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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

The Potosi Reservoir Model 2013c, Property Modeling Update

As part of a larger project co-funded by the United States Department of Energy (US DOE) to evaluate the potential of formations within the Cambro-Ordovician strata above the Mt. Simon as potential targets for carbon sequestration in the Illinois and Michigan Basins, the Illinois Clean Coal Institute (ICCI) requested Schlumberger to evaluate the potential injectivity and carbon dioxide (CO2) plume size of the Cambrian Potosi Formation. The evaluation of this formation was accomplished using wireline data, core data, pressure data, and seismic data from this project as well as two other separately funded projects: the US DOE-funded Illinois Basin–Decatur Project (IBDP) being conducted by the Midwest Geological Sequestration Consortium (MGSC) in Macon County, Illinois, and the Illinois Industrial Carbon Capture and Sequestration (ICCS) project funded through the American Recovery and Reinvestment Act. In 2010, technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the Verification Well #1 (VW1) and the Injection Well (CCS1), structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. The intention was for 2.2 million tons per annum (2 million tonnes per annum [MTPA]) of CO2 to be injected for 20 years. In the Task Error! Reference source not found., the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010") was re-run using a new injection scenario of 3.5 million tons per annum (3.2 MTPA) for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. The models size was insufficient to accommodate the evolution of the plume. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 by 30 mi (48 by 48 km), while preserving all property modeling workflows and layering. This model was retained as the base case. In the preceding Task [1], the Potosi reservoir model was updated to take into account the new data from the Verification Well #2 (VW2) which was drilled in 2012. The porosity and permeability modeling was revised to take into account the log data from the new well. Revisions of the 2010 modeling assumptions were also done on relative permeability, capillary pressures, formation water salinity, and the maximum allowable well bottomhole pressure. Dynamic simulations were run using the injection target of 3.5 million tons per annum (3.2 MTPA) for 30 years. This dynamic model was named Potosi Dynamic Model 2013b. In this Task, a new property modeling workflow was applied, where seismic inversion data guided the porosity mapping and geobody extraction. The static reservoir model was fully guided by PorosityCube interpretations and derivations coupled with petrophysical logs from three wells. The two main assumptions are: porosity features in the PorosityCube that correlate with lost circulation zones represent vugular zones, and that these vugular zones are laterally continuous. Extrapolation was done carefully to populate the vugular facies and their corresponding properties outside the seismic footprint up to the boundary of the 30 by 30 mi (48 by 48 km) model. Dynamic simulations were also run using the injection target of 3.5 million tons per annum (3.2 MTPA) for 30 years. This new dynamic model was named Potosi Dynamic Model 2013c. Reservoir simulation with the latest model gives a cumulative injection of 43 million tons (39 MT) in 30 years with a single well, which corresponds to 40% of the injection target. The injection rate is approx. 3.2 MTPA in the first six months as the well is injecting into the surrounding vugs, and declines rapidly to 1.8 million tons per annum (1.6 MTPA) in year 3 once the surrounding vugs are full and the CO2 start to reach the matrix. After, the injection rate declines gradually to 1.2 million tons per annum (1.1 MTPA) in year 18 and stays constant. This implies that a minimum of three (3) wells could be required in the Potosi to reach the injection target. The injectivity evaluated in this Task was higher compared to the preceding Task, since the current facies modeling (guided by the porosity map from the seismic inversion) indicated a higher density of vugs within the vugular zones. 5 As the CO2 follows the paths where vugs interconnection exists, a reasonably large and irregular plume extent was created. After 30 years of injection, the plume extends 13.7 mi (22 km) in E-W and 9.7 mi (16 km) in N-S directions. After injection finishes, the plume continues to migrate laterally, mainly driven by the remaining pressure gradient. After 60 years post-injection, the plume extends 14.2 mi (22.8 km) in E-W and 10 mi (16 km) in N-S directions, and remains constant as the remaining pressure gradient has become very low. Should the targeted cumulative injection of 106 million tons (96 MT) be achieved; a much larger plume extent could be expected. The increase of reservoir pressure at the end of injection is approximately 1,200 psia (8,274 kPa) around the injector and gradually decreases away from the well. The reservoir pressure increase is less than 10 psia (69 kPa) beyond 14 mi (23 km) away from injector. Should the targeted cumulative injection of 106 million tons (96 MT) be achieved; a much larger areal pressure increase could be expected. The reservoir pressure declines rapidly during the first 30 years post injection and the initial reservoir pressure is nearly restored after 100 years post-injection. The present evaluation is mainly associated with uncertainty on the vugs permeability and interconnectivity. The use of porosity mapping from seismic inversion might have reduced the uncertainty on the lateral vugs body distributions. However, major uncertainties on the Potosi vugs permeability remains. Therefore, injection test and pressure interference test among the wells could be considered to evaluate the local vugs permeability, extent, and interconnectivity. Facies modeling within the Potosi has yet to be thoroughly addressed. The carbonates during the time of deposition are believed to be regionally extensive. However, it may be worth delineating the reservoir with other regional wells or modern day analogues to understand the extent of the Potosi. More specifically, the model could incorporate lateral changes or trends if deemed necessary to represent facies transition. Data acquisitions to characterize the fracture pressure gradient, the formation water properties, the relative permeability, and the capillary pressure could also be considered in order to allow a more rigorous evaluation of the Potosi storage performance. A simulation using several injectors could also be considered to determine the required number of wells and appropriate spacing to achieve the injection target while taking into account the pressure interference.

