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At least 541 records · Page 30

Opening-mode fracturing and cementation during hydrocarbon generation in shale: An example from the Barnett Shale, Delaware Basin, West Texas

Relative timing of fracturing is a key input for predictive fracture models, but timing information for fractures is commonly difficult to obtain. In this study, we used crosscutting relations and fluid inclusion assemblage temperatures from fracture cements from a few well-documented sampled fractures, combined with a one-dimensional burial history model, to establish timing for three generations of opening-mode fractures in a Barnett Shale core from the southern part of the Delaware Basin, Pecos County, West Texas. A burial history model is presented for the cored well and matched to measured vitrinite reflectance in samples from the core, and bottomhole temperature in the well. Here, the earliest fractures (group 1) likely formed due to early fluid-expulsion events (ca. 300 Ma) and were folded during host-rock compaction. Later group 2 fractures are sealed with fibrous barite containing primary, liquid hydrocarbon inclusions (mean homogenization temperature [T h ] = –9°C) and aqueous fluid inclusions (mean T h = 108.1°C). Group 2 fractures likely formed in response to fluid overpressure associated with cracking of type II kerogen to oil. Group 3 vertical fractures are up to 2 m in height with kinematic apertures ranging from less than 0.05 to 1.4 mm, partly open, and strike dominantly 010°–020°. Sequentially trapped aqueous fluid inclusions in fracture-spanning quartz cement bridges (mean T h = 110°C in crack-seal texture and 128°C in post-crack-seal fracture cement) record fracture opening under increasing temperature, inferred to reflect increasing burial, with continued overpressuring during the Triassic to Late Cretaceous. Some group 3 fractures may have continued to fill during Cenozoic uplift.

02 PETROLEUM↗

Salt Diapir‐Driven Recycling of Gas Hydrate

Abstract By harnessing both hypothetical, synthetic basin and gas hydrate (GH) system models and real‐world models of well‐studied salt diapir‐associated GH sites at Green Canyon (Gulf of Mexico) and Blake Ridge (U.S. Atlantic coast), we propose and demonstrate salt movement (and in particular, diapirism) to be a new mechanism for the recycling of marine GH. At Green Canyon, for example, we show that by considering this newly proposed diapir‐driven recycling mechanism in conjunction with previously proposed lithological control on sandy‐reservoir‐hosted hydrate at the base of the GH stability zone (BGHSZ; ∼bottom‐simulating reflector, BSR), modeled GH saturations match drilling data. Overall, salt diapir movement‐induced GH recycling provides a temperature‐driven mechanism by which GH saturations at the BGHSZ may reach >90 vol. % and by which GH volumes near and free gas volumes beneath the BGHSZ may be increased significantly through time. Interestingly, comparison of salt diapir‐driven recycling and sediment burial‐driven recycling scenarios suggests notably higher rates of recycling via diapir‐driven versus burial‐driven processes. Our results suggest that GH and associated free gas accumulations above salt diapir crests represent particularly attractive targets for unconventional and conventional hydrocarbon resource exploration and for scientific and academic drilling expeditions aimed at exploiting GH systems. Salt basins containing GH systems—including passive margin basins of the Gulf of Mexico, southeastern Brazil, and southwestern Africa—are therefore compelling localities for studying salt‐driven GH recycling and for salt diapir‐associated natural gas exploration.

58 GEOSCIENCES↗

Applying 3D Geologic Modeling Workflows to the Argillite Reference Case (Rev. 1)

