Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Well Data”

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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Interplanetary medium data book, supplement, 1975 - 1978

Since the issurance of the Interplanetary Medium Data Book (NSSDC/WDC-A-R&S 77-04, 1977) which contains plots and listings of hourly average interplanetary field and plasma parameters covering the period November 27, 1963 through December 30, 1975, additional data are available which fill some 1975 data gaps and which extend the data coverage well into 1978. This supplement contains all the presently available data for the years 1975-1978, Interplanetary magnetic field (IMF) data are from the IMP 8 triaxial fluxgate magnetometer experiment. Derived plasma parameters are form the IMP 7 and IMP 8 instruments. Some of the early 1975 IMF data are from a HEOS 1 experiment.

King, J. H.↗
NASA NTRS1984

The effect of spatial, spectral and radiometric factors on classification accuracy using thematic mapper data

An experiment of a factorial design was conducted to test the effects on classification accuracy of land cover types due to the improved spatial, spectral and radiometric characteristics of the Thematic Mapper (TM) in comparison to the Multispectral Scanner (MSS). High altitude aircraft scanner data from the Airborne Thematic Mapper instrument was acquired over central California in August, 1983 and used to simulate Thematic Mapper data as well as all combinations of the three characteristics for eight data sets in all. Results for the training sites (field center pixels) showed better classification accuracies for MSS spatial resolution, TM spectral bands and TM radiometry in order of importance.

Wrigley, R. C.↗
NASA NTRS1984

The effect of spatial, spectral and radiometric factors on classification accuracy using Thematic Mapper data

An experiment of a factorial design was conducted to test the effects on classification accuracy of land cover types due to the improved spatial, spectral and radiometric characteristics of the LANDSAT Thematic Mapper (TM) in comparison to the Multispectral Scanner (MSS). High altitude aircraft scanner data from the Airborne Thematic Mapper instrument was used to simulate TM data as well as all combinations of the three characteristics for eight data sets in all. Results for the training sites (field-center pixels) show better classification accuracies for MSS spatial resolution, TM spectral bands and TM radiometry in order of importance.

Wrigley, R. C.↗
NASA NTRS1987

Evaluating North American net primary productivity with satellite observations

An ecological model is developed to estimate annual net primary productivity (NPP) in 12 North American biomes. The model combines existing models which address canopy photosynthesis in response to light, temperature, and moisture availability, and account for respiration. Climate data, solar radiation data, and spectral vegetation index data are utilized. Estimates of NPP from the model compare well with data in the literature, but a systematic error is suspected. Difficulties encountered in specifying certain model parameters are discussed as possible sources of this error. The results of this study suggest the promise of remotely sensed measurements for macroscale evaluation and modeling of NPP.

Goward, Samuel N.↗
NASA NTRS1990

Temporally and spatially resolved flow in a two-stage axial compressor. Part 2: Computational assessment

Fluid dynamics of turbomachines are complicated due to aerodynamic interactions between rotors and stators. It is necessary to understand the aerodynamics associated with these interactions in order to design turbomachines that are both light and compact as well as reliable and efficient. The current study uses an unsteady, thin-layer Navier-Stokes zonal approach to investigate the unsteady aerodynamics of a multi-stage compressor. Relative motion between rotors and stators is made possible by use of systems of patched and overlaid grids. Results have been computed for a 2 1/2-stage compressor configuration. The numerical data compares well with experimental data for surface pressures and wake data. In addition, the effect of grid refinement on the solution is studied.

Gundy-Burlet, Karen L.↗
NASA NTRS1998

[MODIS Investigation]

