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Digital rock: How computer simulation can change the game for O&G companies

Several industrial applications depend on porous materials. For instance,  understanding how fluid permeates through material and how much fluid content can be retained or stored in the pores are important considerations when designing improved devices or  figuring out a system’s behavior  under different conditions. O&G operators depend on these analyses in order to develop better processes for oil and gas exploration and production. In addition, in today’s competitive industrial scene, insights like these can decrease costs and accelerate  project development.

Enter PORE, a new simulation software that is a modern alternative to traditional porous material characterization. PORE is especially effective for petroleum reservoir rocks and classical core analysis experiments. Its approach is computationally attractive—simpler and faster—with a sufficiently accurate topological representation of the rock porous structure.

The classical core analysis experiments can be easily simulated digitally, providing a replicable and non-destructive approach, since the material sample is not modified or subjected to experimental equipment and procedures. Moreover, analyses—experimental or by DNS—that would take days or weeks can be performed in just a few hours with digital rock technology.

What problems PORE can solve?

PORE provides estimates of petrophysical properties through digital rock technology, a modern simulation framework which brings together rock imaging and porous media flow modeling. Compared with traditional petrophysics methods that are based on laboratory experiments, digital rock techniques can speed up a property’s estimation to days instead of months!

Examples of potential applications:

  • Petrophysical properties of petroleum reservoir rocks
  • CO2 capture and storage (CCS) subsurface rocks
  • Coalbed methane gas storage and shale gas extraction
  • Battery and fuel cells
  • Cement and concrete microstructure analysis

The applications above require material analyses to obtain information about the porous space structure and how one or more fluids flow through such space. Intrinsic material properties like porosity and permeability provide grasps about the medium’s capability and its availability for fluid flow. 

Additionally, when more than one fluid is filling the porous space, the relative permeability of each fluid should be taken into account. This is the context where PORE can be a powerful tool. PORE performs such analyses with a modern digital framework using material images and pore network simulations, providing the following main results:

  • Total and effective porosity
  • Absolute and relative permeabilities
  • Residual/irreducible saturation of fluids
  • Capillary pressure estimates

Despite the wide range of potential applications, PORE is tailored especially for petroleum engineering uses, solving rock sample core analyses with the help of digital rock physics.

How does PORE work?

PORE is a digital rock physics software. Its main goal is to construct a digital representation of a porous material sample. This modern approach brings together imaging and pore network modeling (PNM). A rock sample (or any porous material) is imaged by micro-computed tomography (micro-CT), creating a stack of images. PORE reads the image stack, applies an image segmentation to binarize each image layer, and thus reconstructs the 3D image volume with porous space and solid matrix regions (see figure below, retrieved from [1]).

Binarized and reconstructed 3D image volume.
Figure 1: Binarized and reconstructed 3D image volume.

With the 3D reconstructed image volume, the pore network extraction is carried out based on the well-established Maximal Ball algorithm [2, 3]. Hence, a simplified yet accurate topological representation of the porous space is now given by Pore and Throats entities, as depicted in  Figure 2 below.

A pore network extracted from a 3D image.
Figure 2: A pore network extracted from a 3D image.

Even though Figure 2 is composed of “balls and sticks,” PORE represents Pore and Throats by prisms with generalized cross-sections [4, 5], selected according to the prism shape factor compared with the pore bodies’ shape factors identified in 3D by the Maximal Ball algorithm. Such a generalized approach allows to improve capillary effects and wettability representation in each pore body.  Furthermore, PORE is capable of generating multi-scale Pore Networks when two image stacks with different resolutions are available, i.e., coarse and fine scales, using an approach based on [6], as shown in Figure 3.

Two-scale Pore Network. The white and blue/red are the coarse and fine networks, respectively.
Figure 3: Two-scale Pore Network. The white and blue/red are the coarse and fine networks, respectively.

With the Pore Network properly configured, fluid flow is simulated through the Pore Network. A simplified approach is adopted to represent the flux of the fluids based on the analytical Hagen-Poiseuille solution and capillary pressure to fill the pores. The resulting system to be solved is smaller than the typical ones originated from direct numerical simulations (DNS), such as the finite volume method in 3D cases. The outcomes are the fluids’ saturations and pressure value for each pore.

The calculations of petrophysical properties are obtained from digital “versions” of classical experiments: mercury intrusion, drainage, and imbibition.

Final remarks

Although PORE is already available to customers, this software is under constant improvements. Future releases will include features such as the reactive transport through pore networks and rock dissolution effects.


[1] Plucenio, D. M., 2016. “Caracterização de rochas reservatório de petróleo a partir da modelagem do sistema poroso em rede de poros,” Masters Dissertation, Universidade Federal de Santa Catarina, Florianópolis.

[2] Dong, H., 2007. “Micro-CT Imaging and Pore Network Extraction,” PhD thesis, Imperial College, London.

[3] Al-Kharusi, A.S. & Blunt, M.J., 2008. “Multiphase flow predictions from carbonate pore space images using extracted network models,” Water Resources Research, 44(6).

[4] E Oren, Stig Bakke, Ole Jakob Arntzen, et al., 1998. “Extending predictive capabilities to network models.” In: SPE Journal 3.04, pp. 324–336

[5] Patzek, T.W., 2000, January. “Verification of a complete pore network simulator of drainage and imbibition.” In SPE/DOE Improved Oil Recovery Symposium. Society of Petroleum Engineers.[6] Jiang, Z., Van Dijke, M.I.J., Sorbie, K.S. and Couples, G.D., 2013. “Representation of multiscale heterogeneity via multiscale pore networks.” Water Resources Research, v. 49(9), pp. 5437-5449.

Diego Volpatto

Numerical Developer, ESSS

Diego Volpatto has a Bachelor's degree in Chemical Engineering from the Federal University of Rio Grande do Norte (UFRN), a Master's degree in Computational Modeling from National Laboratory for Scientific Computing (LNCC), and an on-going Doctoral degree at the same institution. Diego has been working at ESSS since 2018 as a Numerical Developer, implementing valuable simulation tools for the O&G industry, such as fluid phase equilibrium calculations, digital rock physics, model calibration, and uncertainty quantification.

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