The objective of this short report is to document the application of our 3D geologic modeling workflow to an argillite (shale) host rock. Over the past four years, our team at Los Alamos National Laboratory has developed a geologic modeling workflow that can be applied to generic alluvial basins such as those found in the western United States. In “frontier” or “exploratory” basins where data are sparse, the first steps are to collect, evaluate and integrate available subsurface data into conceptual geologic models. Those models form the basis for constructing the geologic framework model, a 3D geocellular model ideally constrained by seismic and borehole data. To date we have constructed our models using “synthetic” well data derived from conceptual models, without the prospect of validating our workflow using “real” subsurface data. We were tasked to investigate whether our workflow designed for alluvial basin sediments could be applied to other potential repository host rocks. This task also provided the opportunity to work with high-quality subsurface data collected specifically for siting and evaluating a nuclear waste repository. Nagra, the Swiss governmental agency responsible for the disposal of the nation’s radioactive waste, generously provided us with data from two deep boreholes drilled through their argillaceous target formation. The aim of our proof-of-concept demonstration is to evaluate whether geostatistical methods offer a viable approach to property modeling in argillaceous rocks. Nagra provided us with the well data on the condition that we maintain confidentiality with all transferred information and results. Fortunately, Nagra posts numerous technical reports on its public website that describe the subsurface geology in great detail. All of the information and illustrations in this report related to the Swiss repository enterprise are taken from the Nagra public website.

58 GEOSCIENCES↗

Contrasting Indian Ocean SST Variability With and Without ENSO Influence: A Coupled Atmosphere-Ocean GCM Study

In this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO's influence on the interannual sea surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSOs influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3-5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin- wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east-west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.

Yu, Jin-Yi↗

Managing well leakage risks at a geologic carbon storage site with many wells

Potential geologic carbon storage (GCS) sites with a history of oil and gas production have well-characterized injectivity and storage capacity, but the presence of legacy wells increases leakage risk. Thus, the success of GCS operations at sites with many wells will require a thorough leakage risk assessment and a robust strategy for managing well leakage risk over the lifetime of the project. In this study, we demonstrate a workflow that uses the National Risk Assessment Partnership’s open-source Integrated Assessment Model to quantify well leakage risks and test the performance of various leakage risk management strategies at a heavily drilled GCS site. Here, our model simulates a 50-year basin-scale injection of CO 2 at a hypothetical site based on the Kimberlina Project Site in the Southern San Joaquin Valley of California. Brine and CO 2 leakage through 1,000 legacy wells into a USDW are stochastically simulated as a proxy for risk. We consider multiple scenarios that explore the efficacy of various well leakage risk management strategies with changes in well leakage behavior, reservoir behavior, and post-injection site care (PISC) length. Predicted leakage at the site after 100 years was small with a maximum CO 2 leakage of 102.1 tonnes (4.08×10 -5 % of the 250 Mt injected) and a maximum brine leakage of 2.4 tonnes. Leakage risk management strategies based on accurate prior information about well leak probability reduced leakage risks more effectively at the modeled site and were more robust with respect to reservoir uncertainty than strategies based on the distance of the legacy well from the injector. The importance of the PISC period length was not clear as it had a negligible impact on CO 2 leakage risk but a sizable impact on brine leakage risk in our model.

58 GEOSCIENCES↗

On Estimating Provenances of Lunar Highland Materials

That even relatively small impacts can spread material across the face of the Moon is evident from the rays of Tycho. Tycho ejecta triggered the landslide that produced the light mantle deposit at Apollo 17 and perhaps excavated the Central Valley craters there. Basin-sized impacts appear to follow the same scaling laws as smaller impacts, as indicated by the satisfaction of a geophysical model. These giant impacts rearranged huge amounts of premare material, complicating the determination of provenance of materials collected from the highlands. We have developed a model to estimate the probability that material at a particular location might derive from a given basin or large crater. This model is based on crater scaling laws, and effects of secondary cratering. Because it accounts for the volume of primary ejecta from the basin-forming transient craters and the excavating and mixing effects of these ejecta with the substrate onto which they fall, it gives much thicker deposits than an early work. Our modeling takes into account the distribution of sizes of primary ejecta fragments (PriFrags) to obtain the probability at a given site for a deposit of a particular thickness and with a fraction of PriFrags.

