The petroleum industry requires new technologies to improve the economics of exploration and production. Digital rock physics is a methodology that seeks to revolutionize reservoir characterization, an essential step in reservoir assessment, using computational methods. A combination of X-ray computed microtomography, digital pore network modeling, and 3D printing technology represents a novel workflow for transferring digital rock models into tangible samples that can be manufactured in a variety of materials and tested with standard laboratory equipment. Accurate replication of pore networks depends on the resolution of tomographic images, rock sample size, statistical algorithms for digital modeling, and the resolution of 3D printing. We performed this integrated approach on a sample of Idaho Gray Sandstone with an estimated porosity of 29% and permeability of 2200 mD. Tomographic images were collected at resolutions of 30 and $7\mathrm{\mu m}$ per voxel. This allowed the creation of digital porosity models segmented into grains and pores. Surfaces separating pores from grains were extracted from the digital rock volume and 3D printed in plastic as upscaled tangible models. Two model types, normal (with pores as voids) and inverse (with pores as solid), allowed visualization of the geometry of the grain matrix and topology of pores, while allowing characterization of pore connectivity. The current resolution of commodity 3D printers with a plastic filament ($30\mathrm{\mu m}$ for pore space and $16\mathrm{\mu m}$ for grain matrix) is too low to precisely reproduce the Idaho Gray Sandstone at its original scale. However, the workflow described here also applies to advanced high-resolution 3D printers, which have been becoming more affordable with time. In summary, with its scale flexibility and fast manufacturing time, 3D printing has the potential to become a powerful tool for reservoir characterization.

Three-dimensional (3-D) printing provides a fast, cost-effective way to produce and replicate complicated designs with minimal flaws and little material waste. Early use of 3-D printing for engineering applications in the petroleum industry has stimulated further adoption by geoscience researchers and educators. Recent progress in geoscience is signified by capabilities that translate digital rock models into 3-D printed rock proxies. With a variety of material and geometric scaling options, 3-D printing of near-identical rock proxies provides a method to conduct repeatable laboratory experiments without destroying natural rock samples. Rock proxy experiments can potentially validate numerical simulations and complement existing laboratory measurements on changes of rock properties over geologic time scales. A review of published research from academic, government, and industry contributions indicates a growing community of rock proxy experimentalists. Three-dimensional printing techniques are being applied to fundamental research in the areas of multiphase fluid flow and reactive transport, geomechanics, physical properties, geomorphology, and paleontology. Further opportunities for geoscience research are discussed. Applications in education include teaching models of terrains, fossils, and crystals. The integration of digital data sets with 3-D printed geomorphologies supports communication for both societal and technical objectives. Broad benefits that could be realized from centralized 3-D printing facilities are also discussed.

Three-dimensional (3-D) printing provides an opportunity to build lab-testable models of reservoir rocks from tomographic data. This study combines tomography and 3-D printing to reproduce a sample of the Fontainebleau sandstone at different magnifications to test how this workflow can help characterization of transport properties at multiple scales. For this sandstone, literature analysis has given a porosity of 11%, permeability of 455 md, mean pore throat radius of 15 μm, and a mean grain size of 250 μm. Digital rock analysis of tomographic data from the same sample yielded a porosity of 13%, a permeability of 251 md, and a mean pore throat radius of 15.2 μm. The 3-D printer available for this study was not able to reproduce the sample’s pore system at its original scale. Instead, models were 3-D printed at 5-fold, 10-fold, and 15-fold magnifications. Mercury porosimetry performed on these 3-D models revealed differences in porosity (28%–37%) compared to the literature (11%) and to digital calculations (12.7%). Mercury may have intruded the smallest matrix pores of the printing powder and led to a greater than 50% increase in measured porosity. However, the 3-D printed models’ pore throat size distribution (15 μm) and permeability (350–443 md) match both literature data and digital rock analysis. The powder-based 3-D printing method was only able to replicate parts of