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Dashboard for Marine Energy Site Assessment and Monitoring

The marine energy (ME) industry presently relies upon fragmented site assessment solutions that require high resource expenditure for deployment at each site and do not leverage the wealth of readily available tools and information. A wave energy resource assessment dashboard, currently in development, will substantially improve siting, permitting, operations, and maintenance of ME projects by providing an integrated solution that is a one-stop-shop for a developer’s needs. The Site Energy Assessment and MOnitoring Dashboard (SEAMOD) will be of commercial interest to anyone seeking to deploy an ME project and is easily expandable to include tidal and wind energy site assessments. The integrated dashboard is being developed using state-of-the-art database and cloud computing methods and data-assimilative modeling tools that can be coupled with low-cost, rapidly deployable wave buoys and environmental sensing hardware. The combined software and hardware dashboard will reduce wave energy site characterization and wave climate monitoring costs by more than 60 percent and provide assessments that meet international industry standards. To realize a thriving global ME industry, the physical environment at a potential deployment site must be understood, not only for resource characterization, but also for optimization of device and power conversion performance. SEAMOD directly addresses these needs with a commercially marketable product. SEAMOD is a low-cost solution that provides comprehensive ME resource assessments, baseline environmental monitoring, and offshore characterizations required for successful ME development. The key technical objectives for Phase I were a series of software development goals, which when implemented with monitoring solutions, produced an initial proof-of-concept low-cost wave energy resources dashboard. In Phase II, the development of the prototype SEAMOD continued. The basic framework employed was the development of a revised dashboard and monitoring tool customized for ME applications by focusing on IEC site assessment and method requirements. Development was focused on the integration of full hindcast metocean products to provide hindcast resource characterization and environmental information. The final integrated dashboard provides a low-cost solution that delivers comprehensive, scalable, industry-standard energy resource assessments and offshore characterizations required for successful ME development. The integrated dashboard offers visibility of the most recent site modeling, measurements, and historical data. The application and integration of consensus-based standards for wave energy resource assessment, as determined by the International Electrotechnical Commission (IEC), are crucial for the impact and value of SEAMOD. SEAMOD includes monthly, seasonal, and yearly statistics, as well as the total 30-year record, offering temporal resolution of the IEC parameters to aid potential developers in determining the available wave energy resources in their area of interest.

16 TIDAL AND WAVE POWER↗

The effect of monitoring complexity on stakeholder acceptance of CO2 geological storage projects in the US gulf coast region

Environmental monitoring at geologic CO 2 storage sites is required by regulations for the purposes of environmental protection and emissions accounting in the case of leakage to surface. However, another very important goal of environmental monitoring is to assure stakeholders that the project is monitored for safety and effectiveness. With current efforts to optimize monitoring for cost-effectiveness, the question remains: will optimization of monitoring approaches degrade stakeholder assurance, or do heavily-instrumented sites communicate higher risk to a stakeholder? We report the results of a stakeholder survey in Gulf Coast states of the US where carbon capture and storage (CCS) is developing quickly. We rely on a 2 by 2 factorial experiment in which we manipulate message complexity (complex v. simple) and social norm (support from scientists v. support from community members). Subjects were randomly assigned to one of four conditions: 1) complex message with scientist support; 2) complex message with community member support; 3) simple message with scientist support; or 4) simple message with community member support. In addition to the experimental stimuli, subjects were also asked about their need for cognition, attitudes toward science and scientists, attitudes about climate change and support for carbon capture and storage (CCS). Our sample is drawn from residents in states bordering the western Gulf of Mexico (Texas, Louisiana, Florida) where CO 2 geologic storage is being planned both onshore and offshore. The results offer important implications for public outreach efforts to key stakeholders.

