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16th International Conference on Greenhouse Gas Technologies (GHGT-16), Lyon, France, October 23-27, 2022
The monitoring of multiphase flow is an established process that has spanned several decades. This paper demonstrates the use of acoustic emission (AE) technology to investigate sand transport characteristic in three-phase (air-water-sand) flow in a horizontal pipe where the superficial gas velocity (VSG) had a range of between 0.2 ms{sup −1} to 2.0 ms{sup −1} and superficial liquid velocity (VSL) had a range of between 0.2 ms{sup −1} to 1.0 ms{sup −1}. The experimental findings clearly show a correlation exists between AE energy levels, sand concentration, superficial gas velocity (VSG) and superficial liquid velocity (VSL)
Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.
Additive manufacturing (AM) has attracted considerable attention in recent years. This technology overcomes the geometrical limits of workpieces produced with the traditional subtractive methods and so gives the opportunity to manufacture highly complex shapes. Unfortunately, the repeatability of the manufacturing process and the monitoring of quality are not reliable enough to be utilized in mass production. The quality monitoring of AM processes in commercial equipment has been largely based on temperature measurements of the process zone or high-resolution imaging of the layers. However, both techniques lack information about the physical phenomena taking place in the depth of the materials medium and this limits their reliability in real-life applications. To overcome those restrictions, we propose to combine acoustic emission and reinforcement learning. The former captures the information about the subsurface dynamics of the process. The latter is a branch of machine learning that allows interpreting the received data in terms of quality. The combination of both is an original method for in situ and real-time quality monitoring. Acoustic data were collected during a real process using a commercial AM machine. The process parameters were selected to achieve three levels of quality in terms of porosity concentration while manufacturing a stainless steel 316L cuboid shape. Using our method, we demonstrated that each level of quality produced unique acoustic signatures during the build that were recognized by the classifier. The classification accuracy reached in this work proves that the proposed method has high potential to be used as in situ and real-time monitoring of AM quality.
We report active acoustic sensors are widely used in oceanographic and environmental studies. Although many have nominal operating frequencies above the range of marine mammal hearing, they can produce out-of-band sound that may be audible to marine mammals. Acoustic emissions from four active acoustic transducers were characterized and compared to marine mammal hearing thresholds. All four transducers had nominal operating frequencies above the reported upper limit of marine mammal hearing, but produced measurable sound below 160 kHz. A spatial map of the acoustic emissions of each sonar is used to evaluate potential effects on marine mammal hearing when the transducer is continuously operated from a stationary platform. Based on the cumulative sound exposure level metric, the acoustic emissions from the transducers are unlikely to cause temporary threshold shifts in marine mammals, but could affect animal behavior. The extent of audibility is estimated to be, at most, on the order of 100 m.
This is the final technical report for the Virginia Tech Center for Photonics Technology (VT-CPT) research project entitled “Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays”. In the the four-year effort, VT-CPT collaborated with the Departments of Mathmatics at VT and Sentek Instrument, LLC (Sentek) to develop a fiber-optic sensing system capable of real-time simultaneous distributed measurement of multiple subsurface, drilling, and production parameters. The ultra-sensitive fiber optic distributed acoustic sensing technology, picoDAS, developed by Sentek was integrated with a novel multi-material optical sensing fiber fabricated by CPT-VT to obtain distributed acoustic and magnetic field measurements with ultrahigh sensitivity and high spatial resolution. The sensing technology successfully developed and demonstrated under this research program is truly unique has application beyond subsurface imaging to include carbon storage and electrical grid monitoring, as well as healthcare and nuclear fusion. The project, sponsored by the Advanced Technology Program, began in 2019 and had the original goal of developing the next generation of harsh environment sensing systems. Exhaustive theoretical modeling was performed to optimize the multi-material optical fiber design. VT developed the processing techniques employed to successfully fabricate single mode fibers with metal cladding wires. Sensing fibers with nickel and Metglas cladding wires were fully characterized, inscribed with sensors, and fully integrated with the picoDAS system. Laboratory scale testing was performed to demonstrate performance upon exposure to lateral and transverse magnetic fields. Preliminary field trials were performed for prototype magnetic and acoustic sensing systems upon near surface deployment at VT. The distributed acoustic and magnetic field sensing system was advanced from a (Technology Readiness Level) TRL=2 to a TRL=5 via laboratory scale system validation in relevant environments. The truly one-of-its kind distributed magnetic and acoustic sensing system is expected to find immediate applications that require subsurface monitoring, to include carbon storage site monitoring, and has the potential to be a distributive technology in healthcare and electric grid markets. The technologies developed by Virginia Tech’s Center for Photonics Technology will support the mission of the National Energy Technology Laboratory (NETL) to drive innovation and deliver solutions for an environmentally sustainable and prosperous energy future by ensuring affordable, abundant, and reliable energy that drives a robust economy and national security. Technical accomplishments during the program are summarized briefly here and described in detail in the remainder of the report.
