contrast Agents for Enhanced Geophysical Sensing

Injecting fluids into underground geologic structures is crucial for the development of long-term strategies for managing captured carbon and facilitating sustainable energy extraction operations. Here, we have previously reported that the injection of metal–organic frameworks (MOFs) into the subsurface can enhance seismic monitoring tools to track fluids and map complex structures, reduce risk, and verify containment in carbon storage reservoirs because of their absorption capacity of low-frequency seismic waves. Here, we demonstrate that water-based Cr/Zn/Zr MOF colloidal suspensions (nanofluids) are multimodal geophysical contrast agents that enhance near-wellbore logging tools. Based on experimental fluid-only measurements, MIL-101(Cr), ZIF-8, and UiO-66 nanofluids have distinct complex conductivity and/or low-field nuclear magnetic resonance (NMR) signatures that are relevant to field-deployed technologies, implying the potential to enhance near-wellbore monitoring of CO 2 injection and associated processes with downhole logging tools. Small- and wide-angle X-ray scattering characterization of ~0.5 wt % MIL-101(Cr) suspensions confirmed phase stability and provided insight into the fractal nature of colloidal nanoparticles. Finally, low-field (2 MHz) NMR measurements of MIL-101(Cr) nanofluid injection into a prototypical Berea sandstone demonstrate how paramagnetic high-surface area MOFs may dominate the relaxation times of hydrogen-bearing fluids in porous geologic matrices, enhancing the mapping of near-surface and near-wellbore transport pathways and advancing sustainable subsurface energy technologies.

NMR↗

Numerical calculations of the collapse of nonrotating, magnetic gas clouds

Results of the first self-consistent numerical calculations of the dynamic collapse of a magnetized protostellar gas cloud are presented. Symmetry about an axis parallel to the initial magnetic field direction has been assumed, so that the calculations could be performed on a two-dimensional grid. Also, the cloud was taken to be nonrotating and isothermal, and the magnetic field was assumed to remain frozen in to the gas. As starting models for the calculations, gas spheres with uniform density and magnetic field were used. The time evolution of the clouds has been calculated for roughly two initial free-fall times, at which point the central density has increased by a factor of approximately 10,000 to 1,000,000. Several such calculations have been performed for different values of the cloud's initial thermal, magnetic, and gravitational energies. In virtually all cases it is found that, once a flattened core forms in the cloud, the central magnetic field strength, B, varies with gas density, rho, according to (d log B/d log rho) = 1/2. This behavior is independent of the initial energy ratios mentioned above. It is also found that the magnetic field is able to prevent completely the collapse of part of the outer envelope of the cloud.

Scott, E. H.↗

A Survey of Distant Clusters of Galaxies Selected by X-Rays

I will discuss the results of a new survey of X-ray selected, distant clusters of galaxies that has been undertaken by our group at.CfA (Vikhlinin, McNamara, Forman, Jones). We have analyzed the inner 17.5 arcminute region of roughly 650 ROSAT PSPC images of high latitude fields to compile a complete, flux-limited sample of clusters with a mean flux limit roughly 20 times more sensitive than the Einstein Medium Sensitivity Survey. The goal of our survey, which presently contains 233 extended X-ray sources, is to study cluster evolution over cosmological timescales. We have obtained optical images for nearly all of the faintest sources using the 1.2 m telescope of the Fred L. Whipple Observatory, and when including POSS images of the brighter sources, we have nearly completed the identification of all of the extended sources. Roughly 80% of the sources were identified as clusters of galaxies. We have measured redshifts for 42 clusters using the MMT, and including additional measurements from the literature, roughly 70 clusters in our catalog have spectroscopic redshifts. Using CCD photometry and spectroscopic redshifts, we have determined a magnitude-redshift relation which will allow redshifts of the remaining clusters in our sample to be determined photometrically to within a delta z over z of roughly ten percent. I will discuss the Log(N)-Log(S) relation for our sample and compare it to other determinations. In addition, I will discuss the evolution of core radii of clusters.