54 ENVIRONMENTAL SCIENCES↗

Operational-Condition-Independent Criteria Dedicated to Monitoring Wind Turbine Generators: Preprint

To date the existing wind turbine condition monitoring technologies and commercially available systems have not been fully accepted for improving wind turbine availability and reducing their operation and maintenance costs. One of the main reasons is that wind turbines are subject to constantly varying loads and operate at variable rotational speeds. As a consequence, the influences of turbinefaults and the effects of varying load and speed are coupled together in wind turbine condition monitoring signals. So, there is an urgent need to either introduce some operational condition de-coupling procedures into the current wind turbine condition monitoring techniques or develop a new operational condition independent wind turbine condition monitoring technique to maintain high turbineavailability and achieve the expected economic benefits from wind. The purpose of this paper is to develop such a technique. In the paper, three operational condition independent criteria are developed dedicated for monitoring the operation and health condition of wind turbine generators. All proposed criteria have been tested through both simulated and practical experiments. The experimentshave shown that these criteria provide a solution for detecting both mechanical and electrical faults occurring in wind turbine generators.

17 WIND ENERGY↗

Integrated Systems-Based Approach to Monitoring Environmental Remediation

The US Department of Energy (DOE) is responsible for risk reduction and cleanup of its nuclear weapons complex. Remediation strategies for some of the existing contamination use techniques that mitigate risk, but leave contaminants in place. Monitoring to verify remedy performance and long-term mitigation of risk is a key element for implementing these strategies and can be a large portion of the total cost of remedy implementation. Especially in these situations, there is a need for innovative monitoring approaches that move away from the cost and labor intensive point-source monitoring. A systems-based approach to monitoring design focuses monitoring on controlling features and processes to enable effective interpretation of remedy performance.

environmental remediation↗

ROBUST ONLINE MONITORING FOR CALIBRATION ASSESSMENT OF TRANSMITTERS AND INSTRUMENTATION

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. Specifically, the next generation of OLM technology is expected to include newly developed advanced algorithms that improve monitoring of sensor/system performance and enable the use of plant data to derive information that currently cannot be measured. These advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this paper, we discuss an overview of research being performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. Algorithm development is focused on the following OLM functions: • Signal validation – fault detection and selection of acceptance criteria • Virtual sensing – signal value prediction and acceptance criteria • Response-time assessment – fault detection and acceptance criteria selection A GP-based uncertainty quantification (UQ) method previously developed for UQ in OLM, was adapted for use in sensor-fault detection and virtual sensing. For signal validation, the various components to the OLM residual (which is computed using an AAKR model) were explicitly defined and modeled using a GP. Evaluation was conducted using flow loop data from multiple sources. Results using experimental data from laboratory-scale flow loops indicate that the approach, while capable of detecting sensor drift, may be incapable of discriminating between sensor drift and model inadequacy. This may be due to a simplification applied in the initial modeling, where the sensor degradation is assumed to be stationary. In the case of virtual sensors, the GP model was used in a predictive mode to estimate the correct sensor reading for sensors that may have failed. Results have indicated the viability of using this approach for virtual sensing. However, the GP model has proven to be computationally expensive, and so alternative algorithms for virtual sensing are being evaluated. Finally, automated approaches to performing noise analysis for extracting sensor response time were developed. Evaluation of this technique using laboratory-scale data indicates that it compares well with manual techniques previously used for noise analysis. Moreover, the automated and manual approaches for noise analysis also compare well with the current “gold standard”, hydraulic ramp testing, for response time monitoring. Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants.

calibration interval extension↗

Evaluations of Silicon Carbide Temperature Monitors

The effect of irradiation on materials properties is an important field of study for materials usage in both fission and fusion systems for energy production. Neutron flux and energy spectrums are well understood; however, the irradiation temperature can be more difficult to determine. Since the early 1960s, Silicon Carbide (SiC) has been used as a passive post-irradiation temperature monitor because the irradiation defects anneal out above the irradiation temperature. Irradiation temperature is determined by measuring a property change after isochronal annealing or during a continuously monitored annealing process. There are many properties that may be measured including electrical resistivity, bulk density, dimensions, thermal diffusivity, or lattice spacing. Electrical resistivity is accepted as a robust measurement technique; however, such method is time-consuming since the steps involved must be performed in a serial manner. The use of thermal expansion from continuous dilatometry is an automated process requiring minimal setup time. As part of a Nuclear Science User Facilities (NSUF) project, low dose silicon carbide monitors were irradiated in the BR2 material test reactor at SCK, Belgium, and were then evaluated at the Idaho National Laboratory (INL) High Temperature Test Laboratory (HTTL) to determine their peak temperature achieved during irradiation. The technical significance of this work was that the monitors were irradiated to a dose that was significantly less than recommended in published literature. This paper will discuss the evaluation processes available at HTTL and the performance of the low dose silicon carbide temperature monitors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance of a GM tube based environmental dose rate monitor operating in the Time-To-Count mode