Haskin, Larry A.↗

Volume of Impact Melt Generated by the Formation of the South Pole-Aitken Basin

The South Pole-Aitken Basin (SPA) is the largest, deepest, and oldest identified basin on the Moon and as such contains surfaces that are unique due to their age, composition, and depth of origin in the lunar crust [1-5] (Figure 1). SPA has been a target of intense interest as an area for robotic sample return in order to determine the age of the basin and the composition and origin of its interior [6-8]. In response to this interest there have been several efforts to estimate the likely provenance of regolith material within central SPA [9-12]. These model estimates suggest that, despite the formation of basins and craters following SPA, the regolith within SPA is dominated by locally derived material. An assumption of these models has been that the locally derived material is primarily SPA impact-melt as opposed to local basement material (e.g. unmelted lower crust). However, the definitive identification of SPA derived impact melt on the basin floor, either by remote sensing [5, 13] or via photogeology [2, 14] is extremely difficult due to the number of subsequent impacts and volcanic activity [4].

Petro, Noah E.↗

Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning

Recently, rainfall-runoff simulations in small headwater basins have been improved by methodological advances such as deep neural networks (NNs) and hybrid physics-NN models—particularly, a genre called differentiable modeling that intermingles NNs with physics to learn relationships between variables. However, hydrologic routing simulations, necessary for simulating floods in stem rivers downstream of large heterogeneous basins, had not yet benefited from these advances and it was unclear if the routing process could be improved via coupled NNs. We present a novel differentiable routing method (δMC-Juniata-hydroDL2) that mimics the classical Muskingum-Cunge routing model over a river network but embeds an NN to infer parameterizations for Manning's roughness (n) and channel geometries from raw reach-scale attributes like catchment areas and sinuosity. The NN was trained solely on downstream hydrographs. Synthetic experiments show that while the channel geometry parameter was unidentifiable, n can be identified with moderate precision. With real-world data, the trained differentiable routing model produced more accurate long-term routing results for both the training gage and untrained inner gages for larger subbasins (>2,000 km2) than either a machine learning model assuming homogeneity, or simply using the sum of runoff from subbasins. The n parameterization trained on short periods gave high performance in other periods, despite significant errors in runoff inputs. The learned n pattern was consistent with literature expectations, demonstrating the framework's potential for knowledge discovery, but the absolute values can vary depending on training periods. The trained n parameterization can be coupled with traditional models to improve national-scale hydrologic flood simulations.

54 ENVIRONMENTAL SCIENCES↗

Integrating a reservoir regulation scheme into a spatially distributed hydrological model

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, natural streamflow timing and magnitude have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land use/land cover and climate changes. To understand the fine scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is of desire. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Model (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM model was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficients of determination (R2) and the Nash-Sutcliff Efficiency (NSE) are 0.85 and 0.75, respectively. These results suggest that this reservoir module has promise for use in sub-monthly hydrological simulations. Enabled with the new reservoir component, the DHSVM model provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.

Zhao, Gang↗

HPC-enabled computation of demand models at scale

The purpose of this project is to examine the energy impact of urban-scale traffic for the Los Angeles Basin by developing and implementing a scalable traffic assignment model. An energy optimization function will be posed and when integrated into the optimization code for travel assignment it can be mathematically proven to converge. The energy optimization function can then be compared to the typical travel time optimization that is traditionally used in traffic assignment models. The analysis will begin with static traffic assignment models with the routing for all origin and destinations computed in parallel on high performance computing facilities. Convergence of the numerical methods rely on the solution of convex programs (or extensions of these). This step will mostly consist of demonstrating the ability to parallelize the Frank Wolfe algorithm on various platforms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Deep Structure of Lunar Basins: Clues to the Understanding of Basin Formation and Modification

Basin excavation has played a major role in shaping the surface and subsurface of the Moon. Though photogeologic observations provide estimates for the present volumes of lunar impact basins and their ejecta deposits, there is not sufficient information to describe completely either the geometry of the basins at the time of impact or their modification with time. Determination of the structure of the crust and upper mantle beneath large basins can provide important insight into the thermal and mechanical processes associated with basin formation and modification as well as the differences in these processes as functions of basin age and size. Using observed gravity and topography together with the seismically determined crustal thickness of the central nearside, a model for the structure of the crust and upper mantle of the nearside of the Moon is presented. With this model the deep structure of the largest lunar basins are compared. The implications for the processes of basin formation and modification at different stages in lunar history are explored.

