Search NASA⌕ Search

SEARCH · Search NASA

Results for “inversion and monitoring”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Analysis of the inversion monitoring capabilities of a monostatic acoustic radar in complex terrain

A qualitative interpretation of the records from a monostatic acoustic radar is presented. This is achieved with the aid of airplane, helicopter, and rawinsonde temperature soundings. The diurnal structure of a mountain valley circulation pattern is studied with the use of two acoustic radars, one located in the valley and one on the downwind ridge. The monostatic acoustic radar was found to be sufficiently accurate in locating the heights of the inversions and the mixed layer depth to warrant use by industry even in complex terrain.

Koepf, D.↗
DOE OSTI2022

Enhanced Multi-Dimensional Inversion Through Target-Specific Inversion Parameter Bounds With an Application to Crosswell Electromagnetic for Sequestration Monitoring

In geophysical inversions, lower and upper model parameter bounds are a means of solution stabilization. Further, constraints that intend to let only geologically plausible inverse solutions pass are amenable to lower and upper bounds. Reliable prior information is paramount to construct such bound constraints. It is common practice to narrow and widen bound intervals for regions of, respectively, more and less certain prior information. Contrary to this practice, we experiment with widened bound intervals in zones that are poorly resolved by a given survey configuration but where prior information would suggest structural anomalies of interest. The purpose of enlarged parameter bounds that correlate spatially with predefined targets is to let the inversion explore a larger solution space, thus increasing the potential to resolve otherwise hidden anomalies. Application of the method is based on a carbon-sequestration baseline (pre-injection) crosswell electromagnetic (EM) field survey at the Containment and Monitoring Institute Field Research Station (Alberta, Canada), where impeded measurements led to generally reduced sensitivities for the interwell region. Synthetic-data proofs of concept use augmented bounds designed to boost the resolution of artificial plume targets, indicating an enhanced illumination compared to constant bounds. Comparative field data inversions with spatially variable bounds constructed from prior resistivity and velocity information highlight non-horizontal baseline structures.

3-D electrical resistivity imaging↗
NASA NTRS1993

Inverse sequential procedures for the monitoring of time series

Climate changes traditionally have been detected from long series of observations and long after they happened. The 'inverse sequential' monitoring procedure is designed to detect changes as soon as they occur. Frequency distribution parameters are estimated both from the most recent existing set of observations and from the same set augmented by 1,2,...j new observations. Individual-value probability products ('likelihoods') are then calculated which yield probabilities for erroneously accepting the existing parameter(s) as valid for the augmented data set and vice versa. A parameter change is signaled when these probabilities (or a more convenient and robust compound 'no change' probability) show a progressive decrease. New parameters are then estimated from the new observations alone to restart the procedure. The detailed algebra is developed and tested for Gaussian means and variances, Poisson and chi-square means, and linear or exponential trends; a comprehensive and interactive Fortran program is provided in the appendix.

Radok, Uwe↗
DOE OSTI2022

Real-time deep-learning inversion of seismic full waveform data for CO 2 saturation and uncertainty in geological carbon storage monitoring

Deep-learning inversion has recently drawn attention in geological carbon storage research due to its potential of imaging and monitoring carbon storage in real time, significantly improving efficiency and safety of carbon storage operations. We present a deep-learning full waveform inversion method that after the neural network has been trained can image CO 2 saturation and its uncertainty in real time. Our deep-learning inversion method is based on the U-Net architecture with the neural network trained on pairs of synthetic seismic data and CO 2 saturation models. Accordingly, our training establishes a mapping relationship between seismic data and CO 2 saturation models and once fully trained directly estimates CO 2 saturation as a function of subsurface location. We further quantify uncertainties of CO 2 saturation estimates using the Monte Carlo dropout method and a bootstrap aggregating method. For this proof-of-concept study, the CO 2 training models and data are derived from the Kimberlina 1.2 model, a hypothetical 3D geological carbon storage model that is constructed based on various geological and hydrological data from the Southern San Joaquin Basin, California. We perform deep-learning inversion experiments using noise-free and noisy training and test data sets and compare the results. Our modelling experiments show that (1) the deep-learning inversion can estimate 2D distributions of CO 2 fairly well even in the presence of Gaussian random noise and (2) both CO 2 saturation imaging and uncertainty quantification can be done in real time. Our results suggest that the deep-learning inversion method can serve as a robust real-time monitoring tool for geological carbon storage and/or other time-varying reservoir/aquifer properties that result from injection, extraction, and/or other subsurface transport phenomena.