Adushita, Yasmin↗
DOE OSTI2013

Gnawts

High Performance Computing (HPC) systems generate millions of inter-related event log lines per day from thousands of computers, providing feedback on both successful and unsuccessful operations within the system. Thorough analysis of these logs is often required for root cause analysis of problems and tuning for greatest performance. This "app" for the "Gnawts" log analysis software (http://www.gnawts.com) facilitates faster and deeper insights into HPC system logs.

Jon Stearley, Charles Snider↗
DOE OSTI2016

Cloud object store for checkpoints of high performance computing applications using decoupling middleware

Cloud object storage is enabled for checkpoints of high performance computing applications using a middleware process. A plurality of files, such as checkpoint files, generated by a plurality of processes in a parallel computing system are stored by obtaining said plurality of files from said parallel computing system; converting said plurality of files to objects using a log structured file system middleware process; and providing said objects for storage in a cloud object storage system. The plurality of processes may run, for example, on a plurality of compute nodes. The log structured file system middleware process may be embodied, for example, as a Parallel Log-Structured File System (PLFS). The log structured file system middleware process optionally executes on a burst buffer node.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A New Record Census of Dwarf AGN and a Bimodal $M_{\rm BH}$-$M_{\star}$ Scaling Relation with DESI DR1

Using the first spectroscopic data release from the Dark Energy Spectroscopic Instrument (DESI DR1), we search for AGN signatures in 1,678,787 low-redshift ($0.001 \le z \le 0.45$) line-emitting galaxies. Based on the [NII]-BPT emission-line ratio diagnostic, we identify AGN in 314,245/1,211,573 (25.9%) high-mass ($\log (M_{\star}/M_{\odot}) > 9.5$) and 9648/467,214 (2.1%) dwarf ($\log (M_{\star}/M_{\odot}) \le 9.5$) galaxies. Among these AGN, 17,949 are broad-line candidates (BL-AGN) with broad H$α$ emission, enabling black hole (BH) mass estimates using single-epoch virial methods. We find that the AGN fraction in line-emitting galaxies increases monotonically with stellar mass, rising from $\sim$1.4% at the low-mass end to $\sim$93.3% at the high-mass end. Using the large BL-AGN sample, we extend the $M_{\rm BH} - M_{\star}$ scaling relation down to $\log (M_{\star}/M_{\odot}) \approx 7.8$ and $\log (M_{\rm BH}/M_{\odot}) \approx 4.4$. In the context of high-redshift overmassive BHs, our results suggest that galaxies and their central BHs may follow two distinct evolutionary pathways across cosmic time. With this paper, we release the EmFit value-added catalog, containing emission-line flux and width measurements for $\sim$7.4 million galaxies, the largest catalog with emission-line decomposition into narrow, broad, and outflow components to date. This work significantly expands upon the early DESI results and provides a statistical sample for probing the galaxy$-$BH connection in the low-mass galaxy regime.

