The SmartGeo project aims to enhance the use of geophysical prospecting techniques for characterizing contaminated sites by integrating computational, modeling, and industry expertise. It includes the development of data analysis applications, information dissemination, and practical specifications that align with user requirements, as well as the implementation of multi-offset Ground Penetrating Radar (GPR) surveys. Additionally, the project promotes the use of advanced imaging technology and grid computing to optimize data collection and analysis in environmental studies.

1. SmartGeo
Bonifiche
7-11-2014
SmartGeo

2. SmartGeo
Il ruolo della prospezione geofisica nella
caratterizzazione del sito contaminato:
concetti generali, potenzialita’,
problematiche e sviluppi recenti

3. Il progetto SmartGeo
In questo progetto il CRS4 si propone di mettere
in connessione le capacita’ modellistiche,
informatiche e computazionali dei suoi
ricercatori con la competenza delle aziende
coinvolte, e di ingegnerizzare gli applicativi
sperimentali sviluppati nel progetto Grida3, fino
ad ottenere un prodotto professionale che
soddisfi le esigenze reali di un utilizzatore

4. 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 delle
esigenze pratiche e delle specifiche richieste delle
aziende coinvlte nel cluster.
• WP3 Costruire il prodotto: implementazione
dell’applicativo di analisi dati. In questa fase si
implementeranno le caratteristiche scaturite in fase di
analisi.

5. Seismic reflection data acquisition
Gestore di Risorse Condivise per Analisi di
Dati e Applicazioni Ambientali

6. GPR data
Multi-offset GPR data:
Aim: monitoring of water content and water
conductivity
Target depth: 0 - 5 m
2D line: length 55 m
RAMAC/GPR CU II with MC4 +
4 unshielded 200 Hz antennas
Number of sources: 546
Source spacing: 0.1m
Number of receivers: 28
Receiver spacing: 0.2 m
Maximum offset: 0.6 m

7. SR/GPR data: Fields of application
Environmental EEEnnnvvviiirrrooonnnmmmeeennntttaaalll eeeennnnggggiiiinnnneeeeeeeerrrriiiinnnngggg::::
Detection of problematic solid-waste in dumping grounds
Control of the topography of the impermeable basement
SSSSeeeeiiiissssmmmmiiiicccc aaaannnndddd ggggeeeeooootttteeeecccchhhhnnnniiiiccccaaaallll eeeennnnggggiiiinnnneeeeeeeerrrriiiinnnngggg::::
Characterization of landslides on slopes proximal to the
Gestore di Risorse Condivise per Analisi di
Dati e Applicazioni Ambientali
ground rupture
Evaluation of the seismic local response
HHHHyyyyddddrrrrooooggggeeeeoooollllooooggggyyyy::::
Identification of aquifer boundaries
Estimation of hydrological parameters (porosity, fluid
content, etc.)

9. 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

10. Modelli a confronto
Flusso di lavoro per la prospezione di idrocarburi:
Prima fase: indagine geofisica su larga scala che
fornisce una copertura laterale e una continuita’ che
permettono di interpretare la situazione geoologica e di
individuare le zone bersaglio
Seconda fase: campagna di perforazione intensive nei
bersagli individuati, accompagnate o meno da ulteriori
indagini geofisiche piu focalizzate su particolari regioni.
Motivazione: la perforazione dei pozzi e’ molto piu’
costosa rispetto all’esplorazione geofisica.

11. 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

12. 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

13. • Figure 1. Image of the land surface at OU-1 and underlying clay aquitard
surface. Borehole and CPT positions (shown in blue) form a veritable well
forest.

14. • 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.

15. • 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.

16. • Figure 4. (a) GPR coverage over
site OU-1: heavy blue lines show
locations where the clay aquitard
could 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.

17. • 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.

18. • 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.

19. • 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.

20. • 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.

21. • 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.

22. 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.

23. 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.

