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Workflow Development to Scale up Petrophysical Properties from Digital Rock Physics Scale to Laboratory Scale

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Abstract

Petrophysical rock properties are the crucial point of any reservoir characterization project and represent fundamental input parameters for any simulation. To obtain reservoir characterization data such as porosity, absolute and relative permeabilities, typically core analysis tests are needed. Unfortunately, there are cases where these tests cannot be accomplished. In these situations, digital rock physics (DRP) techniques are useful and may represent a powerful approach to obtain these parameters. Fluid flow at the pore scale can be simulated by DRP. To compare DRP results (micrometric scale) and laboratory tests (centimetric scale), the implementation of an upscaling method is required. In this context, this work aims to propose a novel methodology to allow the digital characterization of rock properties at the plug scale. In particular, the developed workflow exploits and combines different technologies: micro-CT scan, advanced image processing, machine learning, CFD numerical simulation. The first step of the methodology consists of acquiring micro-CT low-resolution scan of the entire core plug; then, machine learning techniques are applied to decompose the digital plug (derived by image processing on micro-CT scan) in reference element of volume (REV)-type equivalent blocks, determining the optimum number of REV type and their locations. One or several high-resolution 3D fine-scale images are used to derive the petrophysical properties of each REV type from individual fluid flow simulations at the pore scale. The resulting REV-type properties are then scaled up to the core plug scale. Finally, the scaled up results are compared to the results of core analysis tests. The overall methodology is validated on a heterogeneous carbonate rock.

Article Highlights

  • Development of a new method for the absolute permeability upscaling from pore to Darcy scale.

  • Imaging and Machine learning processes allow to cluster similar rock fabrics correspondent to petrophysical clusters.

  • Flexible workflow implementation in terms of rock types adaptation and relative permeability evaluation.

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Acknowledgements

We are grateful to Francesca Micheli for her precious reviews. We are greatly thankful to ENI Laboratory for image acquisitions, Bona Nicola for the paper reviews, Mauro Primo Rossi for the help with Avizo ®software and Eni S.P.A. for permission to publish this paper. The authors are also very grateful to the three anonymous reviewers who improved the first draft of the manuscript.

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  1. Eni S.p.A., Via Emilia 1, 20097, San Donato Milanese, Milano, Italy

    Marco Miarelli

  2. Department of Energy, Politecnico di Milano, via Lambruschini 4, 20156, Milano, Italy

    Augusto Della Torre

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Miarelli, M., Della Torre, A. Workflow Development to Scale up Petrophysical Properties from Digital Rock Physics Scale to Laboratory Scale. Transp Porous Med 140, 459–492 (2021). https://doi.org/10.1007/s11242-021-01687-y

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