Pucha, Ragadeepika [Utah U.; Arizona U., Astron. D↗
DOE OSTI2010

EFFECT OF TEMPERATURE AND HUMIDITY ON FORMALDEHYDE EMISSIONS IN TEMPORARY HOUSING UNITS

The effect of temperature and humidity on formaldehyde emissions from samples collected from temporary housing units (THUs) was studied. The THUs were supplied by the U.S Federal Emergency Management Administration (FEMA) to families that lost their homes in Louisiana and Mississippi during the Hurricane Katrina and Rita disasters. Based on a previous study 1, 2, four of the composite wood surface materials that dominated contributions to indoor formaldehyde were selected to analyze the effects of temperature and humidity on the emission factors. Humidity equilibration experiments were carried out on two of the samples to determine how long the samples take to equilibrate with the surrounding environmental conditions. Small chamber experiments were then conducted to measure emission factors for the four surface materials at various temperature and humidity conditions. The samples were analyzed for formaldehyde via high performance liquid chromatography. The experiments showed that increases in temperature or humidity contributed to an increase in emission factors. A linear regression model was built using natural log of percentage relative humidity (RH) and inverse of temperature (in K) as predictor variables, and natural log of emission factors as the target variable. The coefficients of both inverse temperature and log relative humidity with log emission factor were found to be statistically significant for all the samples at the 95percent confidence level. This study should assist to retrospectively estimate indoor formaldehyde exposures of occupants of temporary housing units (THUs).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

58 GEOSCIENCES↗
DOE OSTI2020

Hawthorne Nevada Deep Direct-Use Feasibility Study - Data Used for Geothermal Resource Conceptual Modeling and Power Capacity Estimates

This data submission includes several data components that were used to develop a conceptual model and power capacity-estimates of two low-temperature geothermal resources that define geothermal prospect A at Hawthorne, Nevada. Data are sourced from a combination of legacy publicly-available data and more recent data acquisition conducted by the US Navy Geothermal Program Office (2008-2013) and the Great Basin Center for Geothermal Energy at the University of Nevada, Reno (2008-2010). Data sets include compiled fluid geochemistry data, down-hole temperature logs for wells in the vicinity of prospect A, 2 meter temperature survey data, temperature-spinner logs acquired in well HWAAD-2A, fracture picks from image log data acquired in wells HWAAD-2 and HWAAD-3, and X-Ray Diffraction (XRD) analyses on cuttings from wells HWAAD-2A and HWAAD-3. These data have been reviewed for errors and inconsistencies, but it is possible that few errors could still remain. The resource conceptual model and power capacity estimates are included in the final report to the US Department of Energy, and are presented in a manuscript by Ayling and Hinz. A link to the manuscript published in Geothermics is linked below in this submission.

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

The hydrogen-poor superluminous supernova iPTF 13ajg and its host galaxy in absorption and emission

