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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

CHIPFoam Modification to Allow for Modelling SWIFT Foams

SWIFT (Silicon-water in Familiar Template) foams are silicone foams that have a continuous porosity without having any obvious spherical or ellipsoidal pore shapes. Like other foamed rubber, SWIFT foams can experience large reversible deformations. Because of their microstructure, SWIFT foams have a stiffering behavior in compression that is very abrupt compared to most other foamed rubbers. Work by Benedikt reported by Miller showed that fitting compressive test data with the CHIPFoam model in its current form is impractical and inaccurate. This report describes an extension made to CHIPFoam to allow the modeling of SWIFT foams. While the extension allows the modeling of SWIFT foams, it also extends the range of porosity of foams that can be modelled with CHIPFoam to include very high porosity (>99%) foamed rubber. The previous model was unstable for porosities greater than 70%. The changes made to CHIPFoam include the introduction of a critical porosity at which the compressible Danielsson strain energy function that couples volumetric and deviatoric mechanical behavior begins to increase with compression. This new feature also required the introduction of a third term in the multiplicative decomposition of the relative volume, J . The organization of this report is described here. The first section, SWIFT Foam Structure and Mechanical Behavior, describes the structure of SWIFT foams as contrasted to other foamed rubbers. It also contrasts the mechanical behavior of SWIFT foams to other more traditional foamed rubbers. The second section, CHIPFoam Modifications, describes the specific modifications done to be able to modify the delayed rapid compressive stiffening seen in SWIFT foams. The third section, Results, demonstrates the use of the modified model to fit compressive loading response data from a SWIFT foam sample. The fourth section, Conclusions and Further Work, puts the work in perspective and presents likely further work.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Toward a Machine Learning Approach to Interpreting X-ray Spectra of Trace Impurities by Converting XANES to EXAFS

The fact that the photoabsorption spectrum of a material contains information about the atomic structure, commonly understood in terms of multiple scattering theory, is the basis of the popular extended X-ray absorption spectroscopy (EXAFS) technique. How much of the same structural information is present in other complementary spectroscopic signals is not obvious. Here we use a machine learning approach to demonstrate that within theoretical models that accurately predict the EXAFS signal, the extended near-edge region does indeed contain the EXAFS-accessible structural information. We do this by exhibiting deep operator neural networks (DeepONets) that have learned the relationship between the extended and near edge portions of the X-ray absorption spectrum to predict the former from the latter. We find that we can accurately predict the EXAFS spectrum between 6 and 14 Å –1 from the first 6 Å –1 (≈100 eV) of the absorption spectrum of Cu 2 + substitutional defects in the Fe 3+ mineral hematite (α-Fe 2 O 3 ). This surprising finding implies that theoretical analyses of X-ray absorption spectra could be implemented that extract the same conclusions as high-quality EXAFS studies from spectra collected over a much smaller range of photon energies. This relaxes a host of experimental limitations related to the X-ray source and measurement sample, including collection time, minimum dopant concentration, source brilliance, and energy range. We describe the theoretical data sets and DeepONet construction and show that the resulting DeepONets produce EXAFS that recovers linear combination fits to experimental data with accuracy approaching the original ab initio calculations. We discuss the implications of our findings for minor constituent characterization and for understanding the information content of spectroscopic data more broadly, including how this approach might be applied to measured experimental spectra. In conclusion, to encourage similar efforts, the simulated X-ray spectra, machine learning, and fitting code are publicly available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Identification of crystal plasticity model parameters by multi-objective optimization integrating microstructural evolution and mechanical data

Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.

