SmartGeo Bonifiche 7-11-2014 SmartGeo
Jun 27, 2015
SmartGeoBonifiche 7-11-2014
SmartGeo
SmartGeo
Il ruolo della prospezione geofisica nellacaratterizzazione del sito contaminato:
concetti generali, potenzialita’, problematiche e sviluppi recenti
Il progetto SmartGeo
In questo progetto il CRS4 si propone di metterein connessione le capacita’ modellistiche, informatiche e computazionali dei suoiricercatori con la competenza delle aziendecoinvolte, e di ingegnerizzare gli applicativisperimentali sviluppati nel progetto Grida3, finoad ottenere un prodotto professionale chesoddisfi le esigenze reali di un utilizzatore
Il progetto SmartGeo
• WP1 Informazione e formazione : diffusione e discussione dei risultati ottenuti dal CRS4 nel campo delle tecniche id imaging near-surfce (GPR e sismica a riflessione)
• WP2 Dalla realta’ alle specifiche : ascolto delleesigenze pratiche e delle specifiche richieste delleaziende coinvlte nel cluster.
• WP3 Costruire il prodotto : implementazionedell’applicativo di analisi dati. In questa fase siimplementeranno le caratteristiche scaturite in fase dianalisi.
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
Seismic reflection data acquisition
GPR data
Multi-offset GPR data:
Aim: monitoring of water content and water conductivity
Target depth: 0 - 5 m
2D line: length 55 mRAMAC/GPR CU II with MC4 + 4 unshielded 200 Hz antennas
Number of sources: 546Source spacing: 0.1mNumber of receivers: 28Receiver spacing: 0.2 mMaximum offset: 0.6 m
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
SR/GPR data: Fields of application
Environmental engineering:Environmental engineering:Environmental engineering:Environmental engineering:� Detection of problematic solid-waste in dumping grounds
� Control of the topography of the impermeable basement
� Characterization of landslides on slopes proximal to the ground rupture
Seismic and geotechnical engineering:Seismic and geotechnical engineering:Seismic and geotechnical engineering:Seismic and geotechnical engineering:
� Evaluation of the seismic local response
Hydrogeology:Hydrogeology:Hydrogeology:Hydrogeology:� Identification of aquifer boundaries
� Estimation of hydrological parameters (porosity, fluid content, etc.)
Modelli a confronto
Prospezione geologica per la ricerca di idrocarburi
� Indagine geofisica su larga scala
� Perforazioni guidate dai risultati geofisici
� I pozzi sono costosi rispetto alla prospezione geofisica
Caratterizzazione di siti contaminati
� Lo scavo serve spesso come strumento di esplorazione primario
� La geofisica, se e' usata, arriva in un secondo tempo se i dati di pozzo sono inadeguati
Modelli a confronto
Flusso di lavoro per la prospezione di idrocarburi :
Prima fase : indagine geofisica su larga scala chefornisce una copertura laterale e una continuita’ chepermettono di interpretare la situazione geoologica e diindividuare le zone bersaglio
Seconda fase : campagna di perforazione intensive neibersagli individuati, accompagnate o meno da ulterioriindagini geofisiche piu focalizzate su particolari regioni.
Motivazione : la perforazione dei pozzi e’ molto piu’costosa rispetto all’esplorazione geofisica.
Modelli a confronto
Perche questo approccio differente?
� Spesso i site manager hanno una formazione ingegneristica e sono meno propensi all'uso dei dati geofisici
� L'economia della caratterizzazione dei siti inquinati e' guidata da interessi punitivi o dalla paura delle eventuali sanzioni
� l'esplorazione petrolifera e' guidata dal guadagno ---> maggiore propensione al rischio
Modelli a confronto
L'applicazione di tecniche geofisiche per la caratterizzazione di siti inquinati comporta:
� Rilevanti vantaggi in termini tecnici ed economici
� Maggiore complessita’ nella gestione dei dati
� Necessita’ di conoscenze interdisciplinari
• Figure 1. Image of the land surface at OU-1 and underlying clay aquitardsurface. Borehole and CPT positions (shown in blue) form a veritable well forest.
• Figure 2. Electromagnetic wave propagation velocity as a function of NAPL concentration and porosity. As the mixture grades from full water saturation to full NAPL saturation, the velocity may increase by a factor of 3.