The events at the Fukushima Daiichi power plant in the aftermath of a natural disaster underline the importance of a large array of networked environmental monitors to cover areas around nuclear power plants. These monitors should meet a few basic criteria: have a uniform response over a wide range of gamma energies, have a uniform response over a wide range of incident angles, and have a large dynamic range. Many of these criteria are met if the probe is qualified to the international standard IEC 60532 (Radiation protection instrumentation - Installed dose rate meters, warning assemblies and monitors - X and gamma radiation of energy between 50 keV and 7 MeV), which specifically deals with energy response, angle of incidence, dynamic range, response time, and a number of environmental characteristics. EcoGamma is a dual GM tube environmental gamma radiation monitor designed specifically to meet the requirements of IEC 60532 and operate in the most extreme conditions. EcoGamma utilizes two energy compensated GM tubes operating with a Time-To-Count (TTC) collection algorithm. The TTC algorithm extends the lifetime and range of a GM tube significantly and allows the dual GM tube probe to achieve linearity over approximately 10 decades of gamma dose rate (from the Sv/hr range to 100 Sv/hr). In the TTC mode of operation, the GM tube is not maintained in a biased condition continuously. This is different from a traditional counting system where the GM tube is held at a constant bias continuously and the total number of strikes that the tube registers are counted. The traditional approach allows for good sensitivity, but does not lend itself to a long lifetime of the tube and is susceptible to linearity issues at high count rates. TTC on the other hand only biases the tube for short periods of time and in effect measures the time between events, which is statistically representative of the total strike rate. Since the tube is not continually biased, the life of the tube is extended and the linearity is greatly improved. Testing has been performed at Pacific Northwest National Laboratory (PNNL) in the USA and confirms compliance to IEC 60532 as well as linearity (± 10%) up to 100 Sv/hr. Furthermore, a network of EcoGamma probes may be linked through available supervisory software to provide a dose rate map of an area. This allows for real time monitoring of dose rates from one (or multiple) remote locations. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Progress in the development of the neutron flux monitoring system of the French GEN-IV SFR: simulations and experimental validations [ANIMMA--2015-IO-392]

