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DOE OSTI2021

RivGraph: Automatic extraction and analysis of river and delta channel network topology

River networks sustain life and landscapes by carrying and distributing water, sediment, and nutrients throughout ecosystems and communities. At the largest scale, river networks drain continents through tree-like tributary networks. At typically smaller scales, river deltas and braided rivers form loopy, complex distributary river networks via avulsions and bifurcations.In order to model flows through these networks or analyze network structure, the topology, or connectivity, of the network must be resolved. Additionally, morphologic properties of each river channel as well as the direction of flow through the channel inform how fluxes travel through the network’s channels. Riv Graphis a Python package that automates the extraction and characterization of river channel networks from a user-provided binary image, or mask, of a channel network (Fig. 1). Masks may be derived from (typically remotely-sensed) imagery, simulations, or even hand-drawn. RivGraph will create explicit representations of the channel network by resolving river centerlines as links, and junctions as nodes. Flow directions are solved for each link of the network without using auxiliary data, e.g., a digital elevation model (DEM). Morphologic properties are computed as well, including link lengths, widths, sinuosities, branching angles,and braiding indices. If provided,RivGraph will preserve georeferencing information of the mask and will export results as ESRI shapefiles, GeoJSONs, and GeoTIFFs for easy import into GIS software.RivGraph can also return extracted networks as networkx objects for convenient interfacing with the full-featured networkx package (Hagberg et al., 2008). Finally, RivGraph offers a suite of topologic metrics that were specifically designed for river channel network analysis (Tejedor et al., 2015b).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

LINAC Electrical Cabinets - Structural Analysis

Along LINAC s downstream path is a floor containing various cabinets above the LINAC. Of the dozens of cabinets are 4 specific cabinet types: PFN (pulse-forming network) Module, PFN Power Supply, Water Skid, and Marx. Each of these cabinets may contain some of the various contents that include electronics, wiring, pipe lines, circuits, conduits. In addition, high voltage and flowing fluids are also present within the cabinets. Occasionally, Lab Technicians perform maintenance and inspections of the cabinets and need to access every part, including the top section that is subject to the weight of the technician standing on top. To ensure the cabinet is structurally safe, a CAD model will be developed for each cabinet and a Finite Element Analysis (FEA) will be performed on each cabinet to confirm it is safe to stand on.

Blas, Efren↗

DOE OSTI2015

Security-Constrained Unit Commitment with Linearized AC Optimal Power Flow.

We propose a mathematical programming-based approach to optimize the security-constrained unit commitment problem with a full AC transmission network representation. Our approach is based on our previously introduced successive linear programming (SLP) approach to solving the non-linear, nonconvex AC optimal power flow (ACOPF) problem. By linearizing the ACOPF, we are able to leverage powerful commercial mixed-integer solvers to iteratively optimize the combined unit commitment plus ACOPF model. We demonstrate our approach on six-bus, IEEE RTS-96, and IEEE 118-bus test systems. We perform a comparative analysis of the relative impacts of singlebus, DC, and AC transmission network models on the unit commitment and dispatch solutions and their associated costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Numerical simulations of depressurization-induced gas production from gas hydrates using 3-D heterogeneous models of L-Pad, Prudhoe Bay Unit, North Slope Alaska

Gas production potential is estimated using a three-dimensional reservoir model based on gas hydrate deposits located in the Prudhoe Bay region of the Alaska's North Slope. The model incorporates two hydrate-bearing sand units using detailed reservoir geological and structural information obtained from past and recent drilling programs. Geostatistical porosity models, conditioned to log data from 78 wells drilled in the vicinity of the Prudhoe Bay “L-Pad,” were developed, providing 3D heterogeneity in porosity, porosity-dependent hydrate saturation, and intrinsic permeability. The simulations utilize both vertical and inclined wellbores to induce depressurization of the reservoir at a constant bottom-hole pressure. The results show the superior performance of the inclined well design. Average gas production rates during the first five years were ~6.0 × 10 4 ST m 3 /day (~2.1 MMSCF/day) and ~2.7 × 10 4 ST m 3 /day (~1.0 MMSCF/day) for incline and vertical wells, respectively. After 30 years 5.3 × 10 8 - 5.7 × 10 8 ST m 3 (18.6–20.2 BSCF) and 6.2 × 10 8 - 6.4 × 10 8 ST m 3 (22.0–22.7 BSCF) gas were produced using the vertical and inclined well configurations, respectively. The analysis reveals that 2D reservoir models with homogeneous representations for porosity and hydrate saturation significantly underestimate production potential. The heterogeneity implemented in this work provides complex porous network and preferential pathways for mobile phase flow to a producing well. Consequently, no secondary hydrate formation around a wellbore is predicted in contrast to models that utilize uniform porosity and hydrate saturation distributions.