58 GEOSCIENCES↗
DOE OSTI2023

Integration of seismic-pressure-petrophysics inversion of continuous active-seismic monitoring data for monitoring and quantifying CO 2 plume (Final Report)

The overall objective of this project is to develop and validate an integrated package of joint seismic-pressure-petrophysics inversion (jSPPI) of continuous active-source seismic monitoring dataset capable of providing real-time monitoring of CO 2 plume during geologic carbon sequestration (GCS). The three specific developments include: (a) the methodologies for fast seismic full waveform inversion of continuous active source seismic monitoring, (CASSM) datasets for simultaneously estimating velocity and attenuation, and with data assimilation; (b) joint Bayesian petrophysical inversion of seismic models and pressure data for providing and updating CO 2 saturation models; (c) the methods using multiple datasets including (Crainfield and Frio-II borehole) synthetic, laboratory, and field CASSM datasets. The outcomes of jSPPI include (a) a workflow for processing CASSM data, (b) Bayesian inversion algorithms using CASSM data and pressure response data, and (c) integration with data assimilation algorithms for continuously updating site-specific models used for prediction and reservoir management. The validation of joint FWI will be conducted using synthetic models based on the Cranfield and Frio experiments as well as field CASSM datasets collected as part of the Frio-II pilot injection. To quantify and map the mass and distribution of CO 2 (saturation), we will jointly invert velocity and attenuation measurements from the FWI with a Bayesian approach using a rock physics model for attenuation (e.g., White’s attenuation model with two selected patch sizes (White, 1976; Dutta and Seriff, 1979)). The Bayesian inversion will be applied to each time step in the CASSM survey in an updating scheme, which integrates with an ensemble of reservoir simulations at each step. A more complete experimental validation dataset will be collected as part of a mesoscale (2-3 m) gas-CO 2 injection experiment utilizing a higher frequency version of the CASSM system developed for laboratory studies; the integrated inversion will be demonstrated using this dataset which will provide both a dense geometry as well as more precise secondary confirmation measurements (e.g. saturation) typically not available in the field. The resulting real-time map of CO 2 saturation is able to provide a deeper scientific understanding of the complex, time-varying dynamics of subsurface fluid flow migration path as well as the rapid detection of CO 2 leakage hazards.

25 ENERGY STORAGE↗
DOE OSTI2023

EGS Collab Experiment 2: Shear Stimulation ERT Monitoring Data

This repository contains the electrical resistivity tomography (ERT) monitoring data that was collected before, during, and after shear stimulation attempts were conducted at EGS Collab. These tests were carried out on the SURF 4100 level during Experiment 2 in March, 2022. Flow and stimulation data corresponding to this dataset are available in a different GDR dataset, which is linked below. Also included here are the E4D input files that were used to process the ERT data. E4D is an open source ERT monitoring and inversion code which is linked for use below.

15 GEOTHERMAL ENERGY↗
NASA NTRS1995

(abstract) Using an Inversion Algorithm to Retrieve Parameters and Monitor Changes over Forested Areas from SAR Data

In this work, the application of an inversion algorithm based on a nonlinear opimization technique to retrieve forest parameters from multifrequency polarimetric SAR data is discussed. The approach discussed here allows for retrieving and monitoring changes in forest parameters in a quantative and systematic fashion using SAR data. The parameters to be inverted directly from the data are the electromagnetic scattering properties of the forest components such as their dielectric constants and size characteristics. Once these are known, attributes such as canopy moisture content can be obtained, which are useful in the ecosystem models.

forest canopy SAR data algorithm radar scattering ↗
DOE OSTI2020

Joint Focal Mechanism Inversion Using Downhole and Surface Monitoring at the Decatur, Illinois, CO2 Injection Site