42 ENGINEERING↗
DOE OSTI2023

Energy transport analysis of NSTX plasmas with the TGLF turbulent and NEO neoclassical transport models

This work presents a study of plasma transport at low aspect ratio on the National Spherical Torus Experiment tokamak, where the turbulent and neoclassical energy fluxes calculated by the quasilinear Trapped Gyro Landau Fluid (TGLF) model and the multi species drift-kinetic Neoclassical solver (NEO) are validated against experimental data. The turbulent energy transport of two plasma discharges, one in the L-mode confinement regime and another in the H-mode regime, is dominated by electrostatic drift-wave instabilities, while the ion heat transport has a significant neoclassical contribution. The data analysis workflow is described in detail to understand how the variations of mapping and fitting of experimental data affect the power balance solution and subsequent flux-matching plasma profile predictions with the TGYRO solver. On average, the predicted plasma profiles are consistent with experimental data. However, the solutions are sensitive to various input parameters, including boundary conditions, and the electron-ion coupling. Linear gyrokinetic stability analysis demonstrates close agreement of the real frequencies of unstable modes between TGLF and CGYRO gyrokinetic simulations, but higher growth rates are predicted by TGLF, especially for the H-mode case. Estimates of the low-k modes' contributions to the total flux are consistent with linear stability analysis and the E × B suppression of turbulence in TGLF simulations with the SAT1 saturation model, while the SAT2 saturation model over-predicts the low-k modes' contribution in the H-mode case. Moreover, the results with SAT1 model are consistent with power balance analysis, which indicates only neoclassical ion energy fluxes inside ρ < 0.4 in the L-mode case and $\rho \unicode{x2A7D} 0.7$ in the H-mode case. The presence of multi-scale turbulence and ion-scale driven zonal flow mixing effects are also observed in TGLF scans of the electron turbulent heat flux over a range of temperature gradients and the electron-ion temperature ratio, which could explain the strong model sensitivity to variations of input parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1972

The thermodynamic properties of oxygen and nitrogen. Part 1: Thermodynamic properties of nitrogen from 115 R to 3500 R with pressures to 150000 psia

An equation of state is presented for liquid and gaseous nitrogen for temperatures from 115 R to 3500 R and pressures to 150,000 psia. All of the pressure-density-temperature data available from the published literature have been reviewed, and appropriate corrections have been identified and applied to bring experimental temperatures into accord with the International Practical Temperature Scale of 1968. Comparisons of property values calculated from the equation of state to measured values are included to illustrate the accuracy of the equation in representing the data. The coefficients of the equation of state were determined by a weighted least squares fit to selected published data and, simultaneously, to constant volume data determined by corresponding states analysis from oxygen data, and to data which define the phase equilibrium criteria for the saturated liquid and saturated vapor. The methods of weighting the various data for simultaneous fitting are presented and discussed. The equation of state is estimated to be accurate to within 0.5 percent in the liquid region, to within 0.1 percent for supercritical isotherms up to 15,000 psia, and to within 0.3 percent from 15,000 to 150,000 psia.

Stewart, R. B.↗
NASA NTRS1989

A reduced version of the NMC DERF 2 data set

The National Meterological Center (NMC) Dynamical Extended Range Forecast (DERF 2) data represents a major computational effort to better ascertain the potential for extended range forecasts and to develop a strategy for performing operational extended range forecasts using dynamical models. A major stumbling block for using this data has been the sheer volume of data that must be processed to perform even simple calculations. The product of the data reduction described is a manageable data set that fits comfortably on five magnetic tapes or on one compact disc. The document outlines the data reduction process of the second phase of DERF data. It contains the description of the fields and the resolution of both the original and final fields. In order to assist the users of this data set, maps of selected fields, using both the original truncation at rhomboidal 30 and the truncation of the final data at triangular 20, are displayed.

