scholarly journals Modeling of 3D Rock Porous Media by Combining X-Ray CT and Markov Chain Monte Carlo

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Wei Lin ◽  
Xizhe Li ◽  
Zhengming Yang ◽  
Shengchun Xiong ◽  
Yutian Luo ◽  
...  

Abstract Rocks contain multi-scale pore structures, with dimensions ranging from nano- to sample-scale, the inherent tradeoff between imaging resolution and sample size limits the simultaneous characterization of macro-pores and micro-pores using single-resolution imaging. Here, we developed a new hybrid digital rock modeling approach to cope with this open challenge. We first used micron-CT to construct the 3D macro-pore digital rock of tight sandstone, then performed high-resolution SEM on the three orthogonal surfaces of sandstone sample, thus reconstructed the 3D micro-pore digital rock by Markov chain Monte Carlo (MCMC) method; finally, we superimposed the macro-pore and micro-pore digital rocks to achieve the integrated digital rock. Maximal ball algorithm was used to extract pore-network parameters of digital rocks, and numerical simulations were completed with Lattice-Boltzmann method (LBM). The results indicate that the integrated digital rock has anisotropy and good connectivity comparable with the real rock, and porosity, pore-throat parameters and intrinsic permeability from simulations agree well with the values acquired from experiments. In addition, the proposed approach improves the accuracy and scale of digital rock modeling and can deal with heterogeneous porous media with multi-scale pore-throat system.

Geophysics ◽  
2012 ◽  
Vol 77 (2) ◽  
pp. E159-E170 ◽  
Author(s):  
John Keery ◽  
Andrew Binley ◽  
Ahmed Elshenawy ◽  
Jeremy Clifford

There is growing interest in the link between electrical polarization and physical properties of geologic porous media. In particular, spectral characteristics may be controlled by the same pore geometric properties that influence fluid permeability of such media. Various models have been proposed to describe the spectral-induced-polarization (SIP) response of permeable rocks, and the links between these models and hydraulic properties have been explored, albeit empirically. Computation of the uncertainties in the parameters of such electrical models is essential for effective use of these relationships. The formulation of an electrical dispersion model in terms of a distribution of relaxation times and associated chargeabilities has been demonstrated to be an effective generalized approach; however, thus far, such an approach has only been considered in a deterministic framework. Here, we formulate a spectral model based on a distribution of polarizations. By using a simple polynomial descriptor of such a distribution, we are able to cast the model in a stochastic manner and solve it using a Markov-chain Monte Carlo (McMC) sampler, thus allowing the computation of model-parameter uncertainties. We apply the model to synthetic data and demonstrate that the stochastic method can provide posterior distributions of model parameters with narrow bounds around the true values when little or no noise is added to the synthetic data, with posterior distributions that broaden with increasing noise. We also apply our model to experimental measurements of six sandstone samples and compare physical properties of a number of samples of porous media with stochastic estimates of characteristic relaxation times. We demonstrate the utility of our method on electrical spectra with different response characteristics and show that a single metric of relaxation time for the SIP response is not sufficient to provide clear insight into the physical characteristics of a sample.


1994 ◽  
Author(s):  
Alan E. Gelfand ◽  
Sujit K. Sahu

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