We present imaging and spectroscopy of a hydrogen-poor superluminous supernova (SLSN) discovered by the intermediate Palomar Transient Factory, iPTF 13ajg. At a redshift of z = 0.7403, derived from narrow absorption lines, iPTF 13ajg peaked at an absolute magnitude of M {sub u,} {sub AB} = –22.5, one of the most luminous supernovae to date. The observed bolometric peak luminosity of iPTF 13ajg is 3.2 × 10{sup 44} erg s{sup –1}, while the estimated total radiated energy is 1.3 × 10{sup 51} erg. We detect narrow absorption lines of Mg I, Mg II, and Fe II, associated with the cold interstellar medium in the host galaxy, at two different epochs with X-shooter at the Very Large Telescope. From Voigt profile fitting, we derive the column densities log N(Mg I) =11.94 ± 0.06, log N(Mg II) =14.7 ± 0.3, and log N(Fe II) =14.25 ± 0.10. These column densities, as well as the Mg I and Mg II equivalent widths of a sample of hydrogen-poor SLSNe taken from the literature, are at the low end of those derived for gamma-ray bursts (GRBs) whose progenitors are also thought to be massive stars. This suggests that the environments of hydrogen-poor SLSNe and GRBs are different. From the nondetection of Fe II fine-structure absorption lines, we derive a lower limit on the distance between the supernova and the narrow-line absorbing gas of 50 pc. The neutral gas responsible for the absorption in iPTF 13ajg exhibits a single narrow component with a low velocity width, ΔV = 76 km s{sup –1}, indicating a low-mass host galaxy. No host galaxy emission lines are detected, leading to an upper limit on the unobscured star formation rate (SFR) of SFR{sub [O} {sub II]}<0.07M{sub ⊙}yr{sup −1}. Late-time imaging shows the iPTF 13ajg host galaxy to be faint, with g {sub AB} ≈ 27.0 and R {sub AB} ≥ 26.0 mag, corresponding to M {sub B,} {sub Vega} ≳ –17.7 mag.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp Formation of the Permian (Delaware) Basin. This paper focuses on integration, advanced geological characterization, and 3D subsurface modeling of the comprehensive HFTS-2 dataset. The study showcases a multidisciplinary reservoir characterization approach that incorporates geology, petrophysics, geochemistry, geomechanics, microseismic, and subsurface engineering analysis. Subsurface characterization of organic-rich mudstone formations requires understanding complex hydraulic fracture network growth in relation to inherent lithology, geomechanical properties, and interaction with pre-existing natural fractures. This paper presents a characterization workflow incorporating pre- and post-stimulation subsurface data, unique to the HFTS-2 dataset. The study integrated: (1) rock properties from logs, cores, and thin sections; (2) natural and hydraulic fracture descriptions from cores and image logs; (3) local and regional stresses; (4) geomechanics; (5) microseismic; (6) fiber optic (FO) and bottomhole pressure gauge (BHPG) response; and (7) produced fluids analysis. During a stimulation treatment, creation of the stimulated rock volume (SRV) is influenced by several subsurface factors. Key contributing factors include structural context, stress conditions, lithology, facies architecture, pre-existing natural fractures, and geomechanical properties. The HFTS-2 subsurface data integration indicates that the SRV is comprised of a complex juxtaposition of hydraulic fracture swarms, as evidenced by image logs analysis, core description, and microseismic monitoring. The HFTS-2 microseismic event density was used to generate 3D heat maps that serve as a representative SRV footprint, corroborated by secondary datasets. These maps were further integrated with petrophysical and geomechanical characteristics, as well as responses from FO and BHPG, to estimate the lateral and vertical dimensions of the effective fractures. The geological characterization for the HFTS-2 dataset combined with 3D modeling for petrophysical and geomechanical properties provides a strong foundation for subsurface simulation and optimization studies. Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S005R001/2477501/urtec-2021-5243-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5243 The workflow improved our understanding of HFTS-2 hydraulic fracture propagation and characteristics in relation to offset pressure depletion and interaction with pre-existing natural fractures. Analysis showed that fracture geometry varies by stage and by well, and a complex fracture network is generated with varying fracture density. The multidisciplinary workflow presented herein for integration and characterization serves as a foundation to evaluate completion efficiency and estimate areal and vertical stimulation and depletion extent for the project. Furthermore, the workflow and learnings can also be transferred to other unconventional plays.

58 GEOSCIENCES↗
DOE OSTI2019

Offshore CO2 Saline Storage Assessment Dataset

Dataset containing 646 petrophysical well log interpretations spanning multiple geologic domains (as defined by Subsurface Trend Analysis™) in the Gulf of Mexico. Well logs were manually interpreted by geologic researchers at NETL and were derived from BOEM Sands and IHS data raster logs. This interpretation dataset underpins the Offshore CO2 Saline Storage Calculator.

