Synthesis of global satellite observations of magmatic and volcanic deformation: implications for volcano monitoring & the lateral extent of magmatic domains

Global Synthetic Aperture Radar (SAR) measurements made over the past decades provide insights into the lateral extent of magmatic domains, and capture volcanic process on scales useful for volcano monitoring. Satellite-based SAR imagery has great potential for monitoring topographic change, the distribution of eruptive products and surface displacements (InSAR) at subaerial volcanoes. However, there are challenges in applying it routinely, as would be required for the reliable operational assessment of hazard. The deformation detectable depends upon satellite repeat time and swath widths, relative to the spatial and temporal scales of volcanological processes. We describe the characteristics of InSAR-measured volcano deformation over the past two decades, highlighting both the technique’s capabilities and its limitations as a monitoring tool. To achieve this, we draw on two global datasets of volcano deformation: the Smithsonian Institution Volcanoes of the World database and the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics volcano deformation catalogue, as well as compiling some measurement characteristics and interpretations from the primary literature. We find that a higher proportion of InSAR observations capture non-eruptive and non-magmatic processes than those from ground-based instrument networks, and that both transient ( 5 years) deformation episodes are under-represented. However, satellite radar is already used to assess the development of extended periods of unrest and long-lasting eruptions, and improved spatial resolution and coverage have resulted in the detection of previously unrecognised deformation at both ends of the spatial scale (~ 10 to > 1000 km²). ‘Baseline’ records of past InSAR measurements, including ‘null’ results, are fundamental for any future interpretation of interferograms in terms of hazard‚ both by providing information about past deformation at an individual volcano, and for assessing the characteristics of deformation that are likely to be detectable (and undetectable) using InSAR. More than half of all InSAR deformation signals attributed to magmatic processes have sources in the shallow crust (< 5 km depth). While the depth distribution of InSAR-derived deformation sources is affected by measurement limitations, their lateral distribution provides information about the extent of active magmatic domains. Deformation is common (24% of all potentially magmatic events) at loci ≥5 km away from the nearest active volcanic vent. This demonstrates that laterally extensive active magmatic domains are not exceptional, but can comprise the shallowest part of trans-crustal magmatic systems in a range of volcanic settings

Synthesizing multi-sensor, multi-satellite, multi-decadal datasets for global volcano monitoring

Owing to practical limitations less than half of Earth's 1400 subaerial volcanoes have no ground monitoring and few are monitored consistently. Earth-observing satellite missions provide global and frequent measurements of volcanic activity that are closing these gaps in coverage. We compare databases of global, satellite-detections of ground deformation (1992–2016), SO₂ emissions (1978–2016), and thermal features (2000–2016) that together include 306 volcanoes. Each database has limitations in terms of spatial and temporal resolution but each technique contributed 45–86 unique detections of activity that were not detected by other techniques. Integration of these three databases shows that satellites detected ~10² volcanic activities per year before the year 2000 and ~103 activities per year after the year 2000. We find that most of the 54 erupting volcanoes without satellite-detections are associated with low volcano explosivity index eruptions and note that many of these eruptions (71%, 97/135) occurred in the earliest decades of remote sensing (pre-2000) when detection thresholds were high. From 1978 to 2016 we conduct a preliminary analysis of the timing between the onset of satellite-detections of deformation (N = 154 episodes, N = 71 volcanoes), thermal features (N = 16,544 episodes, N = 99 volcanoes), and SO₂ emissions (N = 1495 episodes, N = 116 volcanoes) to eruption start dates. We analyze these data in two ways: first, including all satellite-detected volcanic activities associated with an eruption; and second, by considering only the first satellite-detected activity related to eruption. In both scenarios, we find that deformation is dominantly pre-eruptive (47% and 57%) whereas available databases of thermal features and SO₂ emissions utilizing mainly low-resolution sensors are dominantly co-eruptive (88% and 76% for thermal features, 97% and 96% for SO₂ emissions)

Limitations in qualitative and quantitative analysis of time-lapse data due to fluid flow uncertainties

