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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.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ultra-Long Distance BOTDA Sensor System Employing Hybrid Amplification and Advanced Noise Reduction Techniques

Brillouin Optical Time Domain Analysis (BOTDA) sensor system play a pivotal role in distributed sensing, which enables precise measurements of strain and temperature across extensive fiber lengths. Nonetheless, challenges emerge as distances grow due to signal attenuation and noise interference resulting in measurement errors. This research offers a comprehensive strategy to extend the sensing range of BOTDA systems beyond 10’s of kilometers while maintaining high spatial resolutions. Such enhanced sensing is realized through the integration of distributed Raman amplification, inline amplification using erbium-doped fiber amplifiers (EDFA), and advanced noise reduction techniques. Leveraging inherent redundancy in measured data as a function of frequency and fiber distance, the non-local means (NLM) filter removes noise while preserving essential physical information. This approach proves particularly advantageous in BOTDA systems, where accurate measurement of Brillouin scattering signals is paramount for long-range sensing, while concurrently safeguarding high spatial resolutions. In summary, this research has shown a holistic exploration of extending BOTDA's distance sensing capabilities up to 150 km with spatial resolutions of 8 meters.

Bhatta, Hari↗
DOE OSTI2024

Ultra-Long Distance BOTDA Sensor System Employing Hybrid Amplification and Advanced Noise Reduction Techniques

Brillouin Optical Time Domain Analysis (BOTDA) sensor systems play a pivotal role in distributed sensing, which enables precise measurements of strain and temperature across extensive fiber lengths. This research offers a comprehensive strategy to extend the sensing range of BOTDA systems beyond tens of kilometers while maintaining high spatial resolutions. Such enhanced sensing is realized through the integration of distributed Raman amplification, inline amplification using erbium-doped fiber amplifiers (EDFA), and advanced noise reduction techniques. Optimizing Raman pump and probe wave profiles ensures the robustness of Brillouin scattering signals, effectively countering attenuation-induced losses. Additionally, enhancing weak Brillouin signals by strategically placing EDFAs at optimal fiber locations keeps sensor sensitivity high. Leveraging inherent redundancy in measured data as a function of frequency and fiber distance, the non-local means (NLM) filter removes noise while preserving essential physical information. In summary, this research has shown a holistic exploration of extending BOTDA’s distance sensing capabilities up to 150 km with spatial resolutions of 8 meters.

Bhatta, Hari↗
DOE OSTI2012

Interpreting Temperature Strain Data from Meso-Scale Clathrate Experiments

Gas hydrates are important in global climate change, carbon sequestra- tion, and seafloor stability. Currently, formation and dissociation pathways are poorly defined. We present a new approach for processing large amounts of data from meso-scale experiments, such as the LUNA distributed sensing system (DSS) in the seafloor process simulator (SPS) at Oak Ridge National Laboratory. The DSS provides a proxy for temperature measurement with a high spatial resolution allowing the heat of reaction during gas hydrate formation/dissociation to aid in locating clathrates in the vessel. The DSS fibers are placed in the sediment following an Archimedean spiral design and then the position of each sensor is solved by iterating over the arc length formula with Newtons method. The data is then gridded with 1 a natural neighbor interpolation algorithm to allow contouring of the data. The solution of the sensor locations is verified with hot and cold stimulus in known locations. An experiment was preformed with a vertically split column of sand and silt. The DSS system clearly showed hydrate forming in the sand first, then slowly creeping into the silt. Similar systems and data processing techniques could be used for monitoring of hydrates in natural environments or in any situation where a hybrid temperature/strain index is useful. Further ad- vances in fiber technology allow the fiber to be applied in any configuration and the position of each sensor to be precisely determined making practical applications easier.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Application of predictive data analytics to model daily hydrocarbon production using petrophysical, geomechanical, fiber-optic, completions, and surface data: A case study from the Marcellus Shale, North America

