Industrial applications of digital rock technology

Abstract

This article provides an overview of the current state of digital rock technology, with emphasis on industrial applications. We show how imaging and image analysis can be applied for rock typing and modeling of end-point saturations. Different methods to obtain a digital model of the pore space from pore scale images are presented, and the strengths and weaknesses of the different methods are discussed. We also show how imaging bridges the different subjects of geology, petrophysics and reservoir simulations, by being a common denominator for results in all these subjects. Network modeling is compared to direct simulations on grid models, and their respective strengths are discussed. Finally we present an example of digital rock technology applied to a sandstone oil reservoir. Results from digital rock modeling are compared to results from traditional laboratory experiments. We highlight the mutual benefits from conducting both traditional experiments and digital rock modeling.

arXiv comment36 pages, 18 figures

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• Re-examining Archie's law: Conductance description by tortuosity and constriction
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Cited by in corpus (5)

• Driving Digital Rock towards Machine Learning: predicting permeability with Gradient Boosting and Deep Neural Networks
• Deep-Learning Driven Noise Reduction for Reduced Flux Computed Tomography
• Conditioning of three-dimensional generative adversarial networks for pore and reservoir-scale models
• Reconstruction of 3D Porous Media From 2D Slices
• Lattice Boltzmann Models for Micro-tomographic Pore-spaces