A new perspective to model subsurface stratigraphy in alluvial hydrogeological basins, introducing geological hierarchy and relative chronology

https://doi.org/10.1016/j.cageo.2020.104506Get rights and content

Highlights

  • Geological knowledge converted into modelling rules within an automatic routine.

  • HIEGEO implements hierarchic stratigraphic approach to model nested alluvial units.

  • Strong and traceable linkage between modelled geometries and their geological origin.

  • Representation of geological architecture at different degrees of detail.

  • Free and open source, applicable to different contexts, extensible to 3-D modelling.

Abstract

This paper presents a novel perspective for modelling alluvial stratigraphy. It integrates the spatial geological information, geological maps and well-log descriptions, with the rules describing the hierarchy and relative chronology of the geological entities. As geological modelling tools are moving fast forward, the urgent need for expert geological input, codified as modelling rules, persists. Concerning subsurface alluvial architectures, the concepts of “stratigraphic hierarchy” and “relative chronology” provide the most relevant rules which permit to link the modelling procedure to the geo-history of a region.

The paper shows how to formalize this knowledge into modelling rules. This is illustrated and implemented in a Python™ module named HIEGEO which is applied on a 2-D cross-section from the Po Basin (N-Italy). The stratigraphic correlation yields 2-D pictures of the hierarchic stratigraphy and relative chronology of the units. The input are: an attribute table of stratigraphic boundaries expressing their hierarchy and chronology; contact points where these boundaries cross the control logs. Since the aim of HIEGEO is to illustrate the principle of the method but not to replace existing 3-D geological modelling tools, it implements a linear interpolation algorithm which creates joins between contact points. It plots linear joins framing polygons based on their hierarchy, at any user's desired detail. HIEGEO highlights potential inconsistencies of the input dataset, helping to re-evaluate the geological interpretation.

The proposed workflow allows to: i) translate geological knowledge into modelling rules; ii) compute stratigraphic models constrained by the hierarchy of stratigraphic entities and the relative chronology of geological events; iii) represent internal geometries of the stratigraphic units, accounting for their composite nature; iv) reduce uncertainty in modelling alluvial architectures. It represents a starting point for multi-scale applications and could be easily integrated into 3-D modelling packages, to couple the hierarchical concept proposed here with existing advanced interpolation methods.

Section snippets

Rationale and aims of the work

Modelling the alluvial stratigraphy of sedimentary basins is important for many applications, like management of groundwater and shallow geothermal resources, or geohazard evaluation. The stratigraphic architecture of alluvial basins derives from multiple geological processes, acting at different spatial and temporal scales. The result is a nested, hierarchical arrangement of the sedimentary bodies and their internal heterogeneities: highest-hierarchy and large stratigraphic units are built-up

General workflow

The proposed workflow is illustrated in Fig. 2. It involves three main steps: the geological interpretation of the data-set in terms of hierarchy and relative chronology rules; the coding of these data using a standardized framework; the computation of the set of interfaces honouring the observations and the presented rules.

As for most geological modelling studies, field and subsurface data represent the starting point. The dataset is organized using a GIS, which permits to manage scale,

Raw data and introduction of the illustrative example

The dataset used to illustrate the proposed workflow derives from the stratigraphic study of the Quaternary fill of the Po Foreland Basin (Cavalli, 2012; Bersezio et al., 2016, Fig. 3). The selected area belongs to the glacio-fluvial and alluvial terraced landscape at the northern alpine margin of the Po Basin. Its stratigraphic architecture is the result of the progressive southward entrenchment and filling of alluvial valleys into the Pliocene-Lower Pleistocene marine sediments, followed by

Interpreting the cross-sections

The subsurface stratigraphic data are analysed with a rigorous GIS data-management method to preserve internal consistency during subsequent elaborations. It involves the following steps:

  • (1)

    1-D analysis (Fig. 4-A). The sharp “coarse-grained above fine-grained” sediment contacts are picked within each borehole, thus subdividing the stratigraphic logs into a sequence of lithotextural intervals, bounded by abrupt textural contacts (compare to the criteria adopted in Fig. 1). The sediment packages in