ABSTRACT The three-year CO2 injection period at the Illinois Basin - Decatur Project site (Decatur, Illinois, United States) produced a number of microseismic events distributed in very distinct spatiotemporal clusters with different orientations. Further characterization of the microseismicity encompasses the determination of the event source mechanisms. Initially, the microseismic monitoring network consisted solely of borehole sensors, but has been extended with surface sensors, thereby significantly improving the data coverage over the focal sphere. This article focuses on 23 events from the northernmost microseismic cluster (about 2 km from the injection point) and takes advantage of both, surface and downhole, recordings. The resulting strike-slip east–west-oriented focal planes are all consistent with the east–west orientation of the cluster in map view. The injection-related increase of pore pressure is far below the formation fracture pressure; however, small stress-field changes associated with the pore-pressure increase may reach as far as to the investigated cluster location. Monte Carlo modeling of the slip reactivation potential within this cluster showed that the observed maximum stress-field orientation of N068° is the optimum orientation for fault reactivation of the east–west-oriented cluster. Our results suggest that the east–west orientation of the investigated cluster is the main reason for its activation, even though the cluster is about 2 km away from the low-pressure injection point.

Geochemistry & Geophysics↗
NASA NTRS1975

Studies of discharge mechanisms in high pressure gases-applications to high efficiency high power lasers

By measuring the absorption and emission cantinua of various states in the cesium/xenon molecule, the collisional rates critical in populating the alkali/rare gas excimer levels have been estimated. Cs atomic states that are weakly optically connected to ground have been shown to form excimer levels that are attractive as potential dissociation lasers. In particular, the (Cs/7 2S/Xe) excited molecule appears promising as a source of high energy laser radiation due to its large dissociation energy, stimulated emission cross section, and small population inversion densities. Monitoring of the optically pumped Cs2 molecular absorption profile in the presence of xenon shows a drastic change with increasing xenon pressure for the Cs2C band. Dominant absorption at large xenon densities is centered around approximately 6380 A as opposed to 6300 A for lower perturber pressure.

Cherrington, B. E.↗
NASA NTRS1995

Inverse sequential procedures for the monitoring of time series

When one or more new values are added to a developing time series, they change its descriptive parameters (mean, variance, trend, coherence). A 'change index (CI)' is developed as a quantitative indicator that the changed parameters remain compatible with the existing 'base' data. CI formulate are derived, in terms of normalized likelihood ratios, for small samples from Poisson, Gaussian, and Chi-Square distributions, and for regression coefficients measuring linear or exponential trends. A substantial parameter change creates a rapid or abrupt CI decrease which persists when the length of the bases is changed. Except for a special Gaussian case, the CI has no simple explicit regions for tests of hypotheses. However, its design ensures that the series sampled need not conform strictly to the distribution form assumed for the parameter estimates. The use of the CI is illustrated with both constructed and observed data samples, processed with a Fortran code 'Sequitor'.

Radok, Uwe↗
NASA NTRS1995

Monitoring Canopy Moisture Using an Inversion Algorithm Applied to SAR Data from Boreas

During several intensive field campaigns in 1993 & 1994, the JPL airborne synthetic aperture radar obtained multifrequency polarimetric radar data over various areas in the Canadian boreal forest designated as primary BOREAS study sites. These were part of a major remote sensing effort geared toward studying the interaction of the forest biome and the atmosphere to identify their role in global change.

Forest Canopy moisture content BOREAS synthetic ap↗
NASA NTRS1996

Monitoring Tree Moisture Using an Inversion Algorithm Applied to SAR Data from BOREAS

During several field campaigns in spring and summer of '94, the NASA/JPL air-borne sythetic aperature radar (AIRSAR) collected data over the southern and northern study sites of BOREAS. Among the areas over which radar data were collected was the young jack pine tower site, which is generally characterized as have shot but closely space trees with a dense crown layer.

forest canopy moisture↗
NASA NTRS2010

Comparison of Summer and Winter California Central Valley Aerosol Distributions from Lidar and MODIS Measurements

