Analysis of data quality for subsurface 3D geological modeling

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1 GIT Chiavenna (SO) Analysis of data quality for subsurface 3D geological modeling Piana F. (1), Irace A. (1), Morelli M. (2), Mosca P. (1), Nicolò G. (2) CNR IGG TO (1) ; ARPA Piemonte (2) (1) CNR, Istituto di Geoscienze e Georisorse, Via Valperga Caluso, 35 - Torino. (2) ARPA Piemonte, Dip. Geologia e Dissesto, Via Pio VII, 9 - Torino,

2 Subsurface geological knowledge in Piemonte? not so well constrained as in other adjoining regions subsurface data on the southern part of the region are more easily available than those of the northern one... some scientific papers (regional syntheses) and a regional deep hydrostratigraphic recontruction are available co-operation agreement between institutions (research and governement) and ENI are very recent...

3 Piemonte subsurface data set ENI seismic lines stratigraphic data and correlation hydrostratigraphic data

4 not so many industrial wells for correlation from outcrops to seismic reflectors Mosca, 2006

5 ... before starting with 3D modeling we have recently mapped the main litho-stratigraphic and discontinuity surfaces, correlating them through the all southern Piemonte at surface and depth data have been organically stored and described in a DB compliant with INSPIRE - GeoSciML data models general agreement on the intended-meanings of most sub-surface geological objects has been achieved

6 -Georeferenced and well-located Objects -clear Intended Meaning -traceable Sources this is what we can call Data Quality DQ is essentially data traceability where Data are stored?

7 Piemonte Geological Map 1: scale DB 250k GeoPiemonte

8 First release of 250KGeoPiemonte: only a simplified graphical layout is available at present Digital structure (.shp) Data Model and DB Conceptual model Descriptive standards

9 250kGeoPiemonte DB Structure

10 Geological Knowledge transfer by using Description Standards DB 250KGeoPiemonte

11 DB 250KGeoPiemonte Geological Knowledge transfer by using Description Standards INSPIRE Data Specification on Geology + GeoSciML Controlled Vocabulary INSPIRE CGI INSPIRE CGI INSPIRE New Attribute Tables Creating Project Attribute Tables using standard - calibrating them to project goals -using Controlled Concepts and Vocabulary

12 correlation to depth is grounded on analysis of Data Quality Hierarchy Source Purpose Intended Meaning

13 regional scale correlations Irace et al., 2010 hydrostratigraphic units

14 Foglio 194 Acqui Terme Piana et al., 2013 clear definition of geological objects supports Data Quality Foglio 194 Acqui Terme (Piana et al., 2013)

15 Mosca et al., 2010 Knowledges leading up to... 3D MODELING log correlation facies distribution

16 Mosca et al., 2010 Kinematic reconstructions at regional scale Knowledges leading up to... 3D modeling

17 Irace et al., 2010 Synthems distribution both at surface and depth Knowledges leading up to... 3D modeling

18 3D visualization Torino city subsurface attempts (for land management) I. 250K GeoPiemonte DB II. Standard Geological Objects ARPA-CNR project Map of the Torino area - G.Fioraso et al. III. Numerical representation of GeObj IV.Surfaces reconstruction (EnterVol - CTech software) V. 3D visualization below topography (Terra Builder)

19 III. numerical representation of surfaces

20 IV. Surfaces reconstruction (EnterVol - CTech software)

21 V. 3D visualization below topography (Terra Builder)

22 V. 3D visualization below topography (Terra Builder)

23 Remarks large and updated data sets (outcrops and subsurface) are available from several institutions in Piemonte data have been mutually integrated in the frame of several research projects a great part of data are stored in the 250k Piemonte DB that has a data model and controlled vocabulary (descriptive standards) some 3D visualization attempts have been done in critical areas these knowledges could be a good starting point to extend correlations of litho- hydrostratigraphic units from the western to the central sector of the Po plain... even in a 3D modeling perspective

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