Petrophyiscal↗
DOE OSTI2024

Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO2 Storage

The project Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO2 Storage 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 South Carolina Research Foundation and partners evaluated the feasibility of CCS in the Jurassic/ Triassic (J / TR) saline formations of the buried Mesozoic South Georgia Rift (SGR) Basin that extends from South Carolina into Georgia. The J / TR sequence, based on preliminary assessment of limited geologic and geophysical data, appears to have both the appropriate areal extent and multiple horizons to permanently and safely store CO2 The presence of several igneous rock layers within the sequence may potentially provide adequate seals to prevent upward CO2 migration into the Coastal Plain aquifer systems. Approximately 81 kilometers of 2-D seismic reflection data were collected by Bay Geophysical, Inc. to explore a portion of the SGR located in southern Georgia. The 81 kilometers were divided into two lines approximately 40.5 kilometers each, with Line 1 intersecting Georgia well GGS 3457. Line 2 intersects Line 1 at the southern portion of Line 1 to maximize the extent of coverage away from GGS-3457 (a deep well drilled in the 1980s for oil and gas exploration). This well had a set of usable logs, including gamma and neutron logs that provided promising results related to CO2 storage. Results showed sandstone with porosity values greater than 10 percent and a thickness of 120 meters. The design of the seismic shot was to extrapolate information away from the well and to better define the extent of the SGR and the necessary reservoir and caprock for a successful CO2 injection. A numerical simulation model of CO2 Injection and migration was developed based on the geology log for the GGS-3457 well. The simulation model was used to investigate the feasibility of injecting 30 million metric tons of CO2 into SGR J / TA sediments and integrity of the diabase layers as seals to prevent CO2 migration.

2-D seismic↗
DOE OSTI2024

Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region

The project Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region 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 Rocky Mountain Carbon Capture and Storage (RMCCS) project investigated multiple geologic formations and characterized a local site on the Colorado Plateau for future CCS opportunities. The RMCCS project focused on the Cretaceous Dakota, Jurassic Entrada, and Pennsylvanian Weber Sandstones, the three largest regional formations. All formations in this project are potential CO2 storage resources for future power plants, natural gas processing plants, cement plants, and oil shale development projects. The area adjacent to Craig, Colorado, (Sand Wash Basin) was the area selected for detailed geologic characterization on the RMCCS project. The basin was selected in part because the geology can be extrapolated to other sites on the Colorado Plateau. Field mapping and seismic surveys were conducted to identify and evaluate the basin's structural configuration. A 9,745-foot deep characterization well was drilled to collect 131 feet of core and a suite of geophysical well log data. Petrophysical tests on samples of core were used to calibrate geophysical log data, which can be used to obtain storage resource estimates and evaluate associated uncertainty as well as simulate the hydrologic behavior of injected CO2. A detailed analysis of the primary formations (Dakota, Entrada and Weber sandstones) yielded a more accurate CO2 storage resource assessment for these formations within the Colorado Plateau; RMCCS estimates indicate a total CO2 storage resource of more than 38,000 million metric tons. The characterization of the Sand Wash Basin (2-D seismic surveys, multiple well logs and lithological, petrophysical and geochemical analyses) allowed for a detailed 3-D model to be constructed. The model served as the framework for analyses ranging from CO2 storage resource, injectivity, and subsurface flow to uncertainty estimates to evaluation of risk.