Aerosol distributions from two aircraft lidar campaigns conducted in the California Central Valley are compared in order to identify seasonal variations. Aircraft lidar flights were conducted in June 2003 and February 2007. While the ground PM(sub 2.5) concentration is highest in the winter, the aerosol optical depth measured from MODIS is highest in the summer. A seasonal comparison shows that PM(sub 2.5) in the winter can exceed summer PM(sub 2.5) by 55%, while summer AOD exceeds winter AOD by 43%. Higher temperatures and wildfires in the summer produce elevated aerosol layers that are detected by satellite measurements, but not surface particulate matter monitors. Temperature inversions, especially during the winter, contribute to higher PM(sub 2.5) measurements at the surface. Measurements of the boundary layer height from lidar instruments provide valuable information need to understand the relationship between satellite measurements of optical depth and in-situ measurements of PM(sub 2.5).

Lewis, Jasper↗
DOE OSTI2023

Understanding Subsurface Fracture Evolution Dynamics Using Time‐Lapse Full Waveform Inversion of Continuous Active‐Source Seismic Monitoring Data

Abstract Predicting the behavior, geometry, and flow properties of subsurface fractures remains a challenging problem. Seismic models that can characterize fractures usually suffer from low spatiotemporal resolution. Here, we develop a correlative double‐difference time‐lapse full waveform inversion of continuous active source seismic monitoring data for determining high‐spatiotemporal‐resolution time‐lapse V p models of in‐situ fracture evolution at a shallow contamination site in Wyoming, USA. Assisted by rock physics modeling, we find that (a) rapidly increasing pore pressure initializes and grows the fracture, increasing the porosity slightly (from ∼13.7% to ∼14.6%) in the tight clay formation, thus decreasing V p (∼50 m/s); (b) the fluid injection continues decreasing V p , likely through the introduction of gas bubbles in the injectate; and (c) final V p reductions reach over ∼150 m/s due to a posited ∼4.5% gas saturation. Our results demonstrate that high‐resolution V p changes are indicative of mechanical and fluid changes within the fracture zone during hydrofracturing.

58 GEOSCIENCES↗
NASA NTRS2019

Developing a soil inversion model framework for regional permafrost monitoring

Currently, the community lacks capabilities to assess and monitor landscape scale permafrost active layer dynamics over large extents. To address this need, we developed a concept of a remote sensing based Soil Inversion Model for regional Permafrost (SIM-P) monitoring. The current SIM-P framework includes a satellite-based soil process model and a soil dielectric model. We are also working on incorporating a radar scattering model for Arctic tundra into the SIM-P framework. A unified soil parameterization scheme was developed to harmonize key soil thermal, hydraulic and dielectric parameters in the soil process and radar models that can be used in the joint soil-radar inversion framework. The soil parameter retrievals of the SIM-P framework include soil organic content (SOC) and active layer thickness (ALT). Initial tests of SIM-P using in-situ soil permittivity observations showed reasonable accuracy in predicting site-level SOC and soil temperature profiles at an Alaska tundra site and ALT in Arctic Alaska. SIM-P will be further tested using airborne P- and L-band radar data collected during NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) to evaluate the sensitivity of longwave radar to active layer properties.

Miller, Charles E.↗
NASA NTRS1986

Variation of the urban NO2 concentration during a ground inversion situation

In February 1985 the NO2 concentration over Goeteborg, a major Swedish city, was monitored during two inversion situations. The differential absorption technique was employed and the results show the build-up of the concentration. In this experiment the laser beam was scanned horizontally over Goeteborg. The results were presented as maps over the NO2 concentration distribution. For security reasons the beam was not parallel to the ground, which gives a height gradient in some measurements. During the measurement period the NO2 concentration variation build-up from the morning to the afternoon was monitored. Great concentration variations were seen. Later the mixing below the inversion layer, resulting in a more uniform, high concentration was seen. The breakdown of the inversion when stronger winds start was also seen. Comparisons with a traditional point-measuring chemiluminiscence instrument and an optical method DOAS (Differential Optical Absorption Spectroscopy), were made. The results are discussed. Strong spatial concentration variations are shown by the lidar measurements. For a point-measuring system, the instrument must be very carefully placed since its location will strongly influence the values it gives.

Sunesson, A.↗