France has a long experience of about 50 years in designing, building and operating sodium-cooled fast reactors (SFR) such as RAPSODIE, PHENIX and SUPER PHENIX. Fast reactors feature the double capability of reducing nuclear waste and saving nuclear energy resources by burning actinides. Since this reactor type is one of those selected by the Generation IV International Forum, the French government asked, in the year 2006, CEA, namely the French Alternative Energies and Atomic Energy Commission, to lead the development of an innovative GEN-IV nuclear- fission power demonstrator. The major objective is to improve the safety and availability of an SFR. The neutron flux monitoring (NFM) system of any reactor must, in any situation, permit both reactivity control and power level monitoring from startup to full power. It also has to monitor possible changes in neutron flux distribution within the core region in order to prevent any local melting accident. The neutron detectors will have to be installed inside the reactor vessel because locations outside the vessel will suffer from severe disadvantages; radially the neutron shield that is also contained in the reactor vessel will cause unacceptable losses in neutron flux; below the core the presence of a core-catcher prevents from inserting neutron guides; and above the core the distance is too large to obtain decent neutron signals outside the vessel. Another important point is to limit the number of detectors placed in the vessel in order to alleviate their installation into the vessel. In this paper, we show that the architecture of the NFM system will rely on high-temperature fission chambers (HTFC) featuring wide-range flux monitoring capability. The definition of such a system is presented and the justifications of technological options are brought with the use of simulation and experimental results. Firstly, neutron-transport calculations allow us to propose two in-vessel regions, namely the above-core and under-core structures. We verify that they comply with the main objective, that is the neutron power and flux distribution monitoring. HTFC placed in these two regions can detect an inadvertent control rod withdrawal that is a postulated initiating event for safety demonstration. Secondly, we show that the HTFC reliability is enhanced thanks to a more robust physical design and the fact that it has been justified that the mineral insulation is insensitive to any increase in temperature. Indeed, the HTFC insulation is subject to partial discharges at high temperature when the electric field between their electrodes is greater than about 200 V/mm or so. These discharges give rise to signals similar to the neutron pulses generated by a fission chamber itself, which may bias the HTFC count rate at start-up only. However, as displayed in Figure 1, we have experimentally verified that one can discriminate neutron pulses from partial discharges using online estimation of pulse width. Thirdly, we propose to estimate the count rate of a HTFC using the third order cumulant of its signal that is described by a filtered Poisson process. For such a statistic process, it is known that any cumulant, also called cumulative moment, is proportional to the process intensity that is here the count rate of a fission chamber. One recalls that the so-called Campbelling mode of such a detector is actually based on the signal variance, which is the second-order cumulant as well. The use of this extended Campbelling mode based on the third-order cumulant will permit to ensure the HTFC response linearity over the entire neutron flux range using a signal processing technique that is simple enough to satisfy design constraints on electric devices important for nuclear safety. We also show that this technique, named high order Campbelling method (HOC), is significantly more robust than another technique based on the change in the HTFC filling gas, which consists in adding a few percent of nitrogen. Finally, we also present an experimental campaign devoted to the required calibration process of the so-called HOC method. The Campbelling results show a good agreement with the simple pulse counting estimation at low count rates. It is also shown that the HOC technique provides a linear estimation of the count rates at higher power levels as well.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Monitoring Carbon Storage Sites with Time-Lapse Gravity Surveys

Monitoring technologies are deployed on carbon storage sites to demonstrate that the injected CO2 is contained within the storage complex during and long after the active life of the project and that the CO2 behavior is conforming to expectations. Detection of gravity variations accompanying mass redistributions in the subsurface caused by fluid movements in reservoirs provides a unique means for monitoring the dynamics of a carbon sequestration site. Time-lapse gravity surveys have a long history of effectively monitoring temporal density changes in the subsurface. However, monitoring of carbon storage sites with time-lapse gravity surveys using surface or borehole measurements remains limited, although it gained more attention during the last decade. With the recent progresses in instrument capabilities, and the increased number of fluid storage sites (e.g., wastewater, CO2, natural gas, etc.), the gravity method (with its unique ability to remotely estimate both the mass of an injected fluid and its location) has a promising future in monitoring. This chapter provides background information regarding the gravity method and discusses its modeling and application to various carbon storage sites.

Carbon Sequestration, time-lapse gravity, monitori↗

Substrate-Coated Illumination Droplet Spray Ionization: Real-Time Monitoring of Photocatalytic Reactions

Real-time monitoring of photocatalytic reactions facilitates the elucidation of the mechanisms of the reactions. However, suitable tools for real-time monitoring are lacking. Herein, a novel method based on droplet spray ionization named substrate-coated illumination droplet spray ionization (SCI-DSI) for direct analysis of photocatalytic reaction solution is reported. SCI-DSI addresses many of the analytical limitations of electrospray ionization (ESI) for analysis of photocatalytic-reaction intermediates, and has potential for both in situ analysis and real-time monitoring of photocatalytic reactions. In SCI-DSI-mass spectrometry (MS), a photocatalytic reaction occurs by loading sample solutions onto the substrate-coated cover slip and by applying UV light above the modified slip; one corner of this slip adjacent to the inlet of a mass spectrometer is the high-electric-field location for launching a charged-droplet spray. After both testing and optimizing the performance of SCI-DSI, the value of this method for in situ analysis and real-time monitoring of photocatalytic reactions was demonstrated by the removal of cyclophosphamide (CP) in TiO{sub 2}/UV. Reaction times ranged from seconds to minutes, and the proposed reaction intermediates were captured and identified by tandem mass spectrometry. Moreover, the free hydroxyl radical (·OH) was identified as the main radicals for CP removal. These results show that SCI-DSI is suitable for in situ analysis and real-time monitoring of CP removal under TiO{sub 2}-based photocatalytic reactions. SCI-DSI is also a potential tool for in situ analysis and real-time assessment of the roles of radicals during CP removal under TiO{sub 2}-based photocatalytic reactions.Graphical Abstract .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Detecting keyhole porosity and monitoring process signatures in additive manufacturing: an in situ pyrometry and ex situ X-ray radiography correlation

