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At least 541 records · Page 30

Feeding and Feedback in the Powerful Radio Galaxy 3C 120

We present a spectral analysis of a 200-kilosecond observation of the broad-line radio galaxy 3C 120, performed with the high-energy transmission grating spectrometer on board the Chandra X-Ray Observatory. We find (i) a neutral absorption component intrinsic to the source with a column density of log N (sub H) equals 20.67 plus or minus 0.05 square centimeters; (ii) no evidence for a warm absorber (WA) with an upper limit on the column density of just log N (sub H) less than 19.7 square centimeters, assuming the typical ionization parameter log xi approximately equal to 2.5 ergs per second per centimeter; the WA may instead be replaced by (iii) a hot emitting gas with a temperature kT approximately equal to 0.7 kiloelectronvolts observed as soft X-ray emission from ionized Fe L-shell lines, which may originate from a kiloparsec-scale shocked bubble inflated by the active galactic nucleus (AGN) wind or jet with a shock velocity of about 1000 kilometers per second determined by the emission line width; (iv) a neutral Fe K alpha line and accompanying emission lines indicative of a Compton-thick cold reflector with a low reflection fraction R approximately equal to 0.2, suggesting a large opening angle of the torus; (v) a highly ionized Fe XXV emission feature indicative of photoionized gas with an ionization parameter log xi equal to 3.75 (sup plus 0.38) (sub minus 0.27) ergs per second per centimeter and a column density of log N (sub H) greater than 22 square centimeters localized within approximately 2 pc from the X-ray source; and (vi) possible signatures of a highly ionized disk wind. Together with previous evidence for intense molecular line emission, these results indicate that 3C 120 is likely a late-state merger undergoing strong AGN feedback.

black hole physics – galaxies: active – line: ↗

National Plan for the Disposal of Existing and Future TRU Wastes - 18616

Now that the Waste Isolation Pilot Plant (WIPP) has re-opened, after being down for three years due to an accident the DOE National TRU Program has re-developed a plan for the disposal of existing and future TRU wastes. The National TRU Waste Management Plan (NTWMP) is an integrated plan to address the needs of DOE sites across the DOE Weapons Complex that create and store TRU waste, and is centered on the capability of WIPP to receive and dispose of TRU waste. The WIPP capability is planned as a weekly shipping rate and is defined by emplacement and receipt rate capabilities since WIPP is not permitted for long-term storage. And, shipping rates may be constrained by new WIPP Waste Acceptance Criteria (WAC) and future plans for repository configurations and disposal package capabilities over the next 30 years. Since WIPP is the only disposal system available to the DOE for TRU waste disposal, DOE has a newly projected life-cycle need for WIPP to remain open and available up to 2050. It is projected that the need for WIPP will continue up to the year 2050 for the disposition of the remaining legacy TRU inventories and for the disposal of TRU waste continuing to be generated at DOE's National Laboratories. In addition, there are several other potential new waste streams in which WIPP is being considered an alternative solution for their disposition. The NTWMP has been updated to reflect the short-term and long-term plans for TRU waste disposal at WIPP. The short-term plan is used by DOE for budget projection and integration purposes to facilitate and inform budget planning, both in DOE's Environmental Management (EM) and National Nuclear Security Administration (NNSA) organizations. Most legacy TRU waste (generated in the past and stored at DOE sites today) is owned and managed by EM. And, EM submits integrated budget requests for DOE sites, including the integration of resources for TRU waste management. NNSA and DOE's Office of Science (OS) funds TRU waste management as part of their mission funding and NNSA should eventually be the primary user of the WIPP resources as EM's legacy TRU waste is cleaned-up. Prior to the unexpected shutdown of WIPP in 2014, there was a small back-log of waste certified for WIPP disposal and shipments of TRU waste to WIPP were 'just-in-time' as waste was certified. After three years of WIPP being down, DOE sites have built significant back-logs of TRU waste to be certified for WIPP. That back-log built up to over 25,000 containers of TRU waste during that three-year period (Table 1). The backlog included both Contact-Handled (CH) TRU waste and Remote-Handled (RH) TRU waste, and even though WIPP re-opened in April of 2017, it is only open for TRU waste containers that can be stacked on disposal room floors. Plans for changing RH waste disposal packages and methods are in-the-works, but are not yet mature enough for significant planning. In addition, the WIPP underground facilities are now partially contaminated with radioactive particulate, which significantly reduces the WIPP operational efficiencies as compared to 2014. With a large back-log of waste ready for WIPP disposal and limited throughput for WIPP disposal rates, the focus of the NTWMP is to prioritize the selection of TRU wastes from the various sites based on WIPP waste emplacement rates and shipping rates to WIPP. Some TRU waste sites have a significant need to be top priority for shipments to WIPP, and that must be balanced with the need for all TRU waste sites to have some shipments to deplete their back-log of TRU wastes. Storage and management of TRU waste is very costly for DOE and many of those resources could be used to optimize the overall disposition of TRU waste and save DOE significant funding. In addition, the plan will show the possible transition of TRU Waste Management from primarily being an EM function to being an NNSA function in the coming years. As legacy TRU waste inventories are removed, and as NNSA mission-related TRU waste inventories are produced, DOE will be faced with deciding where the primary responsibility for TRU waste management should reside. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluation of Drilling Performance at The Geysers with Machine Learning Methods Using Geologic Data