Bratt, S. R.↗

Ejecta from large craters on the moon - Comments on the geometric model of McGetchin et al

Amendments to a quantitative scheme developed by T. R. McGetchin et al. (1973) for predicting the distribution of ejecta from lunar basins yield substantially thicker estimates of ejecta, deposited at the basin rim-crest and at varying ranges beyond, than does the original model. Estimates of the total volume of material ejected from a basin, illustrated by Imbrium, also are much greater. Because many uncertainties affect any geometric model developed primarily from terrestrial analogs of lunar craters, predictions of ejecta thickness and volume on the moon may range within at least an order of magnitude. These problems are exemplified by the variability of T, thickness of ejecta at the rim-crest of terrestrial experimental craters. The proportion of T to crater rim-height depends critically upon scaled depth-of-burst and whether the explosive is nuclear or chemical.

Pike, R. J.↗

Identifying and Mitigating Potential Nutrient and Sediment Hot Spots under a Future Scenario in the Missouri River Basin

Using the Soil and Water Assessment Tool (SWAT) for large-scale watershed modeling could be useful for evaluating the quality of the water in regions that are dominated by nonpoint sources in order to identify potential “hot spots” for which mitigating strategies could be further developed. An analysis of water quality under future scenarios in which changes in land use would be made to accommodate increased biofuel production was developed for the Missouri River Basin (MoRB) based on a SWAT model application. The analysis covered major agricultural crops and biofuel feedstock in the MoRB, including pasture land, hay, corn, soybeans, wheat, and switchgrass. The analysis examined, at multiple temporal and spatial scales, how nitrate, organic nitrogen, and total nitrogen; phosphorus, organic phosphorus, inorganic phosphorus, and total phosphorus; suspended sediments; and water flow (water yield) would respond to the shifts in land use that would occur under proposed future scenarios. The analysis was conducted at three geospatial scales: (1) large tributary basin scale (two: Upper MoRB and Lower MoRB); (2) regional watershed scale (seven: Upper Missouri River, Middle Missouri River, Middle Lower Missouri River, Lower Missouri River, Yellowstone River, Platte River, and Kansas River); and (3) eight-digit hydrologic unit (HUC-8) subbasin scale (307 subbasins). Results showed that subbasin-level variations were substantial. Nitrogen loadings decreased across the entire Upper MoRB, and they increased in several subbasins in the Lower MoRB. Most nitrate reductions occurred in lateral flow. Also at the subbasin level, phosphorus in organic, sediment, and soluble forms was reduced by 35%, 45%, and 65%, respectively. Suspended sediments increased in 68% of the subbasins. The water yield decreased in 62% of the subbasins. In the Kansas River watershed, the water quality improved significantly with regard to every nitrogen and phosphorus compound. The improvement was clearly attributable to the conversion of a large amount of land to switchgrass. The Middle Lower Missouri River and Lower Missouri River were identified as hot regions. Further analysis identified four subbasins (10240002, 10230007, 10290402, and 10300200) as being the most vulnerable in terms of sediment, nitrogen, and phosphorus loadings. Overall, results suggest that increasing the amount of switchgrass acreage in the hot spots should be considered to mitigate the nutrient loads. The study provides an analytical method to support stakeholders in making informed decisions that balance biofuel production and water sustainability.

land use change↗

Constrained curve fitting for semi-parametric models with radial basis function networks

Common to many analysis pipelines in lattice gauge theory and the broader scientific discipline is the need to fit a semi-parametric model to data. We propose a fit method that utilizes a radial basis function network to approximate the non-parametric component of such models. The approximate parametric model is fit to data using the basin hopping global optimization algorithm. Parameter constraints are enforced through Gaussian priors. The viability of our method is tested by examining its use in a finite-size scaling analysis of the $q$-state Potts model and $p$-state clock model with $q=2,3$ and $p=4,\infty$.