Computational steps

In the previous steps, the geological interpretation and the raw data have been coded to obtain a table, containing the coordinates of the contact points and their corresponding attributes (Fig. 4-B). In addition to the input table, HIEGEO reads a parameter file (JSON format) that contains information about the discretization grid, like the minimum and maximum x and z coordinates, and the size of the cells (Δx and Δz). A discretization grid is required to allow the export of the interpreted

Summary and conclusions

The proposed workflow integrates hard geometrical constraints (spatial coordinates of the contact points) and shows how hierarchical rules can be employed in addition to relative chronology to delineate stratigraphic entities in a geological model. This was illustrated on the alluvial stratigraphy of the Po Plain sedimentary basin (Italy). The Python™ code HIEGEO demonstrates, by using a simple illustrative case, how the rules derived from the geological knowledge can be formalized, yielding

Authorship statement

CZ and RB conceived the presented idea, provided the geological data-frame and wrote the manuscript. AC developed the PythonTM script, performed computations and wrote the section related to the modelling procedure. PR aided in interpreting the results and worked on the manuscript. RB and PR supervised the findings of this work.

Computer code availability

The Python™ module HIEGEO can be downloaded and checked at the following link: https://bitbucket.org/alecomunian/hiegeo. Developer: Alessandro Comunian. Dipartimento di Scienze della Terra, Università degli Studi di Milano, via Cicognara 7, 20129 I-Milano, Italy. [email protected].

Funding

This work was supported by funds to RB [grant-RV_ATT_COM16RBERS_M] and to AC [grant-PSR2018_ACOMUNIAN].

Declaration of competing interest

No potential conflict of interest was reported by the authors.

Acknowledgments

The final version of the manuscript benefits from the thoughtful suggestions of F. Wellmann and two anonymous Referees.

References (51)

  • A.M. Lemon et al.

    Building solid models from boreholes and user-defined cross-sections

    Comput. Geosci.

    (2003)
  • S.D. Mackey et al.

    A revised FORTRAN progra to simulate alluvial stratigraphy

    Comput. Geosci. Geosci.

    (1992)
  • A.D. Miall

    Architectural-element analysis: a new method of facies analysis applied to fluvial deposits

    Earth Sci. Rev.

    (1985)
  • K.J. Weber

    How heterogeneity affects oil recovery

  • F. Wellmann et al.

    3-D Structural geological models: concepts, methods , and uncertainties

    Adv. Geophys.

    (2018)
  • J.F. Wellmann et al.

    Validating 3-D structural models with geological knowledge for improved uncertainty evaluations

    Energy Procedia

    (2014)
  • C. Wijns et al.

    Inverse modelling in geology by interactive evolutionary computation

    J. Struct. Geol.

    (2003)
  • G. Zappa et al.

    Modeling heterogeneity of gravel-sand, braided stream, alluvial aquifers at the facies scale

    J. Hydrol.

    (2006)
  • C. Zuffetti et al.

    Soil evolution and origin of landscape in a late Quaternary tectonically mobile setting: the Po Plain-Northern Apennines border in Lombardy (Italy)

    Catena

    (2018)
  • T. Aigner et al.

    A hierarchical process-approach to reservoir heterogeneity: examples from outcrop analogues

    Bull. du Cent. Rech. Elf Explor. Prod.

    (1999)
  • P.A. Allen et al.

    Basin Analysis: Principles and Application to Petroleum Play Assessment

    (2013)
  • R. Bersezio

    Aquifer analogues

    Mem. Descr. della Cart. Geol. d’Italia LXXVI

    (2007)
  • R. Bersezio et al.

    Note Illustrative Della Carta Geologica d'Italia Alla Scala 1:50.000. Foglio 097 - Vimercate

    (2014)
  • R. Bersezio et al.

    The Quaternary N-Apennine tectonics recorded in the Po Basin: stratigraphic and geomorphological evidences along a N-S traverse in Lombardy (Italy )

    Geophys. Res. Abstr.

    (2016)
  • A. Bini et al.

    Note Illustrative Della Carta Geologica d'Italia Alla Scala 1:50.000. Foglio 96 - Seregno

    (2014)
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