A recent well, GDC-36, was drilled in The Geysers Geothermal Field served in a Department of Energy-industry to demonstrate improved drilling performance with polycrystalline diamond compact (PDC) bits. Both PDC and roller cone drill bits were used to drill this well. Key challenges encountered during drilling included lost circulation in the mud-drilled section, and bit damage interfacial severity in the deeper, air-drilled section. The objective of this study is to evaluate the drilling performance in relation to the local geological characteristics using machine learning methods. By applying K-clustering to the sonic log data, we were able to identify areas correlated with measured lost circulation. Also, the boundaries defined by clustering of the mineralogical and lithological data from the mud logs correlate well with interfacial severity during drilling. A random forest model was employed to build correlation between drilling data and rock strength. The confined compressive strength (CCS) of the rock in the training of the machine learning model was inferred from the dipole sonic log. The R-squared of the testing data is 0.78, and the RMSE (Root Mean Squared Error) is 0.06. The trained model was used to forecast rock strength for the section where sonic log data are not available. CCS could also be inferred from mud logs provided the relationship between mineralogy and rock strength is established through core testing data.

15 GEOTHERMAL ENERGY↗

Utah FORGE 2439: Well 16B(78)-32 Field-Test Data from Mini-Frac Tests

This submittal includes the field-test data collected during stress tests conducted in the Utah FORGE 16B(78)-32 wellbore to measure/characterize the stresses in the geothermal reservoir. The type of stress test performed is referred to as a mini-frac test or a micro-frac test. The test is a hydraulic fracture test that involves injecting a small volume of water into a short interval of the reservoir that is isolated by a straddle packer to create a fracture. The test provides information about the minimum and maximum horizontal stress at the test depths. A total of seven mini-frac tests were performed within the upper (vertical or nearly vertical) section of the 9-5/8-inch diameter uncased wellbore, between depths of 5,202 ft MD [5,202 ft TVD] and 5,980 ft MD [5966.18 ft TVD]. Two types of data were generated as part of the mini-frac tests. The first type of data is time-series data for each mini-frac test (e.g., injection-rate, test-interval pressure), and are contained in the "Mini-Frac Test Data.zip" file below. The second type is geophysical log data, attached below in the "Geophysical Logs.zip" file. Here, two types of image logs and acoustic logs were obtained before and after the mini-frac tests to examine each test depth for visual evidence of induced fracture(s) and to measure the azimuth (orientation) of any observed fractures. The attached Readme file includes the test depth information and contents of each data file included here. Analysis of the field-test data was conducted and is documented in the attached report below.