The objective of the last six months were: (1) Continue analysis of Hawaii Ocean Time-series (HOT) bio-optical mooring data, and Southern Ocean bio-optical drifter data; (2) Complete development of documentation of MOCEAN algorithms and software for use by MOCEAN team and GLI team; (3) Deploy instrumentation during JGOFS cruises in the Southern Ocean; (4) Participate in test cruise for Fast Repetition Rate (FRR) fluorometer; (5) Continue chemostat experiments on the relationship of fluorescence quantum yield to environmental factors; and (6) Continue to develop and expand browser-based information system for in situ bio-optical data. We are continuing to analyze bio-optical data collected at the Hawaii Ocean Time Series mooring as well as data from bio-optical drifters that were deployed in the Southern Ocean. A draft manuscript has now been prepared and is being revised. A second manuscript is also in preparation that explores the vector wind fields derived from NSCAT measurements. The HOT bio-optical mooring was recovered in December 1997. After retrieving the data, the sensor package was serviced and redeployed. We have begun preliminary analysis of these data, but we have only had the data for 3 weeks. However, all of the data were recovered, and there were no obvious anomalies. We will add second sensor package to the mooring when it is serviced next spring. In addition, Ricardo Letelier is funded as part of the SeaWiFS calibration/validation effort (through a subcontract from the University of Hawaii, Dr. John Porter), and he will be collecting bio-optical and fluorescence data as part of the HOT activity. This will provide additional in situ measurements for MODIS validation. As noted in the previous quarterly report, we have been analyzing data from three bio-optical drifters that were deployed in the Southern Ocean in September 1996. We presented results on chlorophyll and drifter speed. For the 1998 Ocean Sciences meeting, a paper will be presented on this data set, focusing on the diel variations in fluorescence quantum yield. Briefly, there are systematic patterns in the apparent quantum yield of fluorescence (defined as the slope of the line relating fluorescence/chlorophyll and incoming solar radiation). These systematic variations appear to be related to changes in the circulation of the Antarctic Polar Front which force nutrients into the upper ocean. A more complete analysis will be provided in the next Quarterly report.

Abbott, Mark R.↗
NASA NTRS1998

Improving Acoustic Models by Watching Television

Obtaining sufficient labelled training data is a persistent difficulty for speech recognition research. Although well transcribed data is expensive to produce, there is a constant stream of challenging speech data and poor transcription broadcast as closed-captioned television. We describe a reliable unsupervised method for identifying accurately transcribed sections of these broadcasts, and show how these segments can be used to train a recognition system. Starting from acoustic models trained on the Wall Street Journal database, a single iteration of our training method reduced the word error rate on an independent broadcast television news test set from 62.2% to 59.5%.

Witbrock, Michael J.↗
NASA NTRS2000

The Dependence of Ocean Surface Emissivity on Wind Vector as Measured with TMR

Global TMR brightness temperature observations at 18, 21, and 37 GHz have been colocated with near-simultaneous SeaWinds wind vector data as well as with a monthly SST climatological product. The combined data allow us to study the dependence of ocean surface emissivity, at each frequency, upon both wind speed and direction. Results show a clear two-branch wind speed dependence; weak and linear below 6 m/s with an abrupt increase in sensitivity above that point. Our analysis also shows that the nadir-view ocean surface emissivity depends on the angle between the wind direction and TMR's antenna polarization orientation.

Tran, N.↗
NASA NTRS2001

Combining TOPEX and SeaWinds Data to Refine Models for Ocean Surface Emissivity: Wind Vector Signatures at 18, 21 and 37 GHz

TOPEX Microwave Radiometer (TMR) brightness temperature observations at 18, 21, and 37 GHz have been collocated with near-simultaneous SeaWinds wind vector data as well as with a monthly SST climatological product. The combined data set allows us to study the dependence of ocean surface emissivity (at each frequency) upon both wind speed. Results show clear two-branch wind speed dependence; weak and linear below 6 m/s with an abrupt increase in sensitivity above that point. The analysis also shows that the zenith-directed ocean surface emissivity is polarization dependent above wind speeds of 5-6 m/s with an azimuthal variation related to the wind direction. This last result accords with recent polarimetric radiometer observations collected from aircraft. Implications of these observations to water vapor retrieval algorithms, nadir-viewing polarimetry, and ocean emission modeling will be discussed.