McNamara, Brian↗

Percolative Sulfide Core Formation in Oxidized Meteorite Parent Bodies

Most models of planetary differentiation involve the formation of metallic cores during or after extensive silicate melting, but some volatile-rich reservoirs in the protoplanetary disk did not accrete substantial amounts of Fe,Ni-metal. Instead, their potential core-forming assemblages were dominated by Fe,Ni-sulfides and oxides due to high ƒ O 2 and ƒ S 2 . Derivative melts from these assemblages may have been capable of percolative migration leading to core formation prior to silicate melting. However, no direct evidence for this process has been reported in meteoritic literature. Similarly, while many iron meteorites are thought to represent cores of their respective parent bodies, no direct evidence for Fe,Ni-sulfide/oxide cores have been reported to-date. The most promising potential for such evidence may be found in the anomalous noble metal trace element proportions of restitic oxidized primitive achondrites (i.e., brachinites, log ƒ O 2 ~IW-1), which are similar to those found in sulfides of Rumuruti-type chondrites (RCs) that contain only trace amounts of Fe,Ni-metal at log ƒ O 2 ≥ IW-1. This work addresses the following outstanding questions: (1) Are molten sulfides in oxidized meteorite assemblages capable of percolative melt migration? (2) How is this process recorded in the noble metal (i.e., siderophile/chalcophile) trace element geochemistry of relevant meteorites? (3) Did O,S-rich meteorite parent bodies form sulfide cores?

S. D. Crossley↗

Determination of nitrogen to carbon abundance ratios from transition layer emission lines

We have finished studying the nitrogen to carbon abundance ratios for stars with different effective temperatures T(sub eff) and luminosities using transition layer emission lines and using spectra available in the IUE archives. The N/C abundance ratio determinations using transition layer emission lines are as accurate as the photospheric abundance determinations as found by comparison of results obtained by both methods for the same stars. Our measurements confirm photospheric abundance determinations in regions of the HR diagram where they can be obtained. Our studies have extended the temperature range to higher temperatures. They have shown the exact positions in the HR diagram where the mixing due to the outer convection zones reaches deep enough to bring nuclear processed material to the surface. This occurs at effective temperatures which are higher by delta log T(sub eff) approximately 0.04 or roughly 400 K than expected theoretically. Since the depth of the convection zone increases rapidly with decreasing T(sub eff) this may indicate considerable overshoot beyond the lower boundary of the convection zone. Our N/C abundance ratio determinations from transition layer emission lines have confirmed that the actual enrichment observed for some cool giants is larger than expected theoretically, again indicating a larger degree of mixing in several stars either from below or from above. For the supergiants it probably indicates overshoot above the convective core in the progenitor main sequence stars. For the more massive giants this may also be the case, though we did not find a correlation between delta log N/C and the absolute magnitudes, but these are rather uncertain. As byproducts of these studies we also found anomalies in Si/C and N/C abundance ratios for F giants which can be understood as the relict of surface abundance changes for their main sequence progenitors due to diffusion. This anomaly disappears for G giants, for which the depths of the convection zones are apparently deep enough to wipe out these element separations (Bohm-Vitense 1992).

Boehm-Vitense, Erika↗

Demonstration of a multi-channel fluidized bed particle–supercritical carbon dioxide heat exchanger for concentrating solar applications

High-temperature thermal energy storage in oxide particles at temperatures above 600°C can couple concentrated solar energy with high-efficiency thermal power cycles to provide dispatchable solar-driven electricity. Challenges remain in developing cost-effective primary heat exchangers, which require expensive alloys, to extract the high-temperature thermal energy from the particles to power cycle fluids, such as supercritical CO 2 (sCO 2 ) in recuperated Brayton cycles. To explore one pathway for cost-effective, high-temperature particle heat exchangers, the current study demonstrates a shell-and-plate, particle–sCO 2 heat exchanger with narrow- channel fluidized beds coupled with micro-channel sCO 2 flows in the heat exchanger walls. This study evaluates the feasibility of multiple parallel, narrow-channel fluidized beds in shell-and-plate particle–sCO 2 HXs, to achieve high bed-wall heat fluxes at elevated temperatures. A reduced-order model simulates the narrow- channel, fluidized-bed particle–sCO 2 heat exchanger to design the fluidized bed geometry, in terms of depth, height, and number of channels,for a nominal 40-kWth heat exchanger at particle and sCO 2 inlet temperatures up to 600 °C and 400 °C respectively. The resulting shell-and-plate heat exchanger design operates with bubbling fluidization of the downward-flowing oxide particles to enhance bed-wall heat transfer. The heat exchanger core is fabricated with etched sCO 2 micro-channels in thin wall plates that are diffusion bonded to spacer frames to form the shell-and-plate structure with 12 parallel, fluidized bed channels, 10.4 mm deep. The heat exchanger is tested at the National Solar Thermal Test Facility at Sandia National Laboratories with CARBOBEAD HSP particles at design particle flow rates of 0.20 kg s –1 and inlet temperatures up to 525 °C. Results show that fluidization across multiple parallel channel beds can maintain uniform particle inventory with a common freeboard zone above the heat exchanger core. Bubbling fluidization improves particle–wall heat transfer coefficients but also increases axial dispersion of particle thermal energy, which lowers the log- mean temperature difference such that total heat transfer remains relatively constant to within ±10% over a broad range of fluidization gas velocities. The axial dispersion required particle and sCO 2 flow rates to be increased by 25% over model-designed conditions to achieve the targeted 40 kWth, which indicates the importance of incorporating axial dispersion into heat exchanger design models and of deploying bed structures to suppress it. Furthermore, this study demonstrates the feasibility and preferred fluidizing gas conditions for particle heat exchangers for releasing high-temperature thermal energy storage systems.