2-D seismic↗
DOE OSTI2025

Predicting Dynamic-to-Static Correction Factor from Petrophysical Data and Chemostratigraphy using Unsupervised Machine Learning

Estimating static mechanical properties of stratigraphic layers is critical for optimizing subsurface engineering applications. To estimate dynamic-to-static correction factor F ds (static-to-dynamic Young’s modulus ratio) across the Caney shale interval in Oklahoma, USA, we integrated triaxial test measurements and petrophysical data, including well logs and X-ray fluorescence (XRF) using unsupervised machine learning (ML). We used a novel workflow that includes principal component analysis (PCA) to reduce data set dimensionality of well logs and XRF data sets—both separately and combined—creating three scenarios, and later applied inverse distance weighting (IDW) to derive F ds profiles for these scenarios. Furthermore, we applied K-means clustering on each scenario to predict depositional facies, and built a stiffness zonation profile through chemostratigraphic analysis of the terrigenous elements to validate the predicted F ds . The predicted F ds profile from each scenario using the PCA-IDW method was compared with the constant F ds approach from our previous study by calculating the root mean square error (RMSE). The combined data sets scenario yielded the lowest RMSE value of 0.113, while the RMSE values for the well logs and XRF scenarios were 0.131 and 0.129, respectively. In addition, the predicted F ds from the XRF scenario well-matched the stiffness zonation from the chemostratigraphic analysis that was built using the optimized K-means clustering of nine clusters for that scenario. These methods and findings offer a valuable tool for refining lithological classification and improving the F ds profile, potentially enhancing drilling and stimulation strategies for subsurface energy engineering applications.

clastic rock↗
DOE OSTI2016

Completion Report for Well ER-20-12: Corrective Action Units 101 and 102: Central and Western Pahute Mesa

Well ER-20-12 was drilled for the U.S. Department of Energy, Nevada National Security Administration Nevada Field Office in support of the Underground Test Area Activity. The well was drilled from October 2015 to January 2016 as an addition to the Central and Western Pahute Mesa corrective action units 101 and 102 the Phase II drilling program. Well ER-20-12 was identified based on recommendations of the Pahute Mesa Guidance Team as a result of anomalous tritium detections in groundwater samples collected from Well PM-3 in 2011 and 2013. The primary purpose of the well was to provide information on the hydrogeology in the area downgradient of select underground tests on Western Pahute Mesa and define hydraulic properties in the saturated Tertiary volcanic rocks. The main 46.99-centimeter (cm) (18.5-inch [in.]) borehole was drilled to a depth of 765.14 meters (m) (2,510.3 ft) and the hole opened to 66.04 cm (26 in.); followed by the 50.80-cm (20-in.) surface casing, which was installed and sealed with cement; and a piezometer (p4) was set in the Timber Mountain welded-tuff aquifer (TMWTA) between the casing and the open borehole. The borehole was continued with a 46.99-cm (18.5-in.) drill bit to a depth of 1,326.53 m (4,352.16 ft), and an intermediate 24.44-cm (9.625-in.) casing was installed and sealed to 1,188.72 m (3,900.00 ft) A piezometer (p3) was installed across the Calico Hills zeolitic composite unit (CHZCM) (lava-flow aquifer [LFA]) in the annulus of the open borehole. Two additional piezometers were installed and completed between the intermediate casing and the borehole wall, one (p2) in the CHZCM and one (p1) in the Belted Range aquifer (BRA). The piezometers are set to monitor groundwater properties in the completed intervals. The borehole was continued with a 21.59-cm (8.5-in.) drill bit to a total depth of 1,384.80 m (4,543.33 ft), and the main completion 13.97-cm (5.5-in.) casing was installed in the open borehole across the Pre-Belted Range composite unit (PBRCM). Data collected during hole construction include composite drill cutting samples collected every 3.0 m (10 ft), geophysical logs, hydrophysical logs, percussion core samples, water-quality measurements (including tritium), and water-level measurements. The well penetrated 1,384.4 m (4,543.33 ft) of Tertiary volcanic rocks. The stratigraphy and lithology were generally as expected with one noted exception. A thick lava-flow and related ash-flow tuffs were identified as Calico Hills Formation (Th), and no Crater Flat units were noted. Additionally, many of the Thirsty Canyon and Timber Mountain units were thicker than expected. Fluid levels measured in the borehole during drilling are the following: (1) on November 2, 2015, Navarro measured the fluid level in the borehole at a depth of 492.33 m (1,615.25 ft) below ground surface (bgs); (2) Schlumberger and COLOG recorded fluid levels during geophysical logging on November 4 and 5, 2015, at a depth of 492.86 m (1,617 ft) and 492.25 m (1,615 ft) bgs, respectively; and (3) on December 4, 2015, COLOG and Navarro measured fluid level in the 20-in. casing with an open borehole to 1,326.54 m (4,352.16 ft) bgs at 575.77 m (1,889.00 ft) and 574.03 m (1,883.3 ft) bgs, respectively. These and subsequent water-level measurements indicate a potential head difference of greater than 76.2 m (250 ft) for groundwater in aquifers above and below the Upper Paintbrush confining unit (UPCU). As expected, tritium was occasionally measured above the Safe Drinking Water Act limit (20,000 picocuries per liter [pCi/L]). Lab analysis on four bailed samples and taken from the undeveloped well indicate that the tritium activities average approximately 36,545 pCi/L. All Fluid Management Plan (FMP) requirements for Well ER-20-12 were met. Analysis of monitoring samples and FMP confirmatory samples indicate that fluids generated during drilling at ER-20-12 met the FMP criteria for discharge to the lined sump and designated infiltration area. All sanitary and hydrocarbon waste generated was properly handled and disposed of.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Learning Memento archive routing with Character-based Artificial Neural Networks