A modular borehole monitoring concept has been implemented to provide a suite of well-based monitoring tools that can be deployed cost effectively in a flexible and robust package. The initial modular borehole monitoring system was deployed as part of a CO 2 injection test operated by the Southeast Regional Carbon Sequestration Partnership near Citronelle, Alabama. The Citronelle modular monitoring system transmits electrical power and signals, fibre-optic light pulses, and fluids between the surface and a reservoir. Additionally, a separate multi-conductor tubing-encapsulated line was used for borehole geophones, including a specialized clamp for casing clamping with tubing deployment. The deployment of geophones and fibre-optic cables allowed comparison testing of distributed acoustic sensing. We designed a large source effort (>64 sweeps per source point) to test fibre-optic vertical seismic profile and acquired data in 2013. The native measurement in the specific distributed acoustic sensing unit used (an iDAS from Silixa Ltd) is described as a localized strain rate. Following a processing flow of adaptive noise reduction and rebalancing the signal to dimensionless strain, improvement from repeated stacking of the source was observed. Conversion of the rebalanced strain signal to equivalent velocity units, via a scaling by local apparent velocity, allows quantitative comparison of distributed acoustic sensing and geophone data in units of velocity. We see a very good match of uncorrelated time series in both amplitude and phase, demonstrating that velocity-converted distributed acoustic sensing data can be analyzed equivalent to vertical geophones. We show that distributed acoustic sensing data, when averaged over an interval comparable to typical geophone spacing, can obtain signal-to-noise ratios of 18 dB to 24 dB below clamped geophones, a result that is variable with noise spectral amplitude because the noise characteristics are not identical. With vertical seismic profile processing, we demonstrate the effectiveness of downgoing deconvolution from the large spatial sampling of distributed acoustic sensing data, along with improved upgoing reflection quality. finally, we conclude that the extra source effort currently needed for tubing-deployed distributed acoustic sensing vertical seismic profile, as part of a modular monitoring system, is well compensated by the extra spatial sampling and lower deployment cost as compared with conventional borehole geophones.
Understanding hydraulic fracturing is crucial to improving the stimulation of unconventional reservoirs and increasing fluid production. This study develops a novel seismic monitoring technology using distributed acoustic sensing (DAS) and surface orbital vibrators (SOV) to capture fracture seismic response and mechanical properties at high temporal intervals. We analyze continuous time-lapse vertical seismic profiling (VSP) data acquired every hour during the first nine days of treatment of an unconventional reservoir in the Austin Chalk/Eagle Field Laboratory. The VSP data contain clear seismic signals scattered from the activated fractures. The spatiotemporal changes of the fracture reflectivity revealed by the SOV/DAS data correlate well with the observations of fracture locations inferred from low-frequency DAS data. These results capture the fracture opening and closure processes, as well as highlight potential prestage activations of the fractures due to hydraulic connectivity with preexisting fracture systems. Therefore, analysis of the presented data set provides a unique opportunity to understand fracture initiation and subsequent evolution, not only in the context of unconventional resources but also in enhanced geothermal systems.