Peterson, Curtis T.↗

A modeling study of tidal energy extraction and the associated impact on tidal circulation in a multi-inlet bay system of Puget Sound

Previous tidal energy projects in Puget Sound have focused on major deep channels such as Admiralty Inlet that have a larger power potential but pose greater technical challenges than minor tidal channels connecting to small sub-basins. This paper focuses on the possibility of extracting energy from minor tidal channels by using a hydrodynamic model to quantify the power potential and the associated impact on tidal circulation. The study site is a multi-inlet bay system connected by two narrow inlets, Agate Pass and Rich Passage, to the Main Basin of Puget Sound. A three-dimensional hydrodynamic model was applied to the study site and calibrated for tidal elevations and currents. We examined three energy extraction scenarios in which turbines were deployed in each of the two passages and concurrently in both. Extracted power rates and associated changes in tidal elevation, current, tidal flux, and residence time were examined. Maximum instantaneous power rates reached 250 kW, 1550 kW, and 1800 kW, respectively, for the three energy extraction scenarios. The model suggests that with the proposed level of energy extraction, the impact on tidal circulation is very small. It is worth investigating the feasibility of harnessing tidal energy from minor tidal channels of Puget Sound.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling the seasonal variability of a coupled Arctic ice-ocean system

The seasonal variability of the ice-ocean system in the Arctic Basin and the Norwegian, Greenland, and Barents Seas was modeled using a three-dimensional coupled ice-ocean model developed at Princeton University. The snow-ice model uses a three-level thermodynamic scheme similar to Semtner's (1976), but is extended to include the effect of leads. It is shown that simulations using the climatological monthly forcing fields produce a realistic seasonal variability of the ice cover. The ice thickness had a considerable sensitivity to the choice of the long-wave back radiation scheme, but these effects can be reduced through dynamical factors.

Hakkinen, Sirpa↗

Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.

54 ENVIRONMENTAL SCIENCES↗

Characterizing the Spatial and Temporal Distribution of Aerosol Optical Thickness Over the Atlantic Basin Utilizing GOES-8 Multispectral Data

In recent years, modeling and analysis efforts have suggested that the direct and indirect radiative effects of both anthropogenic and natural aerosols play a major role in the radiative balance of the earth and are an important factor in climate change calculations. The direct effects of aerosols on radiation and indirect effects on cloud properties are not well understood at this time. In order to improve the characterization of aerosols within climate models it is important to accurately parameterize aerosol forcing mechanisms at the local, regional, and global scales. This includes gaining information on the spatial and temporal distribution of aerosols, transport regimes and mechanisms, aerosol optical thickness, and size distributions. Although there is an expanding global network of ground measurements of aerosol optical thickness and size distribution at specific locations, satellite data must be utilized to characterize the spatial and temporal extent of aerosols and transport regimes on regional and global scales. This study was part of a collaborative effort to characterize aerosol radiative forcing over the Atlantic basin associated with the following three major aerosol components in this region: urban/sulfate, Saharan dust, and biomass burning. In-situ ground measurements obtained by a network of sun photometers during the Smoke Clouds and Radiation Experiment in Brazil (SCAR-B) and the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) were utilized to develop, calibrate, and validate a Geostationary Operational Environmental Satellite (GOES)-8 aerosol optical thickness (AOT) product. Regional implementation of the GOES-8 AOT product was used to augment point source measurements to gain a better understanding of the spatial and temporal distributions of Atlantic basin aerosols during SCAR-B and TARFOX.

Fox, Robert↗