Predicting gas production from stimulated unconventional reservoirs has always been a challenge to oil and gas companies because the physics of fluid flow through such reservoirs is not well understood. On the other hand, modeling gas production from shale reservoirs is a complex multi-variate problem that requires proper integration of data from multiple disciplines, such as geology, petrophysics, geomechanics, completions, and surface-based measurements, etc. Here this study demonstrates the application of data-driven machine learning algorithms, integrating geoscientific, distributed acoustic sensing (DAS), distributed temperature sensing (DTS) fiber-optic, completions, flow scanner production log, and surface data to model daily gas production from a 28-stage stimulated horizontal well drilled in the Marcellus Shale of the Appalachian basin in North America. In addition, this study aims to utilize the data from a fiber-optic monitoring system, such as DAS and DTS to evaluate the well performance. We build supervised data-driven machine learning models using Random Forest (RF), Artificial Neural Network (ANN), and Support Vector Machine (SVM) algorithms to understand the well performance and forecast the daily gas production. The study compares the forecasted results, tests the level of accuracy, and addresses different issues with these machine learning algorithms. A spatio-temporal database is constructed and used to perform sensitivity analyses to identify the key drivers for gas production. The results show that RF and ANN algorithms can be used to predict daily gas production with significantly high accuracy; however, RF algorithm is the best predictor in terms of highest accuracy (96%), less computational time and cost. Based on sensitivity analysis, it appears that Poisson's ratio, minimum horizontal stress, DAS, casing pressure, gamma log are the most important parameters to predict gas production.

02 PETROLEUM↗
DOE OSTI2025

Distributed Fiber Optic Sensing for in-well hydraulic fracture monitoring

This study presents the results from in-well hydraulic fracture monitoring within a horizontal well in an unconventional reservoir utilizing Distributed Fiber Optic Sensing (DFOS). An in-house-developed Brillouin-based Distributed Strain Sensing (DSS) interrogator was deployed to obtain strain measurements, complemented by a commercial Raman-based Distributed Temperature Sensing (DTS) interrogator for temperature measurements and a commercial Rayleigh-based Low-Frequency Distributed Acoustic Sensing (LF-DAS) interrogator for strain-rate measurements. Examined over a ten-day period, the spatio-temporal distribution of temperature-compensated strain obtained from DSS and DTS revealed distinct signatures of the multi-stage hydraulic fracturing process. These signatures were analyzed with respect to fracture width growth and closure, residual strain effects, and fracture conductivity near the wellbore. Fracture widths within the fracture zone were estimated for individual stages. The findings were assessed with LF-DAS measurements for further evaluation. This work integrates DFOS-measured strain, temperature, and strain-rate data for monitoring in-well hydraulic fracturing, with the goal of supporting future studies in interpreting DFOS measurements for improved understanding of hydraulic fracturing in unconventional reservoirs.

58 GEOSCIENCES↗
DOE OSTI2022

Fiber-optic sensor packaging assessment and benchmarking for embedded sensing applications

Fiber optic-based sensing for non-destructive evaluation (NDE) and structural health monitoring of various infrastructure and energy assets is an increasingly important sensing scheme. Because of their immunity to electromagnetic interferences, versatility in sensing mechanisms and designs as well as capability for distributed sensing, the fiber optic sensing is of great interest for embedding within infrastructures using advanced manufacturing methods. However, the protection of fiber optic sensors during advanced manufacturing-based embedding is an important aspect for infrastructure monitoring in practice. While successful installation of fiber optic sensors has been accomplished through application of epoxy or adhesives on infrastructure surfaces, there has been only limited investigation of fiber protection packaging schemes which are compatible with in-situ repair techniques such as the metallic cold-spray. With increasing interest and importance of cold spray-based repair processes, the integration of fiber optic sensors simultaneously during the repair is equally important. In this work, we focus our efforts on investigating various types of packaging schemes for their compatibility and integrability on the surfaces of metallic structures such as oil and gas pipelines during an in-situ repair coating. First, we consider sandblasting using silica sand particles of various size for optical fibers on the surface of a metallic coupon as a useful proxy test of sensor packaging stability. Structural damage of packaging is characterized by means of optical microscopy and the optical integrity of embedded fiber optic cables is examined using optical backscatter reflectometry (OBR). In addition, initial investigation of metallic cold-spray embedded fiber optic cables under various packaging on metallic substrates is also considered with early conclusions and future directions.