15 GEOTHERMAL ENERGY↗

A probabilistic perspective on thermodynamic parameter uncertainties: Understanding aqueous speciation of mercury

Speciation plays an important role in determining the fate and transport of metals in terrestrial surface and subsurface systems. Equilibrium speciation modeling in aqueous systems relies on thermodynamic constants (log K values) of complexes, which are subject to uncertainties. In this study, using Monte Carlo (MC) simulations with Latin hypercube sampling (LHS) we systematically analyze the propagation of thermodynamic constant uncertainty through speciation modeling of an inorganic mercury-sulfide-chloride-water system. We find that seemingly small variances of the input log K normal distributions can lead to output species concentrations spanning multiple orders of magnitude, with highly skewed probability distributions. When equilibrium with mineral metacinnabar (β-HgS(s)) is neglected, the relative uncertainty of each output species is strongly positively correlated with the skewness of its concentration probability distribution, i.e., the lowest uncertainty occurs when the species concentration probability distribution is the most negatively skewed as its concentration approaches the total element concentration limit. The highest uncertainty in the identity of dominant species is located around species equivalence points. For cases where the mineral equilibrium is included, we derive analytical probability density functions for the log concentrations of all major species in the system. The mineral log K uncertainty is found to be an important contributor to all output concentration uncertainties. The analysis of combined effects of both pH and total sulfide concentration on output concentration uncertainties shows that high concentration uncertainties occur under highly sulfidic alkaline conditions and low uncertainties at low pH and sulfide concentrations. Finally, an analysis as presented here can distinguish between conditions that require a full uncertainty analysis and those for which the classical deterministic speciation modeling suffices.

58 GEOSCIENCES↗

Method to account for natural fracture induced elastic anisotropy in geomechanical characterization of shale gas reservoirs

Shale has been usually recognized as a transverse isotropic (TI) medium in conventional geomechanical log interpretation due to its laminated nature. However, when natural fractures exist in the shale rock, additional elastic anisotropy is introduced, converting laminated Shale to an orthorhombic (OB) medium. Previous studies illustrate that neglecting the natural fracture induced anisotropy in shale geomechanical log interpretation could lead to inaccurate evaluations of elastic moduli and in-situ stresses. In this paper, a new method is developed to account for the natural fracture induced anisotropy in geomechanical log interpretation based upon the TI acoustic model developed by the author and a characterization technique of elastic wave anisotropy (Sayers, 1991). The new OB model incorporates the four acoustic log data inputs and five modeling constraints in a nonlinear optimization algorithm to solve for the nine independent stiffness coefficients of an OB rock, and further to solve for the geomechanical properties and in-situ stress profiles in an OB formation. The new method was validated with a Marcellus Gas Shale field case. Both the new OB model and the conventional TI model were applied to interpret the minimum horizontal stress profile for the same formation. By comparing the results, the OB model is more robust than the TI from two aspects. First, the average stress magnitude predicted by the OB model is closer to the one measured by the Diagnostic Fracture Injection Test (DFIT). Second, the OB model predicts a more obvious stress barrier between the lower Marcellus and upper Onondaga Limestone than the TI model does. Finally, the predicted stress barrier is consistent with the observation of the microseismic events of a horizontal well drilled and completed nearby, which reveals that no hydraulic fracture propagates downward through the bottom boundary of Marcellus Shale into the underlying Onondaga Limestone.

03 NATURAL GAS↗

Forest structure and solar-induced fluorescence across intact and degraded forests in the Amazon

Tropical forest degradation (e.g., anthropogenic disturbances such as selective logging and fires) alters forest structure and function and influences the forest's carbon sink. In this study, we explored structure-function relationships across a variety of degradation levels in the southern Brazilian Amazon by 1) investigating how forest structural properties vary as a function of degradation history using airborne lidar data; 2) assessing the effects of degradation on solar-induced chlorophyll fluorescence (SIF) seasonality using TROPOMI data; and 3) quantifying the contribution of structural variables to SIF using multiple regression models with stepwise selection of lidar metrics. Forest degradation history was obtained through Landsat time-series classification. We found that fire, logging, and time since disturbance were major determinants of forest structure, and that forests affected by fires experienced larger variability in leaf area index (LAI), canopy height and vertical structure relative to logged and intact forests. Moreover, only recently burned forests showed significantly depressed SIF during the dry season compared to intact forests. Canopy height and the vertical distribution of foliage were the best predictors of SIF. Unexpectedly, we found that wet-season SIF was higher in active regenerating forests (~ 4 years after fires or logging) compared with intact forests, despite lower LAI. Furthermore, our findings help to elucidate the mechanisms of carbon accumulation in anthropogenically disturbed tropical forests and indicate that they can capture large amounts of carbon while recovering.