Schubert, Siegfried↗
NASA NTRS1999

Work on Planetary Atmospheres and Planetary Atmosphere Probes

A major objective of the grant was to complete the fabrication, test, and evaluation of the atmosphere structure experiment on the Galileo Probe, and to receive, analyze, and interpret data received from the spacecraft. The grantee was competitively selected to be Principal Investigator of Jupiter's atmosphere structure on the Galileo Probe. His primary motivation was to learn as much as possible about Jupiter's atmosphere by means of a successful atmosphere structure experiment, and to support the needs and schedule of the Galileo Project. After a number of launch delays, the Flight instrument was shipped to Kennedy Space Center 2 years after the start of this collaboration, on April 14, 1989, at which time it was determined from System level tests of the ASI on the Probe that the instrument was in good working order and ready for flight. The spacecraft was launched on October 18, 1989. Data analysis of test and calibration data taken over a period of years of instrument testing was continued in preparation for the encounter. The initial instrument checkout in space was performed on October 26, 1989. The data set received by telemetry was thoroughly analyzed, and a report of the findings was transmitted to the Probe Operations Office on Feb. 28, 1990. Key findings reported were that the accelerometer biases had shifted by less than 1 mg through launch and since calibration at Bell Aerospace in 1983; accelerometer scale factors, evaluated by means of calibration currents, fell on lines of variation with temperature established in laboratory calibrations; pressure sensor offsets, correlated as a function of temperature, fell generally within the limits of several years of ground test data; atmospheric and engineering temperature sensor data were internally consistent within a few tenths of a degree; and the instrument electronics performed all expected functions without any observable fault. Altogether, this checkout was highly encouraging of the prospects of instrument performance, although performed greater than 5 years prior to Jupiter encounter. Capability of decoding the science data from the Experiment Data Record to be provided at encounter was developed and exercised using the tape recording of the first Cruise Checkout data. A team effort was organized to program the selection and combination of data words defining pressure, temperature, acceleration, turbulence, and engineering quantities; to apply decalibration algorithms to convert readings from digital numbers to physical quantities; and to organize the data into a suitable printout. A paper on the Galileo Atmosphere Structure Instrument was written and submitted for publication in a special issue of Space Science Reviews. At the Journal editor's request, the grantee reviewed other Probe instrument papers submitted for this special issue. Calibration data were carefully taken for all experiment sensors and accumulated over a period of 10 years. The data were analyzed, fitted with algorithms, and summarized in a calibration report for use in analyzing and interpreting data returned from Jupiter's atmosphere. The sensors included were the primary science pressure, temperature, and acceleration sensors, and the supporting engineering temperature sensors. This report was distributed to experiment coinvestigators and the Probe Project Office.

