Challenges and Prospects of Digital Core-Reconstruction Research

Abstract

The simulation of various rock properties based on three-dimensional digital cores plays an increasingly important role in oil and gas exploration and development. The accuracy of 3D digital core reconstruction is important for determining rock properties. In this paper, existing 3D digital core-reconstruction methods are divided into two categories: 3D digital cores based on physical experiments and 3D digital core stochastic reconstructions based on two-dimensional (2D) slices. Additionally, 2D slice-based digital core stochastic reconstruction techniques are classified into four types: a stochastic reconstruction method based on 2D slice mathematical-feature statistical constraints, a stochastic reconstruction method based on statistical constraints that are related to 2D slice morphological characteristics, a physics process-based stochastic reconstruction method, and a hybrid stochastic reconstruction method. The progress related to these various stochastic reconstruction methods, the characteristics of constructed 3D digital cores, and the potential of these methods are analysed and discussed in detail. Finally, reasonable prospects are presented based on the current state of this research area. Currently, studies on digital core reconstruction, especially for the 3D digital core stochastic reconstruction method based on 2D slices, are still very rough, and much room for improvement remains. In particular, we emphasize the importance of evaluating functions, multiscale 3D digital cores, multicomponent 3D digital cores, and disciplinary intersection methods in the 3D construction of digital cores. These four directions should provide focus, alongside challenges, for this research area in the future. This review provides important insights into 3D digital core reconstruction.

Comparative analysis on pore‐scale permeability prediction on micro‐CT images of rock using numerical and empirical approaches

“…Thus, extraction and reconstruction of rock structure from natural rock specimens for petrophysics computation are valuable and have been regarded as an efficient approach to handle those issues. Then, digital rock petrophysics (DRP) has been adopted to obtain those macroscopic properties of rock including strength and permeability, as well as acoustic, electrical, and thermal properties, by simulating the physical process on these reconstructed models . The most widely used DRP approaches of permeability prediction based on CT images are including pore network modeling, Lattice Boltzmann method, and image voxel‐based direct N‐S solver …”

Comparison of various 3D pore space reconstruction methods and implications on transport properties of nanoporous rocks

“…They can be classified between two types: object-based and pixel-based methods. A short survey of these methods is detailed below but we refer the reader to the recent review papers of Tahmasebi [2018] or Zhu et al [2019] for a more comprehensive overview on the advantages and disadvantages of each approach.…”

“…), image segmentation (loss of pores during identification) or from the reconstruction method itself and need to be managed. These artifacts are manifested in different ways, including curtaining effect, disconnected pores or intensity variation and an appropriate advanced image processing has to be applied to mitigate them [Salzer et al, 2015, Zhu et al, 2019. For instance, isolated pores or solid voxels are often generated when using MPS approaches, and even more with SIS.…”

Nature-Inspired Optimization Algorithms for the 3D Reconstruction of Porous Media

“…Alternatively, the 3D material structure can be derived by applying a computational reconstruction technique that uses a single 2D image of the material that is acquired using conventional imaging equipment [4]. The first reconstruction method was proposed quite early by Quiblier [5] in the years when imaging systems were limited and displayed marginal performance.…”