Creation of pores and defects during laser powder bed fusion (LPBF) can lead to poor mechanical properties and thus must be minimized. Post-build inspection is required to ensure the printed parts contain acceptably low defect concentrations. These inspections are time consuming and costly, especially for large or complex parts. As a potential solution, in situ process monitoring can be used to detect the creation of defects, characterize local material behavior and predict expected component properties. However, the precise relationship between pore creation and in situ process monitoring still needs to be understood. In this work, high-speed infrared diode-based pyrometry and high-speed optical imaging signals were used to monitor LPBF printing of 446 stainless steel 316 L single tracks with varying laser power and velocity. Results indicate an increase in pyrometer signal and melt pool dimensions with increasing laser power and decreasing velocity in agreement with previous work. In addition, careful analysis of pyrometer signal reveals a distinct signature of the conduction-to-keyhole mode transition which was confirmed by metallography. Critically, pore defect initiation as characterized by ex situ X-ray radiography was correlated with in situ thermal monitoring signals to derive the probability of defect creation. Our results show that, in principle, a probabilistic prediction of pore formation can be achieved based on in situ high-speed pyrometry monitoring of the LPBF melt pool.

36 MATERIALS SCIENCE↗

Registration and fusion of large-scale melt pool temperature and morphology monitoring data demonstrated for surface topography prediction in LPBF

In-situ monitoring technologies for laser powder bed fusion (LPBF) additive manufacturing often face one key challenge, extracting the ultrafast melt pool (MP) signatures for understanding the localized part properties. Further, the spatial information of each monitored MP signature is essential for correlating the MP – part property. This spatial information is often unavailable especially from commercial LPBF printers. Many MP monitoring methods have been reported and utilized. However, very few of these have the MP’s spatial information. To overcome this challenge, in this work we report a method for spatially registering the key MP signatures (MP intensity, temperature, and area) to the monitored print parts. The MP signatures are obtained from our coaxial high-speed single-camera based two-wavelength imaging pyrometry (STWIP) system and the MP spatial information is obtained from an off-axis camera system. A machine learning aided image analysis method is employed to retrieve the spatial distribution of MPs within the corresponding part’s coordinates system. Then, the MP signature maps (MPSMs) are reconstructed by mapping the STWIP measured MP signatures to the registered MP coordinates. Further, a long short-term memory (LSTM) neural network is developed for estimating the layer surface topography from the registered MPSMs. The obtained results indicate that the layer surface topography can be more accurately estimated by using MP temperature signature rather than MP intensity and/or area signatures as in common practice. Finally, our developed methods for MP monitoring, registration, and MP-surface topography prediction offer advanced capabilities for the online detection of process anomalies and part defects.