54 ENVIRONMENTAL SCIENCES↗

HST/COS detection of deuterated molecular hydrogen in a damped Lyα system at z = 0.18

We report on the detection of deuterated molecular hydrogen, HD, at z = 0.18. HD and H{sub 2} are detected in HST/COS data of a low-metallicity (Z ∼ 0.07 Z {sub ☉}) damped Lyα (DLA) system at z = 0.18562 toward QSO B0120–28, with log N(H I) = 20.50 ± 0.10. Four absorption components are clearly resolved in H{sub 2}, while two components are resolved in HD; the bulk of the molecular hydrogen is associated with the components traced by HD. We find total column densities log N(HD) = 14.82 ± 0.15 and log N(H{sub 2}) = 20.00 ± 0.10. This system has a high molecular fraction, f(H{sub 2}) = 0.39 ± 0.10, and a low HD-to-H{sub 2} ratio, log (HD/2H{sub 2}) = –5.5 ± 0.2 dex. The excitation temperature, T {sub 01} = 65 ± 2 K, in the component containing the bulk of the molecular gas is lower than in other DLAs. These properties are unlike those in other higher redshift DLA systems known to contain HD, but are consistent with what is observed in dense clouds in the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗

Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties on land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classification framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classification as well. Our classification approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classification significantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites. Our findings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classification. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specific pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fire. Both the attribution and uncertainty quantification provide critical information for national greenhouse gas inventories.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning Application to Assess Occurrence and Saturations of Methane Hydrate in Marine Deposits Offshore India

Artificial Neural Networks (ANN) were used to assess methane hydrate occurrence and saturation in marine sediments offshore India. The ANN analysis classifies the gas hydrate occurrence into three types: methane hydrate in pore space, methane hydrate in fractures, or no methane hydrate. Further, predicted saturation characterizes the volume of gas hydrate with respect to the available void volume. Log data collected at six wells, which were drilled during the India National Gas Hydrate Program Expedition 02 (NGHP-02), provided a combination of well log measurements that were used as input for machine learning (ML) models. Well log measurements included density, porosity, electrical resistivity, natural gamma radiation, and acoustic wave velocity. Combinations of well logs used in the ML models provide good overall balanced accuracy (0.79 to 0.86) for the prediction of the gas hydrate occurrence and good accuracy (0.68 to 0.92) for methane hydrate saturation prediction in the marine accumulations against reference data. The accuracy scores indicate that the ML models can successfully predict reservoir characteristics for marine methane hydrate deposits. In conclusion, the results indicate that the ML models can either augment physics-driven methods for assessing the occurrence and saturation of methane hydrate deposits or serve as an independent predictive tool for those characteristics.

58 GEOSCIENCES↗

Quantifying the Impact of Feedstock Quality on the Design of Bioenergy Supply Chain Networks