Seiff, Alvin↗
NASA NTRS1999

Work on Planetary Atmospheres and Planetary Atmosphere Probes

A summary final report of work accomplished is presented. Work was performed in the following areas: (1) Galileo Probe science analysis, (2) Galileo probe Atmosphere Structure Instrument, (3) Mars Pathfinder Atmosphere Structure/Meteorology instrument, (4) Mars Pathfinder data analysis, (5) Science Definition for future Mars missions, (6) Viking Lander data analysis, (7) winds in Mars atmosphere Venus atmospheric dynamics, (8) Pioneer Venus Probe data analysis, (9) Pioneer Venus anomaly analysis, (10) Discovery Venus Probe Titan probe instrument design, and (11) laboratory studies of Titan probe impact phenomena. The work has resulted in more than 10 articles published in archive journals, 2 encyclopedia articles, and many working papers. This final report is organized around the four planets on which there was activity, Jupiter, Mars, Venus, and Titan, with a closing section on Miscellaneous Activities. A major objective was to complete the fabrication, test, and evaluation of the atmosphere structure experiment on the Galileo probe, and to receive, analyze and interpret data received from the spacecraft. The instrument was launched on April 14, 1989. Calibration data were taken for all experiment sensors. The data were analyzed, fitted with algorithms, and summarized in a calibration report for use in analyzing and interpreting data returned from Jupiter's atmosphere. The sensors included were the primary science pressure, temperature and acceleration sensors, and the supporting engineering temperature sensors. Computer programs were written to decode the Experiment Data Record and convert the digital numbers to physical quantities, i.e., temperatures, pressures, and accelerations. The project office agreed to obtain telemetry of checkout data from the probe. Work to extend programs written for use on the Pioneer Venus project included: (1) massive heat shield ablation leading to important mass loss during entry; and (2) rapid planet rotation, which introduced terms of motion not needed on Venus. When the Galileo Probe encountered Jupiter, analysis and interpretation of data commenced. The early contributions of the experiment were to define (1) the basic structure of the deep atmosphere, (2) the stability of the atmosphere, (3) the upper atmospheric profiles of density, pressure, and temperature. The next major task in the Galileo Probe project was to refine, verify and extend the analysis of the data. It was the verified, and corrected data, which indicated a dry abiabatic atmosphere within measurement accuracy. Temperature in the thermosphere was measured at 900 K. Participation in the Mars atmospheric research included: (1) work as a team member of the Mars Atmosphere Working Group, (2) contribution to the Mars Exobiology Instrument workshop, (3) asssistance in planning the Mars global network and (4) assitance in planning the Soviet-French Mars mission in 1994. This included a return to the Viking Lander parachute data to refine and improve the definition of winds between 1.5 and 4 kilometer altitude at the two entry sites. The variability of the structure of Mars atmosphere was addressed, which is known to vary with season, latitude, hemisphere and dust loading of the atmosphere. This led to work on the Pathfinder project. The probe had a deployable meteorology mast that had three temperature sensors, and a wind sensor at the tip of the mast. Work on the Titan atmospheric probe was also accomplished. This included developing an experiment proposal to the European Space Agency (ESA), which was not selected. However, as an advisor in the design and preparation of the selected experiment the researcher interacted with scientist on the Huygens Probe Atmosphere Structure Experiment. The researcher also participated in the planning for the Venus Chemical Probe. The science objectives of the probe were to resolve unanswered questions concerning the minor species chemistry of Venus' atmosphere that control cloud formation, greenhouse effectiveness, and the thermal structure. The researcher also reviewed problems with the Pioneer Venus Probe, that caused anomalies which occurred on the Probes at and below 12.5 km level of the Venus' atmosphere. He convened and participated in a workshop that concluded the most likely hardware cause was insulation failure in the electrical harness outside the Probes' pressure vessels. It was discovered that the shrink tubing material failed at 600K. This failure could explain the anomalies experienced by the probes. The descent data of the Pioneer probes, and the Soviet Vega Lander was analyzed to evaluate the presence of small scale gravity waves in and below the Venus cloud layer.

Lester, Peter↗
NASA NTRS2008

Non-Linear System Identification for Aeroelastic Systems with Application to Experimental Data

Representation and identification of a non-linear aeroelastic pitch-plunge system as a model of the NARMAX class is considered. A non-linear difference equation describing this aircraft model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to aeroelastic dynamics and its properties demonstrated via continuous-time simulations of experimental conditions. Simulation results show that (i) the outputs of the NARMAX model match closely those generated using continuous-time methods and (ii) NARMAX identification methods applied to aeroelastic dynamics provide accurate discrete-time parameter estimates. Application of NARMAX identification to experimental pitch-plunge dynamics data gives a high percent fit for cross-validated data.

Kukreja, Sunil L.↗
NASA NTRS2008

Nonlinear System Identification for Aeroelastic Systems with Application to Experimental Data

Representation and identification of a nonlinear aeroelastic pitch-plunge system as a model of the Nonlinear AutoRegressive, Moving Average eXogenous (NARMAX) class is considered. A nonlinear difference equation describing this aircraft model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to aeroelastic dynamics and its properties demonstrated via continuous-time simulations of experimental conditions. Simulation results show that (1) the outputs of the NARMAX model closely match those generated using continuous-time methods, and (2) NARMAX identification methods applied to aeroelastic dynamics provide accurate discrete-time parameter estimates. Application of NARMAX identification to experimental pitch-plunge dynamics data gives a high percent fit for cross-validated data.