Fiber-optic sensors, Sensors packaging, Metallic C↗
DOE OSTI2011

Fiber Optic Sensing Technology for Detecting Gas Hydrate Formation and Decomposition

A fiber optic-based distributed sensing system (DSS) has been integrated with a large volume (72 L) pressure vessel providing high spatial resolution, time resolved, 3-D measurement of hybrid temperature-strain (TS) values within experimental sediment gas hydrate systems. Areas of gas hydrate formation (exothermic) and decomposition (endothermic) can be characterized through this proxy by time series analysis of discrete data points collected along the length of optical fibers placed within a sediment system. Data is visualized as a 'movie' of TS values along the length of each fiber over time. Experiments conducted in the Seafloor Processing Simulator (SPS) at Oak Ridge National Laboratory show clear indications of hydrate formation and dissociation events at expected P-T conditions given the thermodynamics of the CH4-H2O system. The high spatial resolution achieved with fiber optic technology makes the DSS a useful tool for visualizing time resolved formation and dissociation of gas hydrates in large-scale sediment experiments.

fiber optics↗
DOE OSTI2021

Distributed electric field sensing using fibre optics in borehole environments

In the past decade, rapid advances in distributed optical fibre sensing technologies have made it possible to record various geophysical data (e.g. strain, temperature and pressure) continuously in both time and space along the fibre, providing an unprecedented quantity and spatial density of data compared to traditional geophysical measurements as well as reducing data acquisition cost. To date, no distributed fibre-based electromagnetic field sensing system has been implemented although electromagnetic sensing could have a broad range of applications to geophysical imaging and monitoring in borehole environments. The goal of this paper is to provide a theoretical feasibility study regarding the design and use of an electromagnetic sensing optical fibre for geophysical applications. First, we present the sensitivity analysis of a ‘hypothetical’ optical fibre coated with polyvinylidene fluoride, a polymer that provides relatively high piezoelectric properties, yet unlike ceramics, is flexible. Next, using a two-dimensional electromagnetic modelling algorithm, we simulate the earth electric-field-to-fibre-strain transfer function and estimate the theoretical sensitivity of the optical fibre to electric fields. Given the state-of-the-art distributed acoustic sensing strain sensitivities in the picometres strain range, our numerical modelling analysis suggests that a perfectly coupled polyvinylidene fluoride–coated optical fibre can measure electric field values in the mV/m to V/m amplitude range. We then apply a cylindrically symmetric modelling algorithm to simulate numerical models demonstrating the applicability of such a fibre in an oilfield environment. Scenarios investigated employ an electric field source and suggest that the measurements can be used to distinguish the oil versus water ratio with a fibre mounted inside a producing steel cased oil well as well as distinguishing between brine and hydrocarbon filled reservoir zones with a fibre located outside of the casing.

58 GEOSCIENCES↗
DOE OSTI2016

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping

The reliability of computational fluid dynamics (CFD) codes is checked by comparing simulations with experimental data. A typical data set consists chiefly of velocity and temperature readings, both ideally having high spatial and temporal resolution to facilitate rigorous code validation. While high resolution velocity data is readily obtained through optical measurement techniques such as particle image velocimetry, it has proven difficult to obtain temperature data with similar resolution. Traditional sensors such as thermocouples cannot fill this role, but the recent development of distributed sensing based on Rayleigh scattering and swept-wave interferometry offers resolution suitable for CFD code validation work. Thousands of temperature measurements can be generated along a single thin optical fiber at hundreds of Hertz. Sensors function over large temperature ranges and within opaque fluids where optical techniques are unsuitable. But this type of sensor is sensitive to strain and humidity as well as temperature and so accuracy is affected by handling, vibration, and shifts in relative humidity. Such behavior is quite unlike traditional sensors and so unconventional installation and operating procedures are necessary to ensure accurate measurements. This paper demonstrates implementation of a Rayleigh scattering-type distributed temperature sensor in a thermal mixing experiment involving two air jets at 25 and 45 °C. We present criteria to guide selection of optical fiber for the sensor and describe installation setup for a jet mixing experiment. We illustrate sensor baselining, which links readings to an absolute temperature standard, and discuss practical issues such as errors due to flow-induced vibration. This material can aid those interested in temperature measurements having high data density and bandwidth for fluid dynamics experiments and similar applications. We highlight pitfalls specific to these sensors for consideration in experiment design and operation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Feature Extraction for Pipeline Defects Inspection Based Upon Distributed Acoustic Fiber Optic Sensing Data