• Figure 3. (a) 3D map of the clay aquitard surface constructed from a 3D multi-offset GPR survey designed to investigate the bowl-shaped topographic low adjacent to well U1-072.
• (b) Clay surface with the upper surface of a high-velocity zone that forms an umbrella over the topographic low. Subsequent borehole sampling showed NAPL concentrations as high as 4% within the high-velocity zone.
• Figure 4. (a) GPR coverage over site OU-1: heavy blue lines show locations where the clay aquitardcould be identified, red indicates the location of multi-offset profiles.
• (b) Clay aquitard map derived from GPR measurements and boreholes showing a complex system of paleochannels that drain toward the southwest during low water-table conditions.
• (c) Clay aquitard map derived from wells alone which does not adequately characterize the channel system.
• Figure 5. Map of the four areas identified for detailed multi-offset investigation. Anomaly lines cross features similar to those shown in Figure 3. Area 3 is focused on the deepest paleochannel present at the site. Black dots show previous well locations.
• Figure 6. (a) CDPs along line A3L1 (Figure 5) showing heavy contamination with air waves scattered from out-of-plane fences (horizontal events in the upper set of CDPs).
• (b) Prestack f-k filtering is effective for removing air-wave noise.
• Figure 7. (a) Standard common-offset radar image of line A3L1 (Figure 5) that is heavily contaminated with out-of-plane air-wave scatter.
• (b) Stacking alone cannot adequately attenuate the air-wave noise.
• (c) Prestack f-k filtering in the CDP domain virtually removes all air-wave noise revealing the base of the paleochannel.
• Figure 8. The upper image shows the PSDM result along Line A3L3 (Figure 5). The deep channel in the clay surface is partially filled with water.
• The zone of anomalous reflectivity 1–2 m above the water table is associated with a high-velocity zone shown in the lower image.
• This zone was later found to have a substantial LIF anomaly and up to 5% volumetric LNAPL contamination.
• Figure 9. The upper image shows the prestack depth-migrated section along line ANL4 (Figure 5).
• The clay depression with low-amplitude overlying reflectivity was targeted for further investigation. The lower image show the results of reflection tomograpy.
• A high-velocity zone lying within the clay depression correlated with a LIF anomaly and indicates possible NAPL contamination.
Eiagrid
Il contributo del CRS4
� Il gruppo di geofisica computazionale del CRS4 ha lavorato per molti anni allo sviluppo di codici di calcolo per l'analisi dei dati sismici per la prospezione di idrocarburi.
� Nel progetto Eiagrid ha sviluppato, in collaborazione con il Dicaar (G.P. Deidda) una infrastruttura di calcolo che:
� minimizza le risorse software & hardware richieste all'utilizzatore per una acquisizione dati SR/GPR efficace.
Eiagrid
� ...consente un controllo di qualita in quasi real-time sui dati acquisiti e una ottimizzazione dei parametri di acquisizione anche per utenti meno esperti;
� …fornisce risultati accurati utilizzando algoritmi di imaging data driven implementati con metodologie di high performance computing;
� facilita la collaborazione remota e la creazione di database integrati per gli studi di problemi ambientali.