Vandemark, D.↗
NASA NTRSDate not supplied

Comparison of OVERFLOW Computational and Experimental Results for a Blunt Mars Entry Vehicle Concept During Supersonic Retropropulsion

Simulations of supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle were performed using the Overflow Computational Fluid Dynamics (CFD) solver. Simulation conditions and geometry were designed to match specific test runs in the Descent System Study (DSS) testing campaign. The relative accuracy of simulation predictions are assessed by direct comparison to experimental data. Computational predictions of the SRP flowfield and bow shock shape are compared to experimental schlieren images. Comparisons of the model surface pressure environment are presented for unsteady and static discrete tap data as well as time-averaged Pressure-Sensitive Paint (PSP) data.

Supersonic Retropropulsion↗
DOE OSTI2013

BDDR, a new CEA technological and operating reactor database

The new application BDDR (Reactor database) has been developed at CEA in order to manage nuclear reactors technological and operating data. This application is a knowledge management tool which meets several internal needs: -) to facilitate scenario studies for any set of reactors, e.g. non-proliferation assessments; -) to make core physics studies easier, whatever the reactor design (PWR-Pressurized Water Reactor-, BWR-Boiling Water Reactor-, MAGNOX- Magnesium Oxide reactor-, CANDU - CANada Deuterium Uranium-, FBR - Fast Breeder Reactor -, etc.); -) to preserve the technological data of all reactors (past and present, power generating or experimental, naval propulsion,...) in a unique repository. Within the application database are enclosed location data and operating history data as well as a tree-like structure containing numerous technological data. These data address all kinds of reactors features and components. A few neutronics data are also included (neutrons fluxes). The BDDR application is based on open-source technologies and thin client/server architecture. The software architecture has been made flexible enough to allow for any change. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Sedimentary Geothermal Feasibility in Eastern Nevada and Millard County, Utah Well Databases

In order to gather data to assess sedimentary geothermal feasibility in Nevada and Utah, state oil and gas and geothermal databases were serached for well files and well logs. Well data from the Nevada Bureau of Mines and Geology oil and gas and geothermal databases was mined for the following areas in Nevada: Blackburn oil field, Marys River, North Willow Creek, Tomera Ranch, and Diamond Valley, all in the Elko Basin; Bacon Flat in Railroad Valley; and Steptoe Basin. For Pavant Butte in Utah, the State of Utah Division of Oil and Gas Well File and Well Log Searches were mined for well records in Millard County. Only wells close to Pavant Butte were mined for detailed information, but all Millard County wells are included in the database. Well files were searched for temperature, permeability, pressure information, and formation depth and thickness. Temperature values are uncorrected. Locations for some wells were converted from township and range locations to approximate latitude and longitude using Google Earth and Earth Point grids to locate well pads. If no well pad could be located for a well, the center of the smallest section available (usually partsect) was used as the approximate location.

15 GEOTHERMAL ENERGY↗
NASA NTRS1993

Investigation of spectral analysis techniques for randomly sampled velocimetry data

It is well known that velocimetry (LV) generates individual realization velocity data that are randomly or unevenly sampled in time. Spectral analysis of such data to obtain the turbulence spectra, and hence turbulence scales information, requires special techniques. The 'slotting' technique of Mayo et al, also described by Roberts and Ajmani, and the 'Direct Transform' method of Gaster and Roberts are well known in the LV community. The slotting technique is faster than the direct transform method in computation. There are practical limitations, however, as to how a high frequency and accurate estimate can be made for a given mean sampling rate. These high frequency estimates are important in obtaining the microscale information of turbulence structure. It was found from previous studies that reliable spectral estimates can be made up to about the mean sampling frequency (mean data rate) or less. If the data were evenly samples, the frequency range would be half the sampling frequency (i.e. up to Nyquist frequency); otherwise, aliasing problem would occur. The mean data rate and the sample size (total number of points) basically limit the frequency range. Also, there are large variabilities or errors associated with the high frequency estimates from randomly sampled signals. Roberts and Ajmani proposed certain pre-filtering techniques to reduce these variabilities, but at the cost of low frequency estimates. The prefiltering acts as a high-pass filter. Further, Shapiro and Silverman showed theoretically that, for Poisson sampled signals, it is possible to obtain alias-free spectral estimates far beyond the mean sampling frequency. But the question is, how far? During his tenure under 1993 NASA-ASEE Summer Faculty Fellowship Program, the author investigated from his studies on the spectral analysis techniques for randomly sampled signals that the spectral estimates can be enhanced or improved up to about 4-5 times the mean sampling frequency by using a suitable prefiltering technique. But, this increased bandwidth comes at the cost of the lower frequency estimates. The studies further showed that large data sets of the order of 100,000 points, or more, high data rates, and Poisson sampling are very crucial for obtaining reliable spectral estimates from randomly sampled data, such as LV data. Some of the results of the current study are presented.

