Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Seminario Ernesto Bonomi, 24-05-2012


Published on

Il seminario presenta un approccio innovativo al trattamento dei dati sismici mediante la combinazione di software di processing open source allo stato dell'arte con tecnologie informatiche di grid computing, rendendo possibile ed efficiente l'utilizzo di risorse distribuite e amministrate in remoto per il calcolo e la gestione dei dati. Inoltre illustra i risultati ottenuti per tre diversi tipi di dati (onde di compressione, onde di taglio e multi-offset Ground-Penetrating Radar), tratti da studi idrogeofisici condotti in Sardegna e a Larreule (Francia).

Published in: Technology
  • Be the first to comment

  • Be the first to like this

Seminario Ernesto Bonomi, 24-05-2012

  1. 1. Environmental and ImagingSciencesWEB Services: from Research to IndustrialApplications Ernesto Bonomi Energy and Environment CRS4
  2. 2. Motivation for DoingEnvironment is going to be a major issue.Since 50 years, environmental problems are aggravated by • overpopulation, • increases in agricultural productivity, • fast industrial development.Problems include • starvation and malnutrition, • demand for resources such as fresh water and food, • consumption of natural resources faster than the rate of regeneration (such as fossil fuels), • rising levels of atmospheric carbon dioxide, • global warming, and pollution.Strain on the environment causes a decrease in living conditions.Environmental engineering must grow rapidly from basicresearch and deal with the activities of monitoring andmanaging natural resources on an industrial scale.
  3. 3. ObjectivePromoting an interdisciplinary view of energy andenvironmental problems, in which the mechanisms, be they physical, chemical, biological, or economic,are no longer analyzed and modeled as independent, butare investigated together with the support of • robust theoretical frameworks • accurate numerical tools • reliable reference data • large computing infrastructures • motivated funding partnersOrganizing the efficient use our collective intelligence tostudy solution strategies and design innovative applications
  4. 4. From Modeling to Innovative ServicesProblem formalization Application planning Programming and optimization HPC application as a Cloud service
  5. 5. Critical Issues• The development of software tools for collaborative activities allowing a transparent access to • network resources • data acquisition systems • storage and computing platforms • application software within a unique infrastructureAn integrated vision that requires high level skills for:• The fundamental understanding of physical, chemical and biological processes operating at different scales• Programming and implementing on HPC clusters with architectures in continuous evolution (multicore CPUs, GPUs and FPGAs)• Conceptualizing the data analysis process and development of tools for problem solving and decision support
  6. 6. Real Collaborations and Virtual Organizations monitoring, Working Group 2: monitoring, and sustainable water resource Working Group 1: short management term prediction of extremeA Cloud/Grid is an eventsinfrastructure that allowsthe integrated andcollaborative use ofvirtualized resources Data servers Computational servers Working Group 3: information systems Connecting networks for the analysis of environmental and territorial data Numerical applications Information systemsowned and managed byone or more entities On the infrastructure, each virtual organization acts as a services provider while each partner, researcher or engineer, becomes the recipient
  7. 7. Project Planning and Management: the Developers Site 1 Site 2 Application Environmental developer engineer Compute infrastructure via the Cloud portal Data infrastructure via the Cloud portalNumerical applications input&output) GIS (input&output) Services for the decision support Pre- Pre-processing WEB Collaborative Environment Simulation Engine and Optimizer Data assimilation and Analysis Tools Post- Post-processing Problem Solving driven by physical models Visualization Web GIS (solver output, field data, maps…)
  8. 8. Project Planning and Management: the End Users Site 3 EnvironmentalCollaborative problem-solving managerplatform as a decision supportsystem Interactive simulation tools based on physics Web GIS environment for data Storage Retrieval Rendering Compute infrastructure Analysis and decision instruments for via the Cloud portal Management Meteorology Forest Fire Data infrastructure Planning via the Cloud portal Costs evaluation Hydrology Editing of results and dissemination Site Remediation Geophysical Earth Science Ocean Imaging Dynamics