Fiber-optic distributed acoustic sensing (DAS) is becoming an increasingly important tool for real-time monitoring of energy and civil infrastructure structural health such as pipelines. We present a systematic theoretical study of the potential for DAS to be directly coupled with guided ultrasonic waves typically used in conventional acoustic non-destructive evaluation (NDE) methods for real-time pipeline health monitoring. We are referring to this innovative new NDE technique as ultrasonic guided wave and optical fiber sensor fusion. In the practical application of DAS coupled with guided ultrasonic waves, the structural design of (1) the specific guided waves excited, (2) the physical installation of the acoustic transducers and the fiber optic sensors, and (3) the functional performance specifications (gauge length, sensitivity, Etc.) of fiber optic DAS have an important influence on overall capabilities of the monitoring system. Meanwhile, physics-based analysis of acoustic waves is still a challenge due to the complex nature of the Lamb wave when it propagates, scatters, and disperses in the presence of structural defects. In this work, we simulate carbon steel pipes relevant for oil and gas pipeline applications with diameters of approximately 6-12” and wall thickness of 0.5” as the objects to be monitored. By establishing and implementing these capabilities, we seek to pursue an in-depth study on structural parameter optimization of DAS network, measurement range, and signal processing with an ultimate goal of increasing the sensitivity and efficacy of DAS to defect identification for various modes of corrosion expected in practice. To study the characteristics of scattered acoustic waves and performance of DAS for defect identification, we simulated the response of DAS for multiple pipe structures, defect types, and DAS sensor network configuration using finite element software Ansys, then the properties of signal response are extracted to construct defect-sensitive features. The raw data simulated, and the associated features extracted can ultimately be utilized as annotated training data to benchmark various designs for DAS applications, guided acoustic excitation sources, and learning model parameters to enhance early detection of potentially problematic defects.

Pipeline Defects Inspection, Fiber-optic sensors, ↗
DOE OSTI2021

Microwave–photonic low-coherence interferometry for dark zone free distributed optical fiber sensing

A microwave–photonic low-coherence interferometry (MPLCI) system is proposed for fully distributed optical fiber sensing. Assisted by an unbalanced Michelson interferometer, a low-coherence laser source is used to interrogate cascaded Fabry–Perot interferometers along with an optical fiber for a dark zone free (or spatially continuous) distributed measurement. Here, by combining the advantages of microwaves and photonics, the MPLCI system can synergistically achieve high sensitivity and high spatial resolution. Our tests have confirmed a strain resolution of 95 nε at the spatial resolution of 10 cm.

42 ENGINEERING↗
DOE OSTI2017

High spatial resolution fiber optical sensors for simultaneous temperature and chemical sensing for energy industries

This paper demonstrates optical fibers as high-temperature sensor platforms. Through engineering and onfiber integration of functional metal oxide sensory materials, we report the development of an integrated sensor solution to perform temperature and chemical measurements for high-temperature energy applications. Using the Rayleigh optical frequency domain reflectometry (OFDR) distributed sensing scheme, the temperature and hydrogen concentration were measured along the fiber. To overcome the weak Rayleighbackscattering intensity exhibited by conventional optical fibers, an ultrafast laser was used to enhance the Rayleigh scattering by a direct laser writing method. Using the Rayleigh-enhanced fiber as sensor platform, both temperature and hydrogen reaction were monitored at high temperature up to 750°C with 4-mm spatial resolution.

Yan, Aidong↗