The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. This report describes the monitoring study conducted to assess the effectiveness of DAS (Distributed Acoustic Sensing) -based VSP (Vertical Seismic Profiling) technology for delineating CO 2 injected into the Silurian-age pinnacle reefs in northern Michigan, the host rocks for the MRCSP Phase III demonstration project. The DAS VSP study was conducted in the Chester 16 reef, one of several reefs in Otsego County Michigan that is operated by Core Energy, LLC of Traverse City, Michigan. Time-lapse DAS VSP was implemented at the Chester 16 reef to attempt to detect approximately 85,000 tonnes of CO 2 injected into the A-1 Carbonate and Brown Niagaran Formations. A baseline survey was conducted in February 2017 prior to injecting CO 2 and a repeat survey was conducted in August 2018. During the interim period between the baseline and repeat surveys, CO 2 was injected into the Chester 16 reef via the 6-16 injection well without production (withdrawal) of fluids from the reef. A grid of 181 source positions consisting of 44 vibrator positions, plus 137 dynamite shot locations, was used to give approximately continuous spatial coverage of the injection zone (A-1 Carbonate and upper Brown Niagaran) in the area between the two wells.
Acoustic Emission monitoring is a technique that detects and records phenomena related to the elastic waves generated by the release of strain energy during crack propagation events. The sensors used for this method are highly sensitive and do not typically need to be in relatively close proximity to the indication when compared to methods such as ultrasonic or eddy current testing. This characteristic makes acoustic emission an attractive method for monitoring locations that are not readily accessible to active inspection methods, such as with in-situ examination of dry cask storage system canisters. Acoustic emission is unique among nondestructive evaluation (NDE) methods as emission is caused by the energy released from the object inspected. Most NDE methods require that energy be introduced to the part from an external source; which is not necessary with acoustic emission. Acoustic emission signals are created during crack growth and plastic deformation. EPRI has been investigating the feasibility of using acoustic emission as a complementary NDE method for monitoring the structural condition of dry fuel storage canisters. To assess this feasibility three first of a kind field trials were conducted over a one year period. The goals of the field trials were to determine the potential path forward for the method and to assess needs for further research and development. Why this matters: The study evaluated the efficacy of structural health monitoring methods to support ISFSI license renewal commitments to support aging management of welded stainless steel canisters. (authors)
University of Pittsburgh’s Transducer lab has teamed with the U.S. Department of Energy’s National Energy Technology Laboratory (DOE NETL) to conduct a comprehensive study to develop/evaluate low-cost, efficient CO 2 measuring technologies for geological sequestration sites leakage monitoring. A passive wireless CO 2 sensing system based on surface acoustic wave technology and carbon nanotube nanocomposite was developed. Surface acoustic wave device was studied to determine the optimum parameters. Delay line structure was adopted as basic sensor structure. CNT polymer nanocomposite was fabricated and tested under different temperature and strain condition for natural environment impact evaluation. Nanocomposite resistance increased for 5 times under pure strain, while the temperature dependence of resistance for CNT solely was -1375ppm/°C. The overall effect of temperature on nanocomposite resistance was -1000ppm/°C. The gas response of the nanocomposite was about 10% resistance increase under pure CO 2 . The sensor frequency change was around 300ppm for pure CO 2 . With paralyne packaging, the sensor frequency change from relative humidity of 0% to 100% at room temperature decreased from over 1000ppm to less than 100ppm. The lowest detection limit of the sensor is 1% gas concentration, with 36ppm frequency change. Wireless module was tested and showed over one foot transmission distance at preferred parallel orientation.
As part of the Midwest Regional Carbon Sequestration Partnership (MRCSP) Phase III project, a monitoring study was conducted to assess the effectiveness of DAS (Distributed Acoustic Sensing) -based VSP (Vertical Seismic Profiling) technology for delineating CO 2 injected into the Silurian-age pinnacle reefs in northern Michigan, the host rocks for the MRCSP Phase III demonstration project. The DAS VSP study was conducted in the Chester 16 reef, one of several reefs in Otsego County Michigan that is operated by Core Energy, LLC, of Traverse City, Michigan.