Grida3, Shared
Resources Manager for
Environmental Data Analysis
and Applications
The Grida3 portal aims at supporting problem solving and decision making by integrating
resources for
communication
computation
data storage
software for
simulation
inversion
visualization
and human know how
into a grid computing platform for Environmental Sciences
The Grida3 portal aims at supporting problem solving and decision making by integrating
resources for
communication
computation
data storage
software for
simulation
inversion
visualization
and human know how
into a grid computing platform for Environmental Sciences
TECHNOLOGIESTECHNOLOGIES
InfrastructureInfrastructure User InterfacesUser InterfacesSecure accessSecure access
APPLICATIONSAPPLICATIONS
GIS ToolsGIS Tools
MeteorologyMeteorology
HydrologyHydrology
Site Remediation
Site Remediation
GeophysicalImaging
GeophysicalImagingEIAGRID
ServiceEIAGRIDService
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
Creating a grid computing environment for in-field QC and Optimization of SR/GPR data acquisition by:
1. Providing a web-browser-based user interface easily accessible from the field
2. On-the-fly processing of the seismic field data using a remote GRID environment
3. Fast optimization of data analysis and imaging parameters by parallel processing of alternative workflows
The EIAGRID PortalMain Objectives
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
Creating a data grid environment to facilitate analysis & decision making in integrated multi-disciplinary s tudies by:
1. Providing a flexible and customizable data grid management architecture using iRODS
2. Georeferencing the data using Geo Information System (GIS) technologies
3. Interconnecting the different types of data by mesh-generators and data crossing techniques
The EIAGRID PortalMain Objectives
Multi-offset GPR data:
27
Multi-offset GPR data:● Aim: monitoring of water content and water conductivity
● Target depth: 0 - 5 m
● Profile length: 55 m
Instrumentation:RAMAC/GPR CU II with MC4 + 4 unshielded 200 MHz antennas
Geometry:Number of sources: 546Source spacing: 0.1mNumber of receivers: 28Receiver spacing: 0.2 mMaximum offset: 6 m
28
CMP gather at 10 m
Data visualization toolsData visualization tools
Data visualization toolsData visualization tools
Data visualization toolsData visualization tools
Data visualization toolsData visualization tools
cm/µs
cm/µs
cm/µs
MHz
Data visualization toolsData visualization tools
MHz
cm/µs
cm/µs
cm/µs
cm/µs
cm
cm
cm
cm
µs
CRS stacking result obtained after 4 minutes using 50 CPU
Time domain imagingTime domain imaging
Published in: Perroud, H., and Tygel, M., 2005, Velocity estimation by the common-reflection-surface (CRS) method: Using ground-penetrating radar: Geophysics, 70, 1343–1352.
Results GPR data
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
Seismic reflection data processing
Seismic Records
Input System Output
Processing Phases Subsurface Image
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
Main Problem of SR/GPR acquisition:Main Problem of SR/GPR acquisition:
Real-time processing is difficult and cost intensive
� Acquisition parameters such as recording time, sampling interval, source strength and receiver
spacing cannot be optimized in the field
Solution:Wireless data
transmission + remote GRID computing facilities
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
Remote Grid Computing
Preprocessing and Visualization using SU:Preprocessing and Visualization using SU:Preprocessing and Visualization using SU:Preprocessing and Visualization using SU:� Basic preprocessing steps can be applied without installing
the complex SU processing package.
� Data-driven CRS imaging technology---state-of-the-art in oil exploration---enables highly automated data processing.
Imaging and RSC using CRS technology:Imaging and RSC using CRS technology:Imaging and RSC using CRS technology:Imaging and RSC using CRS technology:
� GRID deployment using high performance computing facilities provides the necessary computing power.
Parallel processing of different Processing workflows:Parallel processing of different Processing workflows:Parallel processing of different Processing workflows:Parallel processing of different Processing workflows:� Cumbersome sequential optimization of processing
workflow and processing parameters speeds up drastically.
EIAGRID PortalEIAGRID Portal
DataData--set uploading and format conversionset uploading and format conversion
Near Surface & Environment & Geotechnical Geophysics: SO-14
Data visualization & preData visualization & pre--processingprocessing
Near Surface & Environment & Geotechnical Geophysics: SO-14
Data preData pre--processing toolsprocessing tools
Near Surface & Environment & Geotechnical Geophysics: SO-14
Data visualization toolsData visualization tools
Near Surface & Environment & Geotechnical Geophysics: SO-14
CRS data processingCRS data processing
Near Surface & Environment & Geotechnical Geophysics: SO-14
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
Workflows running in parallel
New field study using SHNew field study using SH--waves (DIT)waves (DIT)
Advantage of shear wave data:Advantage of shear wave data:Advantage of shear wave data:Advantage of shear wave data:Neither ground roll nor direct waves are generated
Near Surface & Environment & Geotechnical Geophysics: SO-14
Results shear wave data
Time domain imagingTime domain imaging
Obtained using Seismic Processing Workshop © (Parallel Geoscience Corporation)Obtained using the EIAGRID portal
Near Surface & Environment & Geotechnical Geophysics: SO-14
Gestore di Risorse Condivise per Analisi di Dati e Applicazioni Ambientali
ConclusionsEIAGRID
� ...minimizes the software and hardware requirements needed to perform a successful SR/GPR data acquisition.
� ...reduces the complexity of data QC and choice of acquisition parameter for less experienced users.
� …provides fast and accurate results by using modern imaging technology and high performance computing.
Enables a wider use of SR/GPR surveys in environmen tal and earth sciences through Grid technologies
� … facilitates the creation of an integrated geophysical database for environmental studies.