Logging residues, which refer to the unused portions of trees cut during logging, are important sources of biomass for the emerging biofuel industry and are critical feedstocks for the first-type biofuel facilities (e.g., corn-ethanol facilities). Logging residues are under-utilized sources of biomass for energetic purposes. To support the scaling-up of the bioenergy industry, it is essential to design cost-effective biofuel supply chains that not only minimize costs, but also consider the biomass quality characteristics. The biomass quality is heavily dependent upon the moisture and the ash contents. Ignoring the biomass quality characteristics and its intrinsic costs may yield substantial economic losses that will only be discovered after operations at a biorefinery have begun. Here this paper proposes a novel bioenergy supply chain network design model that minimizes operational costs and includes the biomass quality-related costs. The proposed model is unique in the sense that it supports decisions where quality is not unrealistically assumed to be perfect. The effectiveness of the proposed methodology is proven by assessing a case study in the state of Tennessee, USA. The results demonstrate that the ash and moisture contents of logging residues affect the performance of the supply chain (in monetary terms). Higher-than-target moisture and ash contents incur in additional quality-related costs. The quality-related costs in the optimal solution (with final ash content of 1% and final moisture of 50%) account for 27% of overall supply chain cost. In conclusion, based on the numeral experimentation, the total supply chain cost increased 7%, on average, for each additional percent in the final ash content.

09 BIOMASS FUELS↗

Subsea ice-bearing permafrost on the U.S. Beaufort Margin: 2. Borehole constraints: SUBSEA PERMAFROST IN U.S. BEAUFORT II

Borehole logging data from legacy wells directly constrain the contemporary distribution of subsea permafrost in the sedimentary section at discrete locations on the U.S. Beaufort Margin and complement recent regional analyses of exploration seismic data to delineate the permafrost's offshore extent. Most usable borehole data were acquired on a ~500 km stretch of the margin and within 30 km of the contemporary coastline from north of Lake Teshekpuk to nearly the U.S.-Canada border. Relying primarily on deep resistivity logs that should be largely unaffected by drilling fluids and hole conditions, the analysis reveals the persistence of several hundred vertical meters of ice-bonded permafrost in nearshore wells near Prudhoe Bay and Foggy Island Bay, with less permafrost detected to the east and west. Permafrost is inferred beneath many barrier islands and in some nearshore and lagoonal (back-barrier) wells. The analysis of borehole logs confirms the offshore pattern of ice-bearing subsea permafrost distribution determined based on regional seismic analyses and reveals that ice content generally diminishes with distance from the coastline. Lacking better well distribution, it is not possible to determine the absolute seaward extent of ice-bearing permafrost, nor the distribution of permafrost beneath the present-day continental shelf at the end of the Pleistocene. However, the recovery of gas hydrate from an outer shelf well (Belcher) and previous delineation of a log signature possibly indicating gas hydrate in an inner shelf well (Hammerhead 2) imply that permafrost may once have extended across much of the shelf offshore Camden Bay.

54 ENVIRONMENTAL SCIENCES↗

Semi-inclusive wino and higgsino annihilation to LL'

Here, we systematically compute the annihilation rate for winos and higgsinos into the final state relevant for indirect detection experiments, γ + X. The radiative corrections to this process receive enhancement from the large Bloch-Nordsieck-Violating Sudakov logarithm, log(2M${\chi }$/M W ). We resum the double logs and include single logs to fixed order using a formalism that combines nonrelativistic and soft-collinear effective field theories. For the wino case, we update an earlier exclusion adapting results of the HESS experiment. At the thermal relic mass of 3 TeV, LL' corrections result in a ~30% reduction in rate relative to LL. But, single logs do not save the wino, and it is still excluded by an order of magnitude. Finally, experimental cuts produce an endpoint region which, our results show, significantly effects the higgsino rate at its thermal-relic mass near 1 TeV and is deserving of further study.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Double brane holographic model dual to 2d ICFTs

A minimal single brane holographic model can be used as a dual to 2d conformal interfaces (ICFTs) to calculate the transmission coefficient T of energy transported across the defect as well as boundary entropy log g, the additional entanglement entropy for some sub-region that encloses the defect. Both T and log g are uniquely determined by the tension characterizing the brane. In contrast, in field theory defects typically the transmission coefficient can be dialed from 0 to 1 independently for each allowed value of log g. To address this discrepancy, we look at a double brane (3-region bulk) holographic model. Merger of two single brane interfaces creates genuinely new interfaces which indeed allow a range of accessible transmission coefficients for a fixed value of log g. In particular, the T = 0 limit of two completely decoupled BCFTs can be achieved.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Monitoring CO 2 Storage at Cranfield, Mississippi with Time-Lapse Offset VSP – Using Integration and Modeling to Reduce Uncertainty