36 MATERIALS SCIENCE↗

Contribution of citizen science towards international biodiversity monitoring

To meet collective obligations towards biodiversity conservation and monitoring, it is essential that the world's governments and non-governmental organisations as well as the research community tap all possible sources of data and information, including new, fast-growing sources such as citizen science (CS), in which volunteers participate in some or all aspects of environmental assessments. Through compilation of a database on CS and community-based monitoring (CBM, a subset of CS) programs, we assess where contributions from CS and CBM are significant and where opportunities for growth exist. We use the Essential Biodiversity Variable framework to describe the range of biodiversity data needed to track progress towards global biodiversity targets, and we assess strengths and gaps in geographical and taxonomic coverage. Our results show that existing CS and CBM data particularly provide large-scale data on species distribution and population abundance, species traits such as phenology, and ecosystem function variables such as primary and secondary productivity. Only birds, Lepidoptera and plants are monitored at scale. Most CS schemes are found in Europe, North America, South Africa, India, and Australia. We then explore what can be learned from successful CS/CBM programs that would facilitate the scaling up of current efforts, how existing strengths in data coverage can be better exploited, and the strategies that could maximise the synergies between CS/CBM and other approaches for monitoring biodiversity, in particular from remote sensing. More and better targeted funding will be needed, if CS/CBM programs are to contribute further to international biodiversity monitoring.

59 BASIC BIOLOGICAL SCIENCES↗

Design Support of an Above Cap-rock Early Detection Monitoring System using Simulated Leakage Scenarios at the FutureGen2.0 Site

The FutureGen 2.0 Project will design and build a first-of-its-kind, near-zero emissions coal-fueled power plant with carbon capture and storage (CCS). To assess storage site performance and meet the regulatory requirements of the Class VI Underground Injection Control (UIC) Program for CO 2 Geologic Sequestration, the FutureGen 2.0 project will implement a suite of monitoring technologies designed to evaluate CO 2 mass balance and detect any unforeseen loss in CO 2 containment. The monitoring program will include direct monitoring of the reservoir, and early-leak-detection monitoring directly above the primary confining zone. This preliminary modeling study described here focuses on hypothetical leakage scenarios into the first permeable unit above the primary confining zone (Ironton Sandstone) and is used to support assessment of early-leak detection capabilities. Future updates of the model will be used to assess potential impacts on the lowermost underground source of drinking water (Saint Peter Sandstone) for a range of theoretical leakage scenarios. This preliminary modeling evaluation considers both pressure response and geochemical signals in the overlying Ironton Sandstone. This model is independent of the FutureGen 2.0 reservoir model in that it does not simulate caprock discontinuities, faults, or failure scenarios. Instead this modeling effort is based on theoretical, volumetric-rate based leakage scenarios. The scenarios include leakage of 1% of the total injected CO 2 mass, but spread out over different time periods (20, 100, and 500 years) with each case yielding a different mass flux (i.e., smaller mass fluxes for longer duration leakage cases]. A brine leakage scenario using a volumetric leakage similar to the 20 year 1% CO 2 case was also considered. A framework for the comparison of the various cases was developed based on the exceedance of selected pressure and geochemical thresholds at different distances from the point of leakage and at different vertical positions within the Ironton Sandstone. These preliminary results, and results from an updated models that incorporate additional site-specific characterization data, support development/refinement of the monitoring system design.

54 ENVIRONMENTAL SCIENCES↗

Building complex event processing capability for intelligent environmental monitoring

Rapid evolution of Internet-of-Things is driving the increased deployment of smart sensors in environmental applications, contributing to many big data characteristics of environmental monitoring. Most of the current environmental monitoring systems are not designed to handle real-time datastreams, and the best practices for datastream processing and predictive analytics are yet to be established. This work presents a complex event processing (CEP) engine for detecting anomalies in real time, and demonstrates it using a series of real monitoring data from the geological carbon sequestration domain. We show that the service-based CEP engine is instrumental for enabling environmental intelligent monitoring systems to ingest heterogeneous datastreams with scalable performance. Our CEP framework requires minimal coding from the user and can be easily extended to other similar environmental monitoring applications.

