Integrating Sequence Stratigraphy and Geostatistical Methods for <scp>3D</scp> Lithofacies Modelling of the Tiber Alluvial Plain, Rome, Italy

ABSTRACT This study presents a detailed 3D lithofacies model of the Upper Pleistocene–Holocene Tiber Depositional Sequence (TDS) within the alluvial plain of Rome, Italy, developed using an integrated approach. A deterministic framework was used to establish 1D lithofacies constraints, while geostatistical algorithms, particularly indicator kriging, were employed to reconstruct the stacking patterns and interfingering of lithofacies within systems tracts. This methodology allows for the realistic depiction of depositional trends and stratigraphic architecture while addressing challenges posed by limited data density in unsampled locations. The resulting 3D model demonstrates its ability to honour observed data while enabling meaningful extrapolation of subsurface features. The model captures key evolutionary trends and aligns with the conceptual 2D stratigraphic reconstruction developed in this study and the sequence‐stratigraphic framework of the TDS derived from previous studies. Stratigraphic cross‐sections and 2D correlation profiles extracted from the 3D model reveal the depositional architecture and constrain the thickness and extent of primary lithofacies associations. Key findings include the identification of braided and meandering channel‐belt complexes associated with poorly and well‐drained floodplain deposits. The lowstand systems tract (LST) is characterised by extensive braided channel belts with high width‐to‐thickness ratios, while the transgressive systems tract (TST) exhibits vertically stacked meandering channels associated with poorly drained floodplains. The highstand systems tract (HST) shows increased channel clustering and lateral expansion of meandering channel belts, associated with well‐drained floodplain deposits displaying pedogenic features. The findings highlight the strengths and limitations of two‐point geostatistical algorithms, with indicator kriging outperforming traditional methods like Truncated Gaussian Simulation and Sequential Indicator Simulation in maintaining geological coherence and lateral continuity. The 3D model enhances our understanding of the Tiber alluvial basin evolution and provides a robust framework for urban geological applications. It serves as a pivotal tool for managing subsoil resources, mitigating geohazards, and preserving cultural heritage in densely populated areas. This approach demonstrates the feasibility of applying efficient, scalable techniques to model sedimentary successions in similar urbanised alluvial settings worldwide.

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Publication Details

Journal
Basin Research
Published
2025-02-28
DOI
https://doi.org/10.1111/bre.70024
Citations
2
Primary Topic
Geological formations and processes
Type
article
Field-Weighted Citation Impact
3.34
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article

Integrating Sequence Stratigraphy and Geostatistical Methods for 3D Lithofacies Modelling of the Tiber Alluvial Plain, Rome, Italy

Salvatore Milli, Maurizio Simionato, Michele Livani, Marco Mancini et al.
2 citations
Basin Research
Geological formations and processes
3.34
article

Integrating Sequence Stratigraphy and Geostatistical Methods for 3D Lithofacies Modelling of the Tiber Alluvial Plain, Rome, Italy

Salvatore Milli, Maurizio Simionato, Michele Livani, Marco Mancini, Massimiliano Moscatelli, Francesco Stigliano, Daniel Tentori
article en
2 citations

Abstract

ABSTRACT This study presents a detailed 3D lithofacies model of the Upper Pleistocene–Holocene Tiber Depositional Sequence (TDS) within the alluvial plain of Rome, Italy, developed using an integrated approach. A deterministic framework was used to establish 1D lithofacies constraints, while geostatistical algorithms, particularly indicator kriging, were employed to reconstruct the stacking patterns and interfingering of lithofacies within systems tracts. This methodology allows for the realistic depiction of depositional trends and stratigraphic architecture while addressing challenges posed by limited data density in unsampled locations. The resulting 3D model demonstrates its ability to honour observed data while enabling meaningful extrapolation of subsurface features. The model captures key evolutionary trends and aligns with the conceptual 2D stratigraphic reconstruction developed in this study and the sequence‐stratigraphic framework of the TDS derived from previous studies. Stratigraphic cross‐sections and 2D correlation profiles extracted from the 3D model reveal the depositional architecture and constrain the thickness and extent of primary lithofacies associations. Key findings include the identification of braided and meandering channel‐belt complexes associated with poorly and well‐drained floodplain deposits. The lowstand systems tract (LST) is characterised by extensive braided channel belts with high width‐to‐thickness ratios, while the transgressive systems tract (TST) exhibits vertically stacked meandering channels associated with poorly drained floodplains. The highstand systems tract (HST) shows increased channel clustering and lateral expansion of meandering channel belts, associated with well‐drained floodplain deposits displaying pedogenic features. The findings highlight the strengths and limitations of two‐point geostatistical algorithms, with indicator kriging outperforming traditional methods like Truncated Gaussian Simulation and Sequential Indicator Simulation in maintaining geological coherence and lateral continuity. The 3D model enhances our understanding of the Tiber alluvial basin evolution and provides a robust framework for urban geological applications. It serves as a pivotal tool for managing subsoil resources, mitigating geohazards, and preserving cultural heritage in densely populated areas. This approach demonstrates the feasibility of applying efficient, scalable techniques to model sedimentary successions in similar urbanised alluvial settings worldwide.

Basin ResearchVol. 37(2)
Institute of Environmental Geology and Geoengineering (IT), Sapienza University of Rome (IT)
Openalex Percentile: Top 11%
Geological formations and processes
3.34
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