03 NATURAL GAS↗

DOE OSTI2024

A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions

Here, we present a pseudoreversible normalizing flow method for efficiently generating samples of the state of a stochastic differential equation (SDE) with various initial distributions. The primary objective is to construct an accurate and efficient sampler that can be used as a surrogate model for computationally expensive numerical integration of SDEs, such as those employed in particle simulation. After training, the normalizing flow model can directly generate samples of the SDE’s final state without simulating trajectories. The existing normalizing flow model for SDEs depends on the initial distribution, meaning the model needs to be retrained when the initial distribution changes. The main novelty of our normalizing flow model is that it can learn the conditional distribution of the state, i.e., the distribution of the final state conditional on any initial state, such that the model only needs to be trained once and the trained model can be used to handle various initial distributions. This feature can provide a significant computational saving in studies of how the final state varies with the initial distribution. Additionally, we propose to use a pseudoreversible network architecture to define the normalizing flow model, which has sufficient expressive power and training efficiency for a variety of SDEs in science and engineering, e.g., in particle physics. We provide a rigorous convergence analysis of the pseudoreversible normalizing flow model to the target probability density function in the Kullback–Leibler divergence metric. Numerical experiments are provided to demonstrate the effectiveness of the proposed normalizing flow model.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1977

Computational models for the analysis of three-dimensional internal and exhaust plume flowfields

This paper describes computational procedures developed for the analysis of three-dimensional supersonic ducted flows and multinozzle exhaust plume flowfields. The models/codes embodying these procedures cater to a broad spectrum of geometric situations via the use of multiple reference plane grid networks in several coordinate systems. Shock capturing techniques are employed to trace the propagation and interaction of multiple shock surfaces while the plume interface, separating the exhaust and external flows, and the plume external shock are discretely analyzed. The computational grid within the reference planes follows the trace of streamlines to facilitate the incorporation of finite-rate chemistry and viscous computational capabilities. Exhaust gas properties consist of combustion products in chemical equilibrium. The computational accuracy of the models/codes is assessed via comparisons with exact solutions, results of other codes and experimental data. Results are presented for the flows in two-dimensional convergent and divergent ducts, expansive and compressive corner flows, flow in a rectangular nozzle and the plume flowfields for exhausts issuing out of single and multiple rectangular nozzles.

Dash, S. M.↗

DOE OSTI2023

Decision-Making Framework to Evaluate Opportunities for Recovery of Rare Earth Elements and Critical Minerals in Produced Water Networks

Oil and gas development activities require a significant amount of water. Given the environmental impacts associated with high consumption and subsequent disposal of this water, there is a need for strategies to support effective reuse of, treatment of, and/or resource recovery from this produced water. These streams can contain appreciable concentrations of rare earth elements (REE) and critical minerals (CM) (e.g., Lithium), which are critical for many important applications in electronics, technology, manufacturing, energy, and medicine [1]. Along with REE/CM present in produced water, other waste streams such as fly ash from coal-fired power plants and acid mine discharge present other potential sources for recovery of REE/CM [2-4]. And with increases in demand for REE/CM, the need for recovery from wastewater streams is becoming even more important. There is a need to develop effective decision-making tools to evaluate the economic and environmental potential for REE/CM recovery from produced water networks while supporting the needs of drilling and hydraulic fracturing activities. In this work, we present our progress in developing a decision-making framework to efficiently design and operate produced water networks for REE/CM recovery. Our approach considers REE/CM recovery from produced water streams alongside other potential wastewater sources. The models consider the location and capacity of storage and decentralized treatment processes as well as the design and operation of pipeline and transportation networks to connect different sources and effectively schedule inventories, reuse, and recovery opportunities. We focus on the evaluation of opportunities for REE/CM recovery with treatment constraints on composition and flow. We demonstrate this framework with an illustrative case study that features diverse production sites, storage facilities, transportation, and treatment sites. This proposed framework will be deployed in an open-source software package that is compatible with the PARETO framework to deliver analysis and decision-making tools that allow stakeholders to quantitatively evaluate potential opportunities for REE/CM recovery in produced water networks.