We address some limitations in qualitative and quantitative analysis of time-lapse data due to underlying uncertainties in the flow of reservoir fluids. We explore how seismic signals may evolve over time by developing synthetic time-lapse data based on a variety of flow scenarios including radial flow, multi-phase flow and flows with unstable mobility ratios. Model predictions of water saturation and effective stress are used to construct synthetic impedance profiles. Using an idealized model of water-flood type production we show that qualitative analysis can be limited by the signal complexities resulting from flows in which both water saturation and effective stress change gradually, such as may occur when the injected water and the displaced oil are not separated by a sharp interface. A two-layer reservoir flow model is developed with which the limitations of quantitative analysis are explored. If a quantitative inversion technique is error free the resolution limits and signal noise in the seismic data allow only spatially averaged reservoir properties to be known. In some reservoirs undergoing water flood, volumetrically significant movement of the injected water may occur on length scales below that of the resolution and noise threshold the seismic data allows. In such a reservoir the inversion technique gives good quality information about the average location of the injected water but does not provide information about how all the injected water is moving. Specifically the possibility of thin high permeability layering carrying a significant fraction of the injected water cannot be eliminated. We show that this can introduce great uncertainty in estimates of reservoir performanceWe address some limitations in qualitative and quantitative analysis of time-lapse data due to underlying uncertainties in the flow of reservoir fluids. We explore how seismic signals may evolve over time by developing synthetic time-lapse data based on a variety of flow scenarios including radial flow, multi-phase flow and flows with unstable mobility ratios. Model predictions of water saturation and effective stress are used to construct synthetic impedance profiles. Using an idealized model of water-flood type production we show that qualitative analysis can be limited by the signal complexities resulting from flows in which both water saturation and effective stress change gradually, such as may occur when the injected water and the displaced oil are not separated by a sharp interface. A two-layer reservoir flow model is developed with which the limitations of quantitative analysis are explored. If a quantitative inversion technique is error free the resolution limits and signal noise in the seismic data allow only spatially averaged reservoir properties to be known. In some reservoirs undergoing water flood, volumetrically significant movement of the injected water may occur on length scales below that of the resolution and noise threshold the seismic data allows. In such a reservoir the inversion technique gives good quality information about the average location of the injected water but does not provide information about how all the injected water is moving. Specifically the possibility of thin high permeability layering carrying a significant fraction of the injected water cannot be eliminated. We show that this can introduce great uncertainty in estimates of reservoir performanceWe address some limitations in qualitative and quantitative analysis of time-lapse data due to underlying uncertainties in the flow of reservoir fluids. We explore how seismic signals may evolve over time by developing synthetic time-lapse data based on a variety of flow scenarios including radial flow, multi-phase flow and flows with unstable mobility ratios. Model predictions of water saturation and effective stress are used to construct synthetic impedance profiles. Using an idealized model of water-flood type production we show that qualitative analysis can be limited by the signal complexities resulting from flows in which both water saturation and effective stress change gradually, such as may occur when the injected water and the displaced oil are not separated by a sharp interface. A two-layer reservoir flow model is developed with which the limitations of quantitative analysis are explored. If a quantitative inversion technique is error free the resolution limits and signal noise in the seismic data allow only spatially averaged reservoir properties to be known. In some reservoirs undergoing water flood, volumetrically significant movement of the injected water may occur on length scales below that of the resolution and noise threshold the seismic data allows. In such a reservoir the inversion technique gives good quality information about the average location of the injected water but does not provide information about how all the injected water is moving. Specifically the possibility of thin high permeability layering carrying a significant fraction of the injected water cannot be eliminated. We show that this can introduce great uncertainty in estimates of reservoir performanc

Modular engineering of neuromuscular gait simulators

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 72-73).In this thesis we present a novel approach to the computer simulation of forward dynamic gait models and the optimization of parameters that must be tuned for such models. This methodology is not limited to gait simulation, and could be useful for any situation in which a complex Simulink model requires variables to be tuned via machine learning to optimize all heuristic that can only be evaluated via simulation. Through the lens of Biomechatronic engineering research, we combine the fundamentals of software engineering with a refinement of the best practices of Matlab and Simulink programming and a working knowledge of inherent Matlab and Simulink constraints to construct a framework for rapid model development. Key features of this methodology include: the use of Simulink as an environment for rapidly prototyped models, the use of and construction of custom Simulink libraries, and use of the Matlab Optimization Toolbox. This methodology uses parallel evaluation of rapid acceleration Simulink executables to minimize optimization time, and allow research teams to take advantage of parallel processing and cloud computing. This methodology was applied to a bouncing gait model developed by Hartmut Geyer for evaluation. We demonstrate its effectiveness by simulating this model using a custom library of model components, such as ground contact model, Stateflow control, heuristic computation, and body segments.by Matthew D. Furtney.S.M

Innovative Remote Sensing of Coastal Internal Waves and Their Effect on Air-Sea Fluxes

Synthetic aperture radar (SAR) is the premier instrument in satellite remote sensing for the detection of oceanic internal waves due to its sensitivity to changes in small-scale ocean surface roughness and relatively large spatial coverage. The satellite constellation COSMO-SkyMed offers the unique capability to acquire pairs of images of the same scene within 24 minutes, which is ideal for making internal wave motions visible and extracting phase speeds. Other researchers have used pairs of airborne SAR images or images from two different satellite systems, but to our knowledge none have developed an automated method or applied standard feature tracking techniques due to the challenges SAR data poses. Unlike optical images, SAR images suffer from speckle noise and images in a pair can have different look directions, making it difficult to apply feature tracking algorithms for quantifying motions. We developed a multistep technique to identify internal waves and estimate their phase speeds and propagation directions from pairs of SAR images. The estimated speeds are comparable to results based on in situ measurements and KdV theory.Traditionally, researchers studying internal waves limit their focus to the oceanic side of the boundary layer. However, it has been speculated that internal waves can drive wind velocity and stress variance resulting in the enhancement of the total air-sea momentum flux. We investigate the implications of momentum transfer associated with internal waves using data from the CLASI 2021 field experiment. The marine radar swath contains one of the eight ASIS buoys deployed in the Bay. Combining time series and wavelet analysis we relate the radar detected internal wave to the wind information from the ASIS buoy. We suggest the internal waves redistribute the momentum flux among spatial scales without changing the total vertical transport. However, internal waves fall under the synoptic scale rather than the turbulence scale. Therefore they may contribute to the global momentum transfer, but we suggest they should be excluded from turbulent flux estimates.</p

Simple models for the complex process of rock blasting

Numerical modeling of rock blasting is being investigated actively by many groups in the mining and explosives industries. The physical processes occurring in rock blasting span six orders of magnitude in length-scale, time-scale and pressure. The interactive-physical processes involved are time-dependent, non-linear, difficult to quantify experimentally and occur in a discontinuous, heterogeneous medium. These factors present a significant challenge to the modeler. As a compliment to the complex-numerical models being developed, we present a simple model of the blasting process with the objectives of (i) aiding in the understanding of the physical mechanisms occurring during rock blasting and (ii) helping in the development and interpretation of more complex numerical models. The model illustrates the time scales involved and the distribution of the chemical energy of the explosive. The model compares well with published rock blasting experiments