Sree, Dave↗
DOE OSTI2019

Application of a new hybrid particle swarm optimization-mixed kernels function-based support vector machine model for reservoir porosity prediction: A case study in Jacksonburg-Stringtown oil field, West Virginia, USA

Porosity is a fundamental property that characterizes the storage capability of fluid and gas-bearing formations in a reservoir. An accurate porosity value can be measured from core samples in the laboratory; however, core analysis is expensive and time consuming. Well-log data can be used to calculate porosity, but the availability of log suites is often limited in mature fields. Therefore, robust porosity prediction requires integration of core-measured porosity with available well-log suites to control for changes in lithology and fluid content. A support vector machine (SVM) model with mixed kernel function (MKF) is used to construct the relationship between limited conventional well-log suites and sparse core data. Porosity is the desired output, and two conventional well-log responses (gamma ray [GR] and bulk density) and three well-log-derived parameters (the slope of GR, the slope of density, and [Formula: see text]) are input parameters. A global stochastic searching algorithm, particle swarm optimization (PSO), is applied to improve the efficiency of locating the appropriate values of five control parameters in MKF-SVM model. The results of SVM with different traditional kernel functions were compared, and the MKF-SVM model provided an improvement over the traditional SVM model. To confirm the advantage of the hybrid PSO-MKF-SVM model, the results from three models: (1) radial basis function (RBF)-based least-squares SVM, (2) multilayer perceptron artificial neural network (ANN), and (3) RBF ANN, are compared with the result of the hybrid PSO-MKF-SVM model. The results indicate that the hybrid PSO-MKF-SVM model improves porosity prediction with the highest correlation coefficient ([Formula: see text] of 0.9560), the highest coefficient of determination ([Formula: see text] of 0.9140), the lowest root-mean-square error (1.6505), average absolute error value (1.4050), and maximum absolute error (2.717).

Geochemistry & Geophysics↗
DOE OSTI2026

Comparison of CNN-Based Image Classification Approaches for Implementation of Low-Cost Multispectral Arcing Detection

Camera-based sensing has benefited in recent years from developments in machine learning data processing methods, as well as improved data collection options such as Unmanned Aerial Vehicles (UAV) mounted sensors. However, cost considerations, both for the initial purchase of sensors as well as updates, maintenance, or potential replacement if damaged, can limit adoption of more expensive sensing options for some applications. To evaluate more affordable options with less expensive, more available, and more easily replaceable hardware, we examine the use of machine learning-based image classification with custom datasets, utilizing deep learning based-image classification and the use of ensemble models for sensor fusion. Utilizing the same models for each camera to reduce technical overhead, we showed that for a very representative training dataset, camera-based detection can be successful for detection of electrical arcing. We also use multiple validation datasets, based on conditions expected to be of varying difficulty, to evaluate custom data. These results show that ensemble models of different data sources can mitigate risks from gaps in training data, though the system will be less redundant for those cases unless other precautions are taken. We found that with good quality custom datasets, data fusion models can be utilized without specialization in design to the specific cameras utilized, allowing for less specialized, more accessible equipment to be utilized as multispectral camera components. This approach can provide an alternative to expensive sensing equipment for applications in which lower-cost or more easily replaceable sensing equipment is desirable.

convolutional neural networks↗
DOE OSTI2024

Evaluating the Nation's Pipeline Infrastructure with NETL's Advanced Infrastructure Integrity Model (AIIM)