Pulsipher, Joshua↗

DOE OSTI2016

Towards smart corrective switching: analysis and advancement of PJM's switching solutions

Transmission switching, as a power flow control mechanism that can reduce costs and improve reliability, has gained a lot of attention during the last decade. Despite its benefits, industry adoption has been very limited due to its computational complexity, stability and AC performance concerns. Pennsylvania New Jersey Maryland (PJM) has published a list of corrective switching solutions to relieve actual and post‐contingency network violations. The list is developed based on operators ’ prior knowledge and offline studies. This study employs a fast AC‐based real‐time contingency analysis (RTCA) tool with corrective transmission switching (CTS) functionality to analyse PJM's switching solutions with actual PJM data. The results show that the RTCA CTS tool is almost always able to find solutions that perform better than, or equally as well as, PJM's solutions. The results also show that PJM's list identifies solutions for only 3% of the problematic contingencies with post‐contingency violations over the course of one week. The RTCA CTS tool, however, is able to find corrective TS solutions for almost all the cases. The results suggest that CTS is ripe for industry adoption. The tool provides significant savings and would pave the road towards a smarter transmission network as an essential ingredient of the future smart grid.

Balasubramanian, Pranavamoorthy↗

DOE OSTI2015

Model-Based Integrated High Penetration Renewables Planning and Control Analysis

Increasing adoption of Solar Photovoltaic (PV) generation at the distribution level poses several changes for the reliable operation of electrical power distribution systems. The addition of a significant amount of PV to a distribution network can introduce a variety of operational problems, including steady-state overvoltages, reverse flows, voltage flicker and excessive controller movement among others. These adverse impacts can be mitigated through a variety of equipment upgrades which represent a cost to either the electric utility or the owner of the PV site. The study performed here aims to quantify the levels of PV generation which present operational problems on a distribution circuit and how those problems might be alleviated. The study performed here included 20 distribution feeders selected from Pepco Holdings, Inc. (PHI) service territory. These feeders are located in the states of Delaware, Maryland and New Jersey. A hosting capacity study was performed on each feeder to determine how much additional PV it could support in its current configuration. Several improvements were then performed on these circuits including phase balancing, capacitor redesign, reducing the voltage regulator set points, fixed power factor operation on the PV inverters and the installation of battery storage. After each of these improvements the hosting capacity of the circuit was reevaluated in order to determine how that particular improvement impacted the amount of PV that could be hosted by the circuit. Each of these improvements represents a real cost in terms of labor and equipment in order to be implemented. They are expected to provide a benefit in terms of the amount of additional PV generation which can be safely interconnected to the distribution feeder. A cost benefit analysis was performed in order to evaluate the expected costs of each feeder improvement and how each one was able to increase the PV hosting capacity of each feeder. It is hoped that these results can be utilized by other distribution utilities in order to understand how they can improve the hosting capacity of their feeders and facilitate the deployment of more PV generation at the distribution level. Admittedly other utility companies will most likely have different feeder architectures and differing labor and equipment costs so the realized cost benefit numbers may be significantly different.

14 SOLAR ENERGY↗

DOE OSTI2025

Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics

This dataset supports hydrologic modeling and stream network expansion–contraction analysis for the East Fork Poplar Creek (EFPC) Watershed in Tennessee. It includes a Jupyter notebook for model setup, model configuration files, simulation outputs, and derived products used to evaluate model performance and investigate stream dynamics under varying hydrologic conditions. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations using a stream-aligned mesh. Outputs include high-resolution time series of streamflow, active network length, water table depth, and related hydrologic variables. Also included are spatially explicit stream persistency indices and classifications of reaches as perennial or non-perennial. These data facilitate reproducibility and support further research on stream intermittency and variability in network extent.The model data archive is organized in following directories:1) model_setup_inputsContains the Watershed Workflow Jupyter notebooks (accessed through any open source code editor), selected input datasets, and resulting ATS input files, including XML files (access through any open source code editor), computational mesh (.exo files can be viewed using Paraview), and meteorological forcing files (.h5 files can be accessed through h5py python package and HDFView open source software). 2) model_outputsIncludes ATS simulation outputs relevant to this study. Time series of spatially integrated or averaged variables (e.g., streamflow, water table depth) are provided as CSV files. Select spatial fields (e.g., ponded depth and water table depth) are saved as pickled Python objects to reduce file size, and can be accessed through pickle package in Python. Key geometry objects from Watershed Workflow—such as the surface mesh and river tree—are also included to support analysis of streamflow persistency and expansion–contraction dynamics. These files can also be accessed through Watershed Workflow Python package.3) model_evaluationProvides observed streamflow time series and field survey-based flow regime classifications used to evaluate model performance. Jupyter notebooks for processing ATS outputs and comparing model predictions with observations to build confidence in the model prior to scientific analysis are also included.4) Q_L_relationshipsContains workflows for generating time series of discharge, active network length, and related hydrologic variables used in the stream network expansion–contraction analysis. Includes routines for delineating baseflow-dominated periods. For each catchment, notebooks and processed data (as pickled DataFrames accessed through Pandas Python package) are provided. 5) figure_scriptsProvides the Jupyter notebooks used to generate the figures presented in the paper.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