This white paper describes a series of tests that were performed to determine if a neural network could learn patterns from a service that maintains a cache of routing decisions for the discovery of version information for discrete web-at-large URLs. Labeled training data was derived from a log file that records the by-archive availability of Memento availability for a given URL. Training data sets were generated from this log file on a by-archive basis (thus making it a binary classification problem). Each training data set consisted of equal numbers of hit and miss URLs, selected at random. The URLs were converted to a normalized numeric representation where each integer in a URL training vector represents a character in that URL. The corresponding label indicates whether or not Mementos were available for that URL in the selected archive. The training data matrix and the label vector became input to a neural network. A number of neural network architectures and network hyperparameters were explored, however the log entries themselves were used as-is, without any feature engineering, beyond the aforementioned normalization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Training Restricted Boltzmann Machines With a D-Wave Quantum Annealer

Restricted Boltzmann Machine (RBM) is an energy-based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained using contrastive divergence (CD). However, training with CD is slow and does not estimate the exact gradient of the log-likelihood cost function. In this work, the model expectation of gradient learning for RBM has been calculated using a quantum annealer (D-Wave 2000Q), where obtaining samples is faster than Markov chain Monte Carlo (MCMC) used in CD. Training and classification results of RBM trained using quantum annealing are compared with the CD-based method. The performance of the two approaches is compared with respect to the classification accuracies, image reconstruction, and log-likelihood results. The classification accuracy results indicate comparable performances of the two methods. Image reconstruction and log-likelihood results show improved performance of the CD-based method. It is shown that the samples obtained from quantum annealer can be used to train an RBM on a 64-bit “bars and stripes” dataset with classification performance similar to an RBM trained with CD. Though training based on CD showed improved learning performance, training using a quantum annealer could be useful as it eliminates computationally expensive MCMC steps of CD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Preliminary Analysis of Stress in the Newberry EGS Well NWG 55-29

As part of the planning for stimulation of the Newberry Volcano Enhanced Geothermal Systems (EGS) Demonstration project in Oregon, a high-resolution borehole televiewer (BHTV) log was acquired using the ALT ABI85 BHTV tool in the slightly deviated NWG 55-29 well. The image log reveals an extensive network of fractures in a conjugate set striking approximately N-S and dipping 50° that are well oriented for normal slip and are consistent with surface-breaking regional normal faults in the vicinity. Similarly, breakouts indicate a consistent minimum horizontal stress, S hmin , azimuth of 092.3±17.3°. In conjunction with a suite of geophysical logs, a model of the stress magnitudes constrained by the width of breakouts at depth and a model of rock strength independently indicates a predominantly normal faulting stress regime.

15 GEOTHERMAL ENERGY↗