The vision of this project was to develop an integrated system for autonomous underwater vehicle (AUV) monitoring of offshore kelp farms using acoustic, environmental, and optical sensors. This project supports the overall MARINER goals of developing an offshore kelp aquaculture industry to produce low-carbon or carbon-neutral biofuels. The project commenced in the spring of 2018 and used laboratory experiments to test the efficacy of acoustic sensors for monitoring kelp farm lines and growing kelp biomass. Sensors were then integrated onto two AUVs as well as an autonomous surface vehicle in order to establish the optimal type, price point, and vehicle to most efficiently monitor kelp farm structures, kelp biomass, and the surrounding environment. Multiple field deployments of these vehicles and sensors in Massachusetts, New Hampshire, and Maine confirmed that farm lines and kelp could be visualized and that monitoring the spatial patterns of environmental variables was possible. The COVID-19 pandemic severely limited fieldwork activities and laboratory testing, with deployments around kelp farms not occurring again until January 2021. Time spent away from the field focused on data visualization and the development of a low-cost, vessel-based sensor system. Unfortunately, the low-cost system experienced a disk failure during its first deployment and due to multiple resignations from the project team further engineering and development was not possible. Additionally, final results from acoustic sensor testing in 2021 were also not able to be completed due to the resignation of the postdoc leading the analysis. Despite these setbacks, multiple avenues for further development of optical imagery processing from the 360-degree Kelpcam camera and testing of the low-cost sensor system may be possible.
Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on margins of safety in existing codes. Research is required to deploy online monitoring capability to assess the health of concrete structures in nuclear power plants and perform predictive analytics based on heterogeneous measurements, in order to reduce the operation and maintenance costs. The research effort described in this report focuses on the health monitoring of concrete slabs containing reactive aggregates using the vibro-acoustic modulation (VAM) technique and predictive modeling. The research is developing an approach to enable detection, localization, and estimation of the extent of degradation in concrete slabs due to alkali-silica reaction (ASR). The project outcomes are generic and extendable to other degradation modes in concrete. A concrete slab without reinforcements was cast at Vanderbilt University and cured in aggressive conditions to accelerate ASR degradation. In this report, we develop a methodology for the automation of VAM testing, and the construction of machine learning models to facilitate damage localization in concrete structures. We investigate how machine learning models based on physics simulation data can be effectively utilized for damage localization (damage location and depth) and estimation in a concrete slab specimen. Our study indicates that these models could potentially support damage localization and estimation for NPP structures.
DAS records a variety of signals, including (1) earthquakes and volcanic eruptions, (2) explosions (DAG, mining, etc.), (3) acoustic waves, (4) ocean (waves, whales), (5) vehicle, ship and pedestrian traffic, (6) glaciology and landslides, and (7) oil and gas. Main questions include: (1) what is the extent of the signal content? (2) how does DAS compare to traditional sensors? (3) how do interrogators, fiber types, and fiber depth burials impact measurements? (4) special applications offshore to overcome the lack of instrumentation.
This report documents the technical accomplishments of the project, “Acoustic Emission- Based Health Monitoring of Space Launch System Structures,” sponsored by the National Aeronautics and Space Administration (Award No. NNM13AA12G). As the project title suggests, the goal of the project was to develop a structural health monitoring (SHM) system for Space Launch System (SLS) vehicles based on acoustic emission (AE) or AE-like signals. Such a system will enhance SLS reliability by identifying the damage locations and type of damage when the damage is initiated. This SHM system would also lead to reduced maintenance costs by enabling ground support equipment to inspect only SLS elements or parts that are likely to be damaged. Finally, it will facilitate lean designs that meet tolerance levels specified by barely detectable damage. By avoiding excess conservatism in this manner, this SHM system will further reduce manufacturing costs of SLS vehicles.
The projects objectives and purpose are to: (1) development a multipurpose acoustic sensor for downhole fluid monitoring in Enhanced Geothermal Systems (EGS) reservoirs over typical ranges of pressures and temperatures and demonstrate its capabilities and performance for different EGS systems; (2) determine in real-time and in a single sensor package several parameters - temperature, pressure, fluid flow and fluid properties; (3) needed in nearly every phase of an EGS project, including Testing of Injection and Production Wells, Reservoir Validation, Inter-well Connectivity, Reservoir Scale Up and Reservoir Sustainability. (4) Current sensors are limited to operating at lower temperatures, but the need is for logging at high temperatures. The present project deals with the development of a novel acoustic-based sensor that can work at temperatures up to 374 °C, in inhospitable environments.
Fatigue experiments were performed at room temperature for C-fiber reinforced chemical vapor infiltrated (CVI Sic) matrix and melt-infiltrated (MI) matrix composites. The goal was to associate some nondestructive parameter or acoustic emission characteristic with the processes that lead to fatigue failure. Failure only occurred at loads very close to the ultimate. However, correlations between the acoustic data and the eventual failure of the composites could be made. These will be presented with respect to health monitoring of these types of composites.