24. 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
APPLICATIONS
GIS Tools
EIAGRID
EIAGImaRgiInDg
Service
Secure access Infrastructure User Interfaces
TECHNOLOGIES
Meteorology
Hydrology
Site
Remediation
Geophysical
Imaging

25. The EIAGRID Portal
Main Objectives
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
Gestore di Risorse Condivise per Analisi di
Dati e Applicazioni Ambientali

26. The EIAGRID Portal
Main Objectives
Creating a data grid environment to facilitate analysis
decision making in integrated multi-disciplinary studies 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
Gestore di Risorse Condivise per Analisi di
Dati e Applicazioni Ambientali

27. Multi-offset GPR data:
27

28. 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: 546
Source spacing: 0.1m
Number of receivers: 28
Receiver spacing: 0.2 m
Maximum offset: 6 m
28
CMP gather at 10
m

29. Data vviissuuaalliizzaattiioonn ttoooollss

30. Data vviissuuaalliizzaattiioonn ttoooollss

31. Data vviissuuaalliizzaattiioonn ttoooollss

33. Data vviissuuaalliizzaattiioonn ttoooollss
cm/μs
MHz
cm/μs
cm/μs

34. Data vviissuuaalliizzaattiioonn ttoooollss
cm/μs
MHz
cm/μs
cm/μs
cm
cm
cm/μs
μs
cm
cm

37. CRS stacking result obtained after 4 minutes using 50 CPU

38. TTiimmee ddoommaaiinn iimmaaggiinngg
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

39. Seismic reflection data processing
Input System Output
Gestore di Risorse Condivise per Analisi di
Dati e Applicazioni Ambientali
Seismic Records
Processing Phases Subsurface Image

40. Main Problem of SSRR//GGPPRR aaccqquuiissiittiioonn::
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

41. Remote Grid Computing
Preprocessing and Visualization PPPrrreeeppprrroooccceeessssssiiinnnggg aaannnddd VVViiisssuuuaaallliiizzzaaatttiiiooonnn uuuussssiiiinnnngggg SSSSUUUU::::
Basic preprocessing steps can be applied without installing
the complex SU processing package.
IIIImmmmaaaaggggiiiinnnngggg aaaannnndddd RRRRSSSSCCCC uuuussssiiiinnnngggg CCCCRRRRSSSS tttteeeecccchhhhnnnnoooollllooooggggyyyy::::
Data-driven CRS imaging technology---state-of-the-art in oil
exploration---enables highly automated data processing.
GRID deployment using high performance computing
facilities provides the necessary computing power.
PPPPaaaarrrraaaalllllllleeeellll pppprrrroooocccceeeessssssssiiiinnnngggg ooooffff ddddiiiiffffffffeeeerrrreeeennnntttt PPPPrrrroooocccceeeessssssssiiiinnnngggg wwwwoooorrrrkkkkfffflllloooowwwwssss::::
Cumbersome sequential optimization of processing
workflow and processing parameters speeds up drastically.
Gestore di Risorse Condivise per Analisi di
Dati e Applicazioni Ambientali

42. EEIIAAGGRRIIDD PPoorrttaall

43. DDaattaa--sseett uuppllooaaddiinngg aanndd ffoorrmmaatt ccoonnvveerrssiioonn
Near Surface Environment
Geotechnical Geophysics: SO-14

44. Data vviissuuaalliizzaattiioonn pprree--pprroocceessssiinngg
Near Surface Environment
Geotechnical Geophysics: SO-14

45. DDaattaa pprree--pprroocceessssiinngg ttoooollss
Near Surface Environment
Geotechnical Geophysics: SO-14

46. Data vviissuuaalliizzaattiioonn ttoooollss
Near Surface Environment
Geotechnical Geophysics: SO-14

47. CCRRSS ddaattaa pprroocceessssiinngg
Near Surface Environment
Geotechnical Geophysics: SO-14

48. Workflows running in parallel
Gestore di Risorse Condivise per Analisi di
Dati e Applicazioni Ambientali

49. New field ssttuuddyy uussiinngg SSHH--wwaavveess ((DDIITT))
AAAAddddvvvvaaaannnnttttaaaaggggeeee ooooffff sssshhhheeeeaaaarrrr wwwwaaaavvvveeee ddddaaaattttaaaa::::
Neither ground roll nor direct waves are generated
Near Surface Environment
Geotechnical Geophysics: SO-14

50. TTiimmee ddoommaaiinn iimmaaggiinngg
Obtained using Obtained using Seismic the Processing EIAGRID portal
Workshop ©
(Parallel Geoscience Corporation)
Results shear wave data
Near Surface Environment
Geotechnical Geophysics: SO-14

51. Conclusions
… facilitates the creation of an integrated geophysical
database for environmental studies.
Gestore di Risorse Condivise per Analisi di
Dati e Applicazioni Ambientali
EIAGRID
...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 environmental
and earth sciences through Grid technologies