Pore Network Analysis of Brae Formation Sandstone, North Sea. / Thomson, Paul-Ross; Jefferd, Mark; Clark, Brett; Chiarella, Domenico; Mitchell, Tom; Hier-Majumder, Saswata.

In: Marine and Petroleum Geology, Vol. 122, 104614, 12.2020.

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### Abstract

In this work, we apply digital rock physics (DRP) to characterize the pore networks of the Brae Formation sandstones from two different wells in the Miller field area (North Sea, UK). Using X-ray micro-CT scans, we calculate the porosity and permeability and generate pore network models to assess pore shape characteristics. The porous samples are marked by macroporosities ranging from 4.9% to 15.2% with the effective porosities varying from 0 to 14.8%. The samples also contained some microporosity hosted in secondary and accessory mineral phases, varying between 2.6% to 10.7%. Pore network model results for total porosity indicate that the samples have median pore and throat radii ranging from 5.5 µm to 16.8 µm and 6.4 µm to 12.9 µm, respectively. The throat length of all samples has a median value ranging between 36.3 µm and 82.4 µm. The ratio between effective porosity and total porosity ($\phi^\ast$) varies with total porosity ($\phi$) following the exponential relation φ* = 0.98 - e^{-(φi-0.032)/0.028}. Pore network connectivity is established at a porosity of 3% and full communication is achieved at porosities exceeding 10%. Permeability was found to vary with total porosity with an exponent of 3.67. Based on these observations and the results from our models, the connectivity of the pore network has important implications for predicting reservoir performance during large scale subsurface projects such as hydrocarbon production and CO2 storage.
Original language English 104614 11 Marine and Petroleum Geology 122 22 Aug 2020 https://doi.org/10.1016/j.marpetgeo.2020.104614 Published - Dec 2020

• ## NERC Oil & Gas CDT 2016 cohort

Project: Other

• ## Three dimensional modeling of dynamic microstructure

Project: Research

This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 34314810