This poster is a part of BIL-EDX4CCS Task 36: Advanced Infrastructure Integrity Modeling to Evaluate Existing Energy Infrastructure Reusability and Risk, the goal of which is to produce a smart tool that will assess existing energy infrastructure reusability and risk using the Advanced Infrastructure Integrity Model (AIIM). This model forecasts lifespan and potential risk using a multitude of factors such as incidents reports, structural characteristics, and the surrounding environment. The project aims to provide scientific insights for a better understanding of carbon storage (CS), potential to support CS stakeholder needs, national decarbonization, and mitigating climate change. AIIM will utilize an energy infrastructure database as its input, developed by acquiring publicly available data as well as NETL derived products. These resources include incidents, geohazards, and infrastructure variables. Soil data in the form of rasters and pipeline incident reports were processed and a script was developed to count the number of times features such as roads, railroads, and rivers intersected with pipeline segments which were then converted to points. Distance to oil and natural gas wells, petroleum ports, intermodal freight facilities, and geologic structures were also calculated. After data preparation and quality control was completed, the data was integrated into the pipeline points. Once models are complete, a smart tool will be created in the form of an online dashboard.

Malay, Caleb↗
DOE OSTI2019

Statistical analyses of reservoir and fracturing parameters for a multifractured shale oil reservoir in Mississippi

The use of multifractured horizontal wells has improved the efficiency of hydrocarbon extraction from shale gas and oil plays. It is highly desirable to estimate the characteristics of the reservoir and well fracturing through production data analysis. Production rate transient data from 16 wells in the Mississippi sections were analyzed to estimate local reservoir permeability and hydraulic fracture parameters. Key factors affecting well productivity have been identified for optimizing future well completion. Based on the theory of distance of investigation during transient linear flow, the reservoir matrix permeability of TMS was estimated to be between 53 nd and 210 nd, averaging at 116 nd. The matrix permeability follows the lognormal distribution and is considered homogeneous according to the coefficient of variation. The fracture half-length was estimated using the matrix permeability data from the rate transient analysis. The fracture half-length was found to have a mean value of 234 ft with a standard deviation of 66 ft in a normal distribution. The fracture conductivity was back-calculated by matching pseudosteady production rate data to Guo et al's (SPE Reserve Eval Eng.12, 2009, 879) productivity model for boundary-dominated flow. The fracture conductivity was estimated to range from 0.4 md-ft to 3.2 md-ft, averaging at 1.4 md-ft. Based on Guo et al's (SPE Reserve Eval Eng.12, 2009, 879) well productivity model applied to TMS condition, well productivity can be improved significantly by increasing fracture length and conductivity. Future TMS wells should be completed with conductivity values of greater than 10 md-ft.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2016

Reservoir response to thermal and high-pressure well stimulation efforts at Raft River, Idaho

An injection stimulation test begun at the Raft River geothermal reservoir in June, 2013 has produced a wealth of data describing well and reservoir response via high-resolution temperature logging and distributed temperature sensing, seismic monitoring, periodic borehole televiewer logging, periodic stepped flow rate tests and tracer injections before and after stimulation efforts. One of the primary measures of response to the stimulation is the relationship between fluid pressure and flow rate, short-term during forced flow rate changes and the long-term change in injectivity. In this paper we examine that hydraulic response using standard pumping test analysis methods, largely because pressure response to the stimulation was not detected, or measurable, in other wells. Analysis of stepped rate flow tests supports the inference from other data that a large fracture, with a radial extent of one to several meters, intersects the well in the target reservoir, suggests that the flow regime is radial to a distance of only several meters and demonstrates that the pressure build-up cone reaches an effective constant head at that distance. The well’s longer term hydraulic response demonstrated continually increasing injectivity but at a dramatically faster rate later from ~2 years out and continuing to the present. The net change in injectivity is significantly greater than observed in other longterm injectivity monitoring studies, with an approximately 150–fold increase occurring over ~2.5 years. While gradually increasing injectivity is a likely consequence of slow migration of a cooling front, and consequent dilation of fractures, the steady, ongoing, rate of increase is contrary to what would be expected in a radial or linear flow regime, where the cooling front would slow with time. As a result, occasional step-like changes in injectivity, immediately following high-flow rate tests suggest that hydro shearing during high-pressure testing altered the near-well permeability structure.

15 GEOTHERMAL ENERGY↗