54 ENVIRONMENTAL SCIENCES↗

Modeling of time-lapse seismic monitoring using CO 2 leakage simulations for a model CO 2 storage site with realistic geology: Application in assessment of early leak-detection capabilities

Time-lapse surface seismic surveys have been widely used at carbon sequestration sites for site characterization, monitoring subsurface CO 2 plume migration, and detecting potential CO 2 leakage from a storage reservoir. Monitoring in the first permeable unit directly above the primary seal is important for early detection of CO 2 leakage. Forward modeling of time-lapse seismic data can be used to assess the utility of the seismic method for CO 2 leakage detection. We develop a workflow for forward modeling of time-lapse seismic data, including constructing seismic velocity models using flow simulation outputs, modeling of pre-stack and post-stack synthetic seismic data following seismic data processing sequence and analysis of processed synthetic time-lapse seismic data. We apply the forward modeling and analysis workflow to assessing the detectability and the earliest detection time of seismic monitoring using the hypothetical CO 2 leakage scenarios for a model geologic storage site with realistic geology. We then derive the detection thresholds using the simulated normalized root-mean-square (NRMS) differences for the no-leakage case at a range of signal-to-noise ratios, representing the background noise levels in seismic data. We then compare NRMS differences triggered by the CO 2 leakage to the detection thresholds at each time step to quantify the detectability and the earliest detection time of seismic monitoring. We analyze the effects of the acquisition parameters and elastic parameters on the produced synthetic seismic data and earliest detection time. Our modeling results indicate that high signal-to-noise ratio is needed to detect the CO 2 leakage at the model site. Minimizing the background noise in seismic data is crucial for improving the detectability of the seismic method. Increasing the shot density or increasing the dominant frequency of the source wavelet is likely to increase the possibility of the leakage detection and reduce the time needed for the detection. The elastic parameters used in the rock physics modeling have significant effects on the resultant seismic velocity models and synthetic seismic data, highlighting their critical roles in understanding and interpreting time-lapse seismic reflection data associated with CO 2 monitoring, verification and accounting activities.

58 GEOSCIENCES↗

Risk-based monitoring designs for detecting CO 2 leakage through abandoned wellbores: An application of NRAP’s WLAT and DREAM tools

We report that one suggested approach to managing the risk of geologic CO 2 storage projects is to perform risk-based subsurface monitoring targeting early leak detection. The challenge in risk-based monitoring is that leakage impacts are expected to be small in comparison with the footprint of the stored CO 2 plume and could be at depths ranging from the depth of storage (often ~1 km bgs) up to surficial aquifers. Addressing this challenge requires a multidisciplinary effort capable of characterizing potential subsurface leakage in terms of likelihood, location, magnitude, impacts to overlying aquifers, and uncertainty as well as innovative monitoring technology design and implementation. The National Risk Assessment Partnership (NRAP) was established to develop related risk assessment tools to provide guidance on such assessments. Here we demonstrate the application workflow of two of the NRAP computational tools, WLAT (Wellbore Leakage Analysis Tool) and DREAM (Designs for Risk Evaluation and Management), to a hypothetical CO 2 storage site based on a study area in the Midwestern United States. This workflow shows how CO 2 leakage may be estimated, evaluated, and monitored in terms of risk. Results provide guidance on monitoring configurations and technologies which minimize the time to leak detection, maximize the probability detection, and provide cost considerations.

54 ENVIRONMENTAL SCIENCES↗

Optimal design of microseismic monitoring network: Synthetic study for the Kimberlina CO2 storage demonstration site

Microseismic monitoring can play a crucial role to ensure safe long-term geological carbon storage. For reliable long-term monitoring for CO2-injection-induced microseismic events, a surface seismic array is desirable in addition to borehole geophone sensors. Optimal design of surface seismic network is of great interest to achieve cost-effective monitoring. We develop a methodology to determine the optimal number of surface seismic stations with a geometrically satisfactory distribution for given monitoring regions. We design an optimal microseismic monitoring network based on widely-accepted guiding principles, and the relationship between the location accuracy of microseismic events and the total number of seismic stations. We determine the optimal number of seismic stations based on the trade-off curve of the event location accuracy vs. the total number of seismic stations. We apply our optimal design method to the Kimberlina carbon storage site in California. We use a synthetic Kimberlina model to show that approximately 20 surface seismic stations with a geometrically satisfactory distribution are preferred for the best trade-off between the cost and the event location accuracy.

58 GEOSCIENCES↗