  9. 9. Subsurface Imaging Servicesfor Environmental GeophysicsZeno Heilmann, Guido Satta, Andrea PirasCRS4, Department of Energy and EnvironmentPaolo MaggiNICE s.r.l., Department of Research and DevelopmentGianpiero DeiddaUniversity of Cagliari, Department of Civil and EnvironmentalEngineering and Architecture
  10. 10. Environmental Geophysical Imaging: a Cloud SolutionCreating a Cloud infrastructure for environmental geophysics• In-field Quality Control• Optimization of SR/GPR data acquisition/processing • Providing a browser-based user interface easily accessible from the acquisition field • On-the-fly processing of seismic data on the remote infrastructure • Running data-driven and highly parallel imaging and velocity analysis numerical tools • Enabling remote collaboration and monitoring of data acquisition
  11. 11. Environmental Geophysical: Data Acquisition
  12. 12. Environmental Geophysical: Data Processing Input SystemSeismic Records Processing Phases
  13. 13. Environmental Geophysical: Quality ControlOn-site-acquisition quality control is difficult when stronglyvariable near-surface conditions are encountered• Success depends on acquisition parameters such as • recording time • sampling interval • source strength • maximum offset • receivers spacingIt is impossible to optimize in the field the acquisition Cloud services from on-site tablets and PCs using Wireless data transmission + remote HPC processing
  14. 14. Acquisition Quality ControlPreprocessing and visualization using SU• Basic preprocessing steps can be applied fast and conveniently without locally installed processing package.Time imaging using CRS technology• Data-driven CRS imaging technology ---state-of-the-art in oil exploration--- enables highly automated data processing.• Velocity model building based on CRS results and time migration provide complementary subsurface information.Workflow editor:• Fast construction and processing of different workflows to find optimum processing parameters.
  15. 15. The Cloud Portal
  16. 16. The Cloud Portal: Dataset Uploading and DataConversion
  17. 17. The Cloud Portal: Creating a Project Using Uploaded Data
  18. 18. The Cloud Portal: Preprocessing the UploadedData
  19. 19. The Cloud Portal: Data Visualization tool
  20. 20. The Cloud Portal: CRS Imaging Tools
  21. 21. The Cloud Portal: CRS Imaging RunningJobs
  22. 22. The Cloud Portal: CRS Seismic Time ImagingDeidda, G. P., Ranieri, G, Uras, G., Cosentino, P., Martorana, R., 2006: Geophysicalinvestigations in the Flumendosa River Delta, Sardinia (Italy) --- Seismic reflectionimaging: Geophysics, 71, B121–B128.
  23. 23. The Cloud Portal: Velocity Model Builder
  24. 24. The Cloud Portal: Time Migration
  25. 25. The Cloud Portal: GPR Data Time Imaging CRS StackingPerroud, H., and Tygel, M., 2005, Velocity estimation by the common-reflection-surface(CRS) method: Using ground-penetrating radar: Geophysics, 70, 1343–1352.
  26. 26. Time Imaging without Velocity Model: a Data-Driven Solution • The best set of parameters ξ=(R, α0) provides reliable traveltimes • In the image space, the content of each pixel results from the signal averaged along a traveltime trajectory (green)Layers,imaging Sigsbee2A Time faults and diffractors Semblance
  27. 27. (Potential) Services for ForestFires Behavior PredictionAntioco Vargiu, Luca Massidda, Gianni Pagnini e Marino MarrocuCRS4, Department of Energy and Environment
  28. 28. Environmental SciencesA Web fire: simulation chainaLarge solver (2Km)Forest the integrationchain: Medium scale (10Km)Run of portal to the Ensemble Meteorological Forecast with Small scale (20Km) CFD GIS providing orography, boundary conditions and fuel distribution on the ground Selection of a date and an initial timeA collection of services Forest Fire service Selection of a site
  29. 29. Environmental Sciences & Process Engineering and Combustion Forest fire simulation: Budoni, 24 August 2004
  30. 30. ConclusionEnvironmental issues make necessary a strong integration of expertisefrom different disciplines, made possible through the development of virtualorganizations of federated entitiesToday SW technology makes almost transparent the operability of a Cloudinfrastructure (network, compute and data resources) for the data sharingand the exploitation of complex applications via InternetWeb services and Cloud portal technology makes man-Cloud interaction asmuch as possible close to man-desktop interaction