14 SOLAR ENERGY↗

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗

Diagnostic assessment of reservoir response to fracturing: a case study from Hydraulic Fracturing Test Site (HFTS) in Midland Basin

Abstract This paper outlines a data collection and diagnostics case study involving multiple horizontal shale wells. We look at well production profiles using rate transient analysis, differences in near wellbore complexity, geologic variations within the area of interest, as well as compositional differences in the rocks based on cores obtained from within the stimulated reservoir. The Hydraulic Fracturing Test Site is a multi-well experiment involving stimulation of unconventional shale wells in the southeastern Midland portion of the Permian Basin. The targeted formations include both the upper as well as the middle Wolfcamp formations, also referred alternatively as Wolfcamp A and Wolfcamp B. Data integration and analysis shared in this paper help us understand the various geologic controls impacting well productivity, particularly the wide variance observed between the Wolfcamp A and Wolfcamp B formations. Rate transient analysis indicates similar system permeabilities for stimulated wells. However, we observe higher effective fracture half-lengths for upper Wolfcamp wells. Using observations from 3D seismic interpretations (such as pad scale faults) as well as petrophysical and image log data, we highlight the substantial differences in stimulation as we move along the well laterals from the heel toward the toe sections. These differences are further reconciled with observations from zones with high data density at the core locations through stimulated rock, as well as independent data such as microseismic emissions. At the test site, Wolfcamp A was found to be relatively quartz rich with significant heterogeneity whereas Wolfcamp B is richer in clay and organic content. This impacts the geomechanical characteristics of the rock mass with much higher natural fracture density in the shallower interval. Thus, the fracture growth is more uniform in the deeper interval and more heterogeneous with branching likely in upper interval. Increased complexity also leads to consistently better productivity from the wells in the shallower interval as demonstrated from RTA results. This case study is unique because it provides valuable insights from actual sampling of the stimulated zones in hydraulically fractured wells and helps understand impact of various factors that contribute toward variability in well production. The findings from this study provides insights into need for optimization of completion designs in the various Wolfcamp landing zones, such as optimization of cluster or fracture spacing in various Wolfcamp intervals. In addition, it provides a useful template for data collection and research direction in future field test sites of similar nature in unconventional reservoirs.

Energy & Fuels↗

Probabilistic Assessment and Uncertainty Analysis of CO2 Storage Capacity of the Morrow B Sandstone—Farnsworth Field Unit

This paper presents probabilistic methods to estimate the quantity of carbon dioxide (CO2) that can be stored in a mature oil reservoir and analyzes the uncertainties associated with the estimation. This work uses data from the Farnsworth Field Unit (FWU), Ochiltree County, Texas, which is currently undergoing a tertiary recovery process. The input parameters are determined from seismic, core, and fluid analyses. The results of the estimation of the CO2 storage capacity of the reservoir are presented with both expectation curve and log probability plot. The expectation curve provides a range of possible outcomes such as the P90, P50, and P10. The deterministic value is calculated as the statistical mean of the storage capacity. The coefficient of variation and the uncertainty index, P10/P90, is used to analyze the overall uncertainty of the estimations. A relative impact plot is developed to analyze the sensitivity of the input parameters towards the total uncertainty and compared with Monte Carlo. In comparison to the Monte Carlo method, the results are practically the same. The probabilistic technique presented in this paper can be applied in different geological settings as well as other engineering applications.