Kukreja, Sunil L.↗
DOE OSTI2022

Robust estimation of charge carrier diffusivity using transient photoluminescence microscopy

Transient microscopy has emerged as a powerful tool for imaging the diffusion of excitons and free charge carriers in optoelectronic materials. In many excitonic materials, extraction of diffusion coefficients can be simplified because of the linear relationship between signal intensity and local excited state population. However, in materials where transport is dominated by free charge carriers, extracting diffusivities accurately from multidimensional data is complicated by the nonlinear dependence of the measured signal on the local charge carrier density. To obtain accurate estimates of charge carrier diffusivity from transient microscopy data, statistically robust fitting algorithms coupled to efficient 3D numerical solvers that faithfully relate local carrier dynamics to raw experimental measurables are sometimes needed. Here, we provide a detailed numerical framework for modeling the spatiotemporal dynamics of free charge carriers in bulk semiconductors with significant solving speed reduction and for simulating the corresponding transient photoluminescence microscopy data. To demonstrate the utility of this approach, we apply a fitting algorithm using a Markov chain Monte Carlo sampler to experimental data on bulk CdS and methylammonium lead bromide (MAPbBr 3 ) crystals. Parameter analyses reveal that transient photoluminescence microscopy can be used to obtain robust estimates of charge carrier diffusivities in optoelectronic materials of interest, but that other experimental approaches should be used for obtaining carrier recombination constants. Additionally, simplifications can be made to the fitting model depending on the experimental conditions and material systems studied. Our open-source simulation code and fitting algorithm are made freely available to the scientific community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Selection of Training Sets for 235U Source Detection Classifiers Using Gamma Signatures

The machine learning methods for classifiers to detect low level radiation sources are of interest when suitable training data sets are available. Their application and performance assessment, however, involves the aspects of over-fitting and training data selection that are somewhat uncommon in other existing methods for this task.We study U-235 gamma signatures using data sets collected by 21 NaI detectors under controlled conditions. The gamma spectra are collected by the detectors located at different distances from the source, and we study their choice as training sets for classifiers to detect a source. The detectors form the near, middle and outer groups based on the distance to source. The classifiers based on the outer group are susceptible to over-fitting, that is, they achieve low training error but incur much higher testing error in independent tests. The other two groups achieve lower training error and comparable testing error, and the near group achieves the overall lowest error. In detecting a source at an unknown distance, the farther detectors in the middle group achieve the overall lowest testing error with limited over-fitting, thereby indicating the complex dependencies between the training and classifier performance.

Rao, Nageswara↗
NASA NTRS1998

The Problem of Hipparcos Distances to Open Clusters: Constraints from Multicolor a Main-Sequence Fitting - Report 1

Parallax data from the Hipparcos mission allow the direct distance to open clusters to be compared with the distance inferred from main-sequence (MS) fitting. There are surprising differences between the two distance measurements. indicating either the need for changes in the cluster compositions or reddening, underlying problems with the technique of MS fitting, or systematic errors in the Hipparcos parallaxes at the 1 mas level. We examine the different possibilities, focusing on MS fitting in both metallicity-sensitive B-V and metallicity-insensitive V-I for five well-studied systems (the Hyades, Pleiades, alpha Per, Praesepe, and Coma Ber). The Hipparcos distances to the Hyades and alpha Per are within 1 sigma of the MS-fitting distance in B-V and V-I, while the Hipparcos distances to Coma Ber and the Pleiades are in disagreement with the MS-fitting distance at more than the 3 sigma level. There are two Hipparcos measurements of the distance to Praesepe; one is in good agreement with the MS-fitting distance and the other disagrees at the 2 sigma level. The distance estimates from the different colors are in conflict with one another for Coma but in agreement for the Pleiades. Changes in the relative cluster metal abundances, age related effects, helium, and reddening are shown to be unlikely to explain the puzzling behavior of the Pleiades. We present evidence for spatially dependent systematic errors at the 1 mas level in the parallaxes of Pleiades stars. The implications of this result are discussed.