A time-lapse Offset Vertical Seismic Profile (OVSP) data set was acquired as part of a subsurface monitoring program for geologic sequestration of CO 2 . The storage site at Cranfield, near Natchez, Mississippi, is part of a detailed area study (DAS) site for geologic carbon sequestration operated by the U.S. Dept. of Energy’s Southeast Regional Carbon Sequestration Partnership (SECARB). The DAS site includes three boreholes, an injection well and two monitoring wells. The project team selected the DAS site to examine CO 2 sequestration multiphase fluid flow and pressure at the interwell scale in a brine reservoir. The time-lapse (TL) OVSP was part of an integrated monitoring program that included well logs, crosswell seismic, electrical resistance tomography and 4D surface seismic. The goals of the OVSP were to detect the CO 2 induced change in seismic response, give information about the spatial distribution of CO 2 near the injection well and to help tie the high-resolution borehole monitoring to the 4D surface data. The VSP data were acquired in well CFU 31-F1, which is the ~3200 m deep CO 2 injection well at the DAS site. A preinjection survey was recorded in late 2009 with injection beginning in December 2009, and a post injection survey was conducted in Nov 2010 following injection of about 250 kT of CO 2 . The sensor array for both surveys was a 50-level, 3-component, Sercel MaxiWave system with 15 m (49 ft) spacing between levels. The source for both surveys was an accelerated weight drop, with different source trucks used for the two surveys. Consistent time-lapse processing was applied to both data sets. Time-lapse processing generated difference corridor stacks to investigate CO 2 induced reflection amplitude changes from each source point. Corridor stacks were used for amplitude analysis to maximize the signal-to-noise ratio (S/N) for each shot point. Spatial variation in reflectivity (used to ‘map’ the plume) was similar in magnitude to the corridor stacks but, due to relatively lower S/N, the results were less consistent and more sensitive to processing and therefore are not presented. We examined the overall time-lapse repeatability of the OVSP data using three methods, the NRMS and Predictability (Pred) measures of Kragh and Christie (2002) and the signal-to-distortion ratio (SDR) method of Cantillo (2011). Because time-lapse noise was comparable to the observed change, multiple methods were used to analyze data reliability. The reflections from the top and base reservoir were identified on the corridor stacks by correlation with a synthetic response generated from the well logs. A consistent change in the corridor stack amplitudes from pre- to post-CO 2 injection was found for both the top and base reservoir reflections on all ten shot locations analyzed. In addition to the well-log synthetic response, a finite-difference elastic wave propagation model was built based on rock/fluid properties obtained from well logs, with CO 2 induced changes guided by time-lapse crosswell seismic tomography (Ajo-Franklin, et al., 2013) acquired at the DAS site. Time-lapse seismic tomography indicated that two reservoir zones were affected by the flood. The modeling established that interpretation of the VSP trough and peak event amplitudes as reflectivity from the top and bottom of reservoir is appropriate even with possible tuning effects. Importantly, this top/base change gives confidence in an interpretation that these changes arise from within the reservoir, not from bounding lithology. The modeled time-lapse change and the observed field data change from 10 shotpoints are in agreement for both magnitude and polarity of amplitude change for top and base of reservoir. Therefore, we conclude the stored CO 2 has been successfully detected and, furthermore, the observed seismic reflection change can be applied to Cranfield’s 4D surface seismic for spatially delineating the CO 2 /brine interface.

