Numerical Approach in Recognition of Selected Features of Rock Structure from Hybrid Hydrocarbon Reservoir Samples Based on Microtomography

Abstract

Abstract:The study employs numerical calculations in the characterization of reservoir sandstone samples based on high-resolution X-ray computed microtomography. The major goals were to determine porosity through pore size distribution, permeability characterization through pressure field, and structure impact on rock strength by simulation of a uniaxial compression test. Two Miocene samples were taken from well S-3, located in the eastern part of the Carpathian Foredeep. Due to the relation between sample size and image resolution, two X-ray irradiation series with two different sample sizes were performed. In the first approach, the voxel side was 27 µm and in the second it was up to 2 µm. Two samples from different depths have been studied here. Sample 1 has petrophysical features of conventional reservoir deposits, in contrast to sample 2. The approximate grain size of sample 1 is in the range 0.1-1.0 mm, whereas for sample 2 it is 0.01-0.1 mm with clear sedimentation lamination and heterogenic structure. The porosity, as determined by µCT, of sample 1 is twice (10.3%) that of sample 2 (5.3%). The equivalent diameter of a majority of pores is less than 0.027 mm and their pore size distribution is unimodal right-hand asymmetrical in the case of both samples. In relation to numerical permeability tests, the flow paths are in the few privileged directions where the pressure is uniformly decreasing. Nevertheless, there are visible connections in sample 1, as is confirmed by the homogenous distribution of particles in the pore space of the sample and demonstrated in the particle flow simulations. The estimated permeability of the first sample is approximately four times higher than that of the second one. The uniaxial compression test demonstrated the huge impact of even minimal heterogeneity of samples in terms of micropores: 4-5 times loss of strength compared to the undisturbed sample. The procedure presented shows the promising combination of microstructural analysis and numerical simulations. More specific calculations of lab tests with analysis of variable boundary conditions should be performed in the future.

Tortuosity of porous media: Image analysis and physical simulation

“…The popular image-based methods to calculate the geometrical tortuosity are listed in Table 1, including the direct shortest path searching method (DSPSM), the skeleton shortest path searching method (SSPSM), the fast marching method (FMM) and the pore centroid method (PCM), etc. Kaczmarek et al (2017).…”

“…Numerical simulation of thermal conduction was adopted to evaluate the diusional tortuosity of porous media (Cooper et al, 2013;Tjaden et al, 2016;Brown et al, 2016;Sun et al, 2016). Besides, the geometrical tortuosity is commonly used as an alternative to physical tortuosities to model transport properties of porous media (Montes et al, 2007;Sun et al, 2011;Cecen et al, 2012;Holzer et al, 2013;Berg, 2014;Kaczmarek et al, 2017;Li et al, 2017), such as permeability, eective diusivity, formation resistivity factor and thermal conductivity.…”

Petrophysical Analyses of Rock Construction Materials from a Roman Rural Settlement in Podšilo Bay on Rab Island (North-East Adriatic, Croatia)

“…X-ray computed microtomography (XµCT) was used to analyse the internal structure of six samples, employing a rotation technique for multi-viewpoint image acquisition [29,30]. After drying, six samples were analysed using Bruker microCT [Brucker Nano GmbH, Berlin, Germany] and Avizo Fire software (version 8.1) for qualitative descriptions and numerical visualizations.…”

Tortuosity of pore channels in tight rocks as a key parameter in fluid flow ability

“…Tortuosity has an enormous impact on rock ability to uid ow, so the idea of connecting the tortuosity with absolute permeability is signi cant (Javadpour 2009;Berg 2014;Kaczmarek et al 2017). Permeability is a challenging parameter, in both measurement and results interpretation (Soulaine et al 2016;Ghanizadeh et al 2017).…”