Pinsonneault, Marc H.↗
NASA NTRS1977

The galactic halo question: New size constraints from galactic gamma-ray data

The SAS-2 gamma-ray data is analyzed making use of recent CO line emission and other data for determining the large-scale distribution of galactic gas. A nonuniform distribution of cosmic rays in the galaxy is implied. This fact rules out large trapping halo models and extragalactic origin models. Detailed models of diffusion halos of various sizes perpendicular to the galactic plane are considered. In such models, the scale perpendicular to the plane has a strong effect in determining the radial distribution of cosmic rays. Such radial distributions are calculated for cylindrical coordinate models. The implied gamma-ray longitude distributions are then calculated and compared with the SAS-2 data for goodness-of-fit. Assuming the sources to be supernova remnants or pulsars, cosmic ray nucleon halo models with scale heights greater than 3 kpc are found to provide a poor fit to the gamma-ray longitude data (probability of 6% or less). Thin halo, or source dominated diffusion models are found to provide a good fit to the gamma-ray data, with an upper limit scale height of approximately 3 kpc.

Stecker, F. W.↗
NASA NTRS1998

New Approach to Diagnosing Properties of Protoplanetary Disks

In this paper we suggest that subjecting the observationally derived properties of protoplanetary disks to the evolutionary interpretation yields new insights into the working of those disks, and offers valuable constraints on their models. We propose that the global properties of individual disks, such as their accretion rates and disk masses, sorted by the mass of the central star, can be indexed by the age of the star to simulate the evolution of a single disk. Using data from published surveys of T Tauri stars, we show that accretion rate data, and disk mass data for the lowest mass stars, form well-defined evolutionary tracks. The higher mass stars show a definitive negative correlation between accretion rates and star ages. We use the time-dependent alpha-disk model of the viscous protoplanetary disk to link the theory to observations. The data are consistent with the standard theoretical paradigm, but not with the layered accretion model. The best fits to the data are obtained for the standard models that start with disks that are about one-third of the mass of the central star and have their angular momenta, j, and alpha-coefficients linked by the relationship j varies as Solar mass(exp 3/2)alpha(exp 1/3). The proportionality constant in this relationship, when derived from the accretion rate data, differs from the constant derived from the disk mass data. We argue that the accretion rate data are more reliable. Taking into account typical values of the specific angular momentum of disk-forming matter, we obtain alpha is greater than or equal to 10(exp -2). A complete time-dependent standard disk model, built on the parameters determined from the best-fit procedure, is presented. Such a model constitutes a good point of departure for various theoretical studies aimed at the issue of formation of planetary systems and the character of protoplanetary disks.

Stepinski, Tomasz F.↗
NASA NTRS2014

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

strain-gage balance↗
DOE OSTI2021

Relocating microseismicity from downhole monitoring of the Decatur CCS site using a modified double-difference algorithm

SUMMARY The injection of CO2 at the Decatur carbon capture and storage site has generated significant microseismic activity, which occurs in distinct spatial clusters up to approximately 2.2 km from the primary injection well. Accurate and precise event locations are vital for the characterization of the microseismicity to help understand the reservoir response to the CO2 injection, whilst enabling the identification of minor faults and fractures below the resolution of conventional active seismic imaging. However, microseismic monitoring of fluid injection sites, such as Decatur, is often performed using a network of borehole sensors often from a single well. While these downhole sensors have excellent detection capabilities, their poor azimuthal coverage limits the ability to precisely determine event locations. We have developed a modified double-difference relocation algorithm suitable for both 1-D and 3-D velocity models, and which incorporates differential back azimuth observations to allow the benefits of the original double-difference algorithm to be applicable to a downhole microseismic monitoring setting. Applying the modified double-difference algorithm to the microseismicity at Decatur, we have successfully relocated 4293 events. The relocation included over 59 million observations for 757 285 event pairs, split across seven geographic regions. Despite the majority of observations being recorded in only two boreholes, with an almost identical azimuthal coverage, the results have shown to be reliable with significantly reduced residuals and low uncertainties associated with the final locations. We have analysed the residuals in terms of their association with each geographic region, data type, station and individual events, to fully appreciate their influence in the inversion and the fit of the data to the final set of event locations. For each region, the relocated seismicity has become less diffuse with improved clustering, and with newly visible linear features often orientated in a NE–SW direction. These results show the potential improvements that can be made to microseismic event locations recorded by a borehole network with a limited and variable azimuthal distribution.

58 GEOSCIENCES↗