54 ENVIRONMENTAL SCIENCES↗

Clustered BSRs: Evidence for gas hydrate-bearing turbidite complexes in folded regions, example from the Perdido Fold Belt, northern Gulf of Mexico

We detail previously undocumented but extensive gas hydrate accumulations in the mouth of Perdido Canyon in the northern Gulf of Mexico. The accumulations are located within central parts of structural domes (four-way closures) and are characterized by stacked, high-amplitude bottom simulating reflections (BSRs) that we call clustered BSRs. Seismic data from Perdido Canyon show two clustered BSRs associated with turbidite sequences within two dome folds formed from tectonic folding and salt diapir rise. The northwestern (NW) and southeastern (SE) clustered BSRs have aerial extents of ~25 km2 and 50 km2, respectively. Well log data confirm gas hydrate occurs above the NW clustered BSR, within a 225 m-thick consistently high-resistivity interval that we interpret as gas hydrate in near-vertical fractures and turbidite sands. The SE dome is only drilled at the edge of the BSR; nevertheless, the well log data indicate that a 30 m-thick gas hydrate accumulation is present. Gas chromatographic logs in both domes suggest a gradual transition from predominantly microbial gas below the BSR (500–1000 m below seafloor (mbsf)) to thermogenic gas at 1000–2000 mbsf. Based on the well log data and seismic stratigraphic analysis, we find gas hydrate is concentrated in fractures in marine mud, as well as in the pores of submarine fan turbidities, where saturations reach as high as 75%. An estimate of the total gas hydrate-bound gas volume at standard temperature and pressure is between 0.04 and 0.17 trillion cubic meters (TCM) assuming average hydrate saturation of 5-20% in a ~45 m thick turbidite sand unit above the Perdido Canyon BSR area. Measured BSR extent and gas volume estimates indicate that the NW and SE reservoirs are among the largest gas hydrate occurrences known in the Gulf of Mexico.

58 GEOSCIENCES↗

Constructing compact and effective graphs for recommender systems via node and edge aggregations

Exploiting graphs for recommender systems has great potential to flexibly incorporate heterogeneous information for producing better recommendation results. As our baseline approach, we first introduce a naive graph-based recommendation method, which operates with a heterogeneous log-metadata graph constructed from user log and content metadata databases. Although the na ve graph-based recommendation method is simple, it allows us to take advantages of heterogeneous information and shows promising flexibility and recommendation accuracy. However, it often leads to extensive processing time due to the sheer size of the graphs constructed from entire user log and content metadata databases. In this paper, we propose node and edge aggregation approaches to constructing compact and e ective graphs called Factor-Item bipartite graphs by aggregating nodes and edges of a log-metadata graph. Furthermore, experimental results using real world datasets indicate that our approach can significantly reduce the size of graphs exploited for recommender systems without sacrificing the recommendation quality.

97 MATHEMATICS AND COMPUTING↗

Pressure transient analysis during CO 2 push-pull tests into faults for EGS characterization

Here, with the goal of detecting and characterizing faults and fractures in enhanced geothermal systems (EGS), a new technology involving CO 2 push-pull testing, active-source geophysical imaging, and well logging has recently been proposed. This technique takes advantage of (1) the contrasting properties of supercritical CO 2 and water which cause CO 2 to appear distinct from surrounding brine in seismic and other geophysical logging approaches, (2) the non-wetting nature of CO 2 which keeps it localized to the faults and fractures to create contrast potentially sufficient for active seismic and well-logging approaches to image faults and fracture zones at EGS sites. In this study, we evaluate the feasibility of using pressure transient monitoring during CO 2 push-pull tests to complement active seismic and wireline well logging for EGS characterization. For this purpose, we developed a 2D model of a prototypical geothermal site (Desert Peak, NV) that includes a single fault. The fault zone consists of a slip plane, fault gouge, and damage zone, and is bounded by the surrounding matrix of the country rock. Through numerical simulation using iTOUGH2, we found that the pressure transient at the monitoring wells in the fault gouge shows unique traits due to the multiphase flow conditions developed by CO 2 injection, and varies sensitively on the arrival of the CO 2 plume and the degree of CO 2 saturation. A sensitivity analysis shows the pressure transient is most sensitive to the fault gouge permeability, but also depends on multiphase flow parameters and the boundary conditions of the fault. Lastly, an inversion study reveals that the fault gouge permeability can be best estimated with the pressure transient data, whereas additional CO 2 saturation data do not improve the accuracy of the inversion significantly.

58 GEOSCIENCES↗