My vehicle is a data mine

In this talk we explore how analysis of vehicle data provides information of individual vehicle behaviors, information of other vehicles in the flow of traffic, and insights into the behavior of drivers. Over the last two decades traditional passenger vehicles have been transformed from integrated two-port electrical nodes to cyber-physical systems of communicating computational nodes whose individual state and control variables are shared on a standard controller area network (CAN) bus. As driver assistance systems have crept into vehicles as safety features, driver behaviors can be observed through analysis of the data streams on the CAN bus as these new nodes communicate with one another. The properties of these data streams, as well as architectures and approaches to gather the data, are important to consider when drawing conclusions on the relevance of the data in making decisions at varying levels of the information hierarchy. We will demonstrate several technical challenges associated with these data collection processes, as well as preliminary results that demonstrate application relevance of the data to behavior, traffic, and systems domains.

42 ENGINEERING↗

DOE OSTI2024

Methods for Quantitative Thermal Analysis of Lithium Solid-State and Beyond Battery Safety

The use of differential scanning calorimetry (DSC) to measure the thermal behavior of individual components and electrolyte/electrode combinations is common. However, here we focus on DSC tests on an anode, cathode, and electrolyte (ACE) component combination over a temperature range that includes many of the phase transitions and key reactions (i.e., to 500 °C) that contribute to thermal runaway. This method can help quantify the complex reaction network in a full cell, thereby informing potential safety issues. Here, we used DSC heat flow data from a solid-state Li 0.43 CoO 2 +C+PVDF | LLZO | Li metal ACE sample and its components to quantify key factors affecting results. We focused on three areas: (1) ACE sample preparation and assembly in DSC pans, (2) DSC measurement parameters, and (3) heat flow analysis. Key points include the choice of component ratios (e.g., commercially relevant N:P capacity ratio), the importance of conductive carbon and binder, type of pan used, DSC ramp rate, and integration method used when dealing with broad and overlapping exothermic peaks. This work deepens the scientific basis and best practices for obtaining heat flow data from ACE samples for early-stage evaluation of solid-state and beyond battery safety.

25 ENERGY STORAGE↗

DOE OSTI2016

Comparative Kinetic Analysis of Closed-Ended and Open-Ended Porous Sensors

Efficient mass transport through porous networks is essential for achieving rapid response times in sensing applications utilizing porous materials. In this work, we show that open-ended porous membranes can overcome diffusion challenges experienced by closed-ended porous materials in a microfluidic environment. A theoretical model including both transport and reaction kinetics is employed to study the influence of flow velocity, bulk analyte concentration, analyte diffusivity, and adsorption rate on the performance of open-ended and closed-ended porous sensors integrated with flow cells. The analysis shows that open-ended pores enable analyte flow through the pores and greatly reduce the response time and analyte consumption for detecting large molecules with slow diffusivities compared with closed-ended pores for which analytes largely flow over the pores. Experimental confirmation of the results was carried out with open- and closed-ended porous silicon (PSi) microcavities fabricated in flow-through and flow-over sensor configurations, respectively. The adsorption behavior of small analytes onto the inner surfaces of closed-ended and open-ended PSi membrane microcavities was similar. However, for large analytes, PSi membranes in a flow-through scheme showed significant improvement in response times due to more efficient convective transport of analytes. The experimental results and theoretical analysis provide quantitative estimates of the benefits offered by open-ended porous membranes for different analyte systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

