31 May 2021 to 4 June 2021
Europe/Berlin timezone

Multi-phase flow parameters for unconsolidated reservoirs using digital rock physics

1 Jun 2021, 20:00
1h
Poster (+) Presentation (MS9) Pore-scale modelling Poster +

Speaker

Pit Arnold

Description

Advances in technology and computational power have led to an increased impact of digital rock physics, i.e., simulations on the rock’s pore space obtained from computer tomographic imaging. Various processes can be simulated either directly on the obtained structure or on abstracted networks in order to obtain rock and fluid properties such as relative permeability and capillary pressure saturation functions. Typically, simulation results are corroborated with experimental data obtained from routine and special core analysis programs. Compared with experiments, simulations take only a fraction of the time to perform, allowing for additional sensitivity studies with respect to, e.g., fluid configurations. In case of unconsolidated reservoirs, however, there are often no structurally intact samples available. Even if samples are available, their usage in core analysis programs is rather limited and creating subsamples for micro-CT imaging has proved to be challenging. Therefore, the information available might be limited to grain size distributions from sieving analysis, porosity measurements and MICP data. In this study, we generate digital rock models based on grain-size distributions in order to simulate relative permeability and capillary pressure saturation functions. We match the models in the frame of the available experimental data to MICP curves by varying grain sizes, shapes and grain orientation, while keeping the systems’ porosity and grain size bins as boundary criteria. Our results show a high sensitivity to grain shapes rather than sizes. Subsequently, we calculate relative permeability functions based on our matched digital models.
In the present cases, Digital Rock Physics on basis of synthetic rock models may be the only source of multiphase-flow parameters. Their variation with a reasonable range in wettability assumptions serve as starting point for stochastic reservoir modeling.

Time Block Preference Time Block B (14:00-17:00 CET)
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Primary authors

Pit Arnold Mr Alexandru Badescu (Montanuniversität Leoben) Dr Hendrik Rohler (OMV Petrom) Holger Ott (Montanuniversität Leoben)

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