03 NATURAL GAS↗

Architectural Analysis of Complex Evolving Systems of Systems

The goal of this collaborative project between FC-MD, APL, and GSFC and supported by NASA IV&V Software Assurance Research Program (SARP), was to develop a tool, Dynamic SAVE, or Dyn-SAVE for short, for analyzing architectures of systems of systems. The project team was comprised of the principal investigator (PI) from FC-MD and four other FC-MD scientists (part time) and several FC-MD students (full time), as well as, two APL software architects (part time), and one NASA POC (part time). The PI and FC-MD scientists together with APL architects were responsible for requirements analysis, and for applying and evaluating the Dyn-SAVE tool and method. The PI and a group of FC-MD scientists were responsible for improving the method and conducting outreach activities, while another group of FC-MD scientists were responsible for development and improvement of the tool. Oversight and reporting was conducted by the PI and NASA POC. The project team produced many results including several prototypes of the Dyn-SAVE tool and method, several case studies documenting how the tool and method was applied to APL s software systems, and several published papers in highly respected conferences and journals. Dyn-SAVE as developed and enhanced throughout this research period, is a software tool intended for software developers and architects, software integration testers, and persons who need to analyze software systems from the point of view of how it communicates with other systems. Using the tool, the user specifies the planned communication behavior of the system modeled as a sequence diagram. The user then captures and imports the actual communication behavior of the system, which is then converted and visualized as a sequence diagram by Dyn-SAVE. After mapping the planned to the actual and specifying parameter and timing constraints, Dyn-SAVE detects and highlights deviations between the planned and the actual behavior. Requirements based on the need to analyze two inter-system communication protocols that are representative of protocols used in the Aerospace industry have been specified. The protocols are related: APL s Common Ground System (CGS) as used in the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) and the Radiation Belt Space Probes (RBSP) missions. The analyzed communications were implementations of the Telemetry protocol and the CCSDS File Delivery Protocol (CFDP) protocol. Based on these requirements, three prototypes of Dyn-SAVE were developed and applied to these protocols. The application of Dyn-SAVE to these protocols resulted in the detection of several issues. Dyn-SAVE was also applied to several Testbeds that have previously been used for experimentation earlier on this project, as well as, to other protocols and logs for testing its broader applicability. For example, Dyn-SAVE was used to analyze 1) the communication pattern between a web browser and a web server, 2) the system log of a computer in order to detect offnominal computer shut-down behavior, and 3) the actual test cases of NASA Goddard s Core Flight System (CFS) and automatically generated test cases in order to determine the overlap between the two sets of test cases. In all cases, Dyn-SAVE assisted in providing insightful conclusions about each of the cases identified above.

Lindvall, Mikael↗

Violation of the Vogt-Russell theorem for homogeneous nondegenerate stars

A systematic study is made of the number and types of solutions of the equilibrium equations of stellar structure, in the case of homogeneous stars of Population I over the mass range 2-1000 solar masses, with four different opacity representations. A variant of the usual fitting method permits the simultaneous investigation of convergence and tendency toward multiplicity of the solutions. Quadratic interpolation and extrapolation of Carson's new opacity tables produces a very large opacity at low temperatures that greatly affects the loose outer layers of massive stars, while leaving the cores practically unaffected. As a result, over a small mass range, well above 100 solar masses, triple solutions exist, always near an effective temperature of log Te = 4.73. A simple classification of the known exceptions to the Vogt-Russell theorem on the uniqueness of stellar structure is given.

Stothers, R.↗

Observations and theory of Mg II lines in early type stars. II - Theory and predicted profiles. III - The observations and a comparison with the predictions

Profiles of the UV Mg II lines in the spectra of early type stars are computed in a grid of model atmospheres with effective temperatures between 8000 and 35,000 K and log g values of 2.5 to 4.0 using the LTE and non-LTE theories of line formation. The theoretical results indicate that the line cores are strengthened by non-LTE effects over the entire temperature range, resonance-line wings are weaker in the cooler models than in the LTE case, and very large deviations from LTE occur in the hot low-gravity models. These predictions are compared with the equivalent widths of the UV Mg II lines in 106 stars and of the visual lines in 48 stars (spectral types O4 to A3). The observed equivalent widths of normal stars in luminosity classes II through V are found to agree with the predictions over the entire range from O8 to A2 if a certain Mg/H abundance is adopted. The line intensities observed in supergiants, Be, Bp, and Ap stars are discussed.

Snijders, M. A. J.↗