NASA NTRSDate not supplied

Run Time Improvement Efforts for the Roman Space Telescope Thermal Analysis

Observatory thermal models for large, complex missions, such as the Wide Field InfraRed Survey Telescope (WFIRST) mission, produce an immense amount of data to be processed. Configuration management of the model throughout the project life cycle has mainly focused on which versions of the subsystem models form the current observatory level configuration. However, the results produced by the model are not nearly as well The Roman Space Telescope (RST), formerly known as the Wide Field InfraRed Survey Telescope, is the next great astrophysics observatory mission to follow the James Webb Space Telescope with a planned launch in 2026. As a large scale, flagship mission for NASA with challenging wave front error stability requirements, a single model approach for both thermal discipline analysis and thermo-optical distortion analysis has been used since the early days of the project. In alleviating the need to maintain two separate models for different analysis types, it imposes run time penalties on the thermal analysis with a large model with significant radiation heat exchange. Throughout the lifecycle of the project, the component models have steadily grown in size, resulting in a continuous growth of the overall observatory model with each update and consequently a considerable increase in the model run time. While ongoing efforts to reduce run time are continuously investigated, previous efforts had primarily focused on timestep size and total simulation time to reach quasi-equilibrium. More recently, studies were performed on the total number of radiation couplings (radks) included in the model, which has a nearly linear impact on run time, but increases exponentially with node count. As standard practice for spacecraft analysis, small radks were excluded from the temperature solution based on the assumption that their interchange/view factors have a negligible impact on heat flow. Four approaches were investigated to reduce the model run time while minimizing the impact on accuracy: (1) the Equivalent Radiation Network node, (2) Progressive Radk Inclusion as solution proceeds, (3) Targeted Radk Filtering for critical/non critical areas, and lastly (4) Representation of culled radks with Backloads. Furthermore, the investigation of model run time also revealed that cold cases took noticeably longer to run than hot cases; the root computational inefficiencies were explored along with the computation penalty of linearization of the external radks and recalculation of temperature dependent linear couplings at each timestep. This paper outlines the details of each of the above approaches and their impact on run time and model accuracy.

Thermal Analysis↗

NASA NTRSDate not supplied

Run Time Improvement Efforts for the Roman Space Telescope Thermal Analysis

"Observatory thermal models for large, complex missions, such as the Wide Field InfraRed Survey Telescope (WFIRST) mission, produce an immense amount of data to be processed. Configuration management of the model throughout the project life cycle has mainly focused on which versions of the subsystem models form the current observatory level configuration. However, the results produced by the model are not nearly as well The Roman Space Telescope (RST), formerly known as the Wide Field InfraRed Survey Telescope, is the next great astrophysics observatory mission to follow the James Webb Space Telescope with a planned launch in 2026. As a large scale, flagship mission for NASA with challenging wave front error stability requirements, a single model approach for both thermal discipline analysis and thermo-optical distortion analysis has been used since the early days of the project. In alleviating the need to maintain two separate models for different analysis types, it imposes run time penalties on the thermal analysis with a large model with significant radiation heat exchange. Throughout the lifecycle of the project, the component models have steadily grown in size, resulting in a continuous growth of the overall observatory model with each update and consequently a considerable increase in the model run time. While ongoing efforts to reduce run time are continuously investigated, previous efforts had primarily focused on timestep size and total simulation time to reach quasi-equilibrium. More recently, studies were performed on the total number of radiation couplings (radks) included in the model, which has a nearly linear impact on run time, but increases exponentially with node count. As standard practice for spacecraft analysis, small radks were excluded from the temperature solution based on the assumption that their interchange/view factors have a negligible impact on heat flow. Four approaches were investigated to reduce the model run time while minimizing the impact on accuracy: (1) the Equivalent Radiation Network node, (2) Progressive Radk Inclusion as solution proceeds, (3) Targeted Radk Filtering for critical/non critical areas, and lastly (4) Representation of culled radks with Backloads. Furthermore, the investigation of model run time also revealed that cold cases took noticeably longer to run than hot cases; the root computational inefficiencies were explored along with the computation penalty of linearization of the external radks and recalculation of temperature dependent linear couplings at each timestep. This paper outlines the details of each of the above approaches and their impact on run time and model accuracy.

Thermal Analysis↗

NASA NTRS2004

National Airspace System Delay Estimation Using Weather Weighted Traffic Counts

Assessment of National Airspace System performance, which is usually measured in terms of delays resulting from the application of traffic flow management initiatives in response to weather conditions, volume, equipment outages and runway conditions, is needed both for guiding flow control decisions during the day of operations and for post operations analysis. Comparison of the actual delay, resulting from the traffic flow management initiatives, with the expected delay, based on traffic demand and other conditions, provides the assessment of the National Airspace System performance. This paper provides a method for estimating delay using the expected traffic demand and weather. In order to identify the cause of delays, 517 days of National Airspace System delay data reported by the Federal Aviation Administration s Operations Network were analyzed. This analysis shows that weather is the most important causal factor for delays followed by equipment and runway delays. Guided by these results, the concept of weather weighted traffic counts as a measure of system delay is described. Examples are given to show the variation of these counts as a function of time of the day. The various datasets, consisting of aircraft position data, enroute severe weather data, surface wind speed and visibility data, reported delay data and number of aircraft handled by the Centers data, and their sources are described. The procedure for selecting reference days on which traffic was minimally impacted by weather is described. Different traffic demand on each reference day of the week, determined by analysis of 42 days of traffic and delay data, was used as the expected traffic demand for each day of the week. Next, the method for computing the weather weighted traffic counts using the expected traffic demand, derived from reference days, and the expanded regions around severe weather cells is discussed. It is shown via a numerical example that this approach improves the dynamic range of the weather weighted traffic counts considerably. Time histories of these new weather weighted traffic counts are used for synthesizing two statistical features, six histogram features and six time domain features. In addition to these enroute weather features, two surface weather features of number of major airports in the United States with high mean winds and low mean visibility are also described. A least squares procedure for establishing a functional relation between the features, using combinations of these features, and system delays is explored using 36 days of data. Best correlations between the estimated delays using the functional relation and the actual delays provided by the Operations Network are obtained with two different combinations of features: 1) six time domain features of weather weighted traffic counts plus two surface weather features, and 2) six histogram features and mean of weather weighted traffic counts along with the two surface weather features. Correlation coefficient values of 0.73 and 0.83 were found in these two instances.

Chatterji, Gano B.↗

DOE OSTI2017

Imaging Fracture Networks Using Joint Seismic and Electrical Change Detection Techniques (Final Report)

During the initial phase of this SubTER project, we conducted a series of high resolution seismic imaging campaigns designed to characterize induced fractures. Fractures were emplaced using a novel explosive source, designed at Sandia National Laboratories, that limits damage to the borehole. This work provided evidence that fracture locations could be imaged at inch scales using high-frequency seismic tomography but left many fracture properties (i.e. permeability) unresolved. We present here the results of the second phase of the project, where we developed and demonstrated emerging seismic and electrical geophysical imaging technologies that characterize 1) the 3D extent and distribution of fractures stimulated from the explosive source, 2) 3D fluid transport within the stimulated fracture network through use of a contrasting tracer, and 3) fracture attributes through advanced data analysis. Focus was placed upon advancing these technologies toward near real-time acquisition and processing in order to help provide the feedback mechanism necessary to understand and control fracture stimulation and fluid flow. Results from this study include a comprehensive set of 4D cross-hole seismic and electrical data that take advantage of change detection methodologies allowing for perturbations associated with the fracture emplacement and particulate tracer to be isolated. During the testing the team also demonstrated near real-time 4D electrical resistivity tomography imaging and 4D seismic tomography using the CASSM approach with a temporal resolution approaching 1 minute. All of the data collected were used to develop methods of estimating fracture attributes from seismic data, develop methods of assimilating disparate and transient data sets to improve fracture network imaging resolution, and advance capabilities for near real-time inversion of cross-hole tomographic data. These results are illustrated here. Advancements in these areas are relevant to all situations where fracture emplacement is used for reservoir stimulation (e.g. Enhanced Geothermal Systems (EGS) and tight shale gases).

42 ENGINEERING↗

NASA NTRS1984

Measurements of mantle wave velocities and inversion for lateral heterogeneity and anisotropy. II - Analysis by the single-station method

In the present investigation, the single-station method reported by Brune et al. (1960) is utilized for an analysis of long-period Love(G) and Rayleigh(R) waves recorded on digital seismic networks. The analysis was conducted to study the lateral heterogeneity of surface wave velocities. The data set is examined, and a description is presented of the single-station method. Attention is given to an error analysis for velocity measurements, the estimation of geographical distribution of surface wave velocities, the global distribution of surface wave velocities, and the correlation between the surface wave velocities and the heat flow on the geoid. The conducted measurements and inversions of surface wave velocities are used as a basis to derive certain conclusions. It is found that the application of the single-station method to long-period surface waves recorded on digital networks makes it possible to reach an accuracy level comparable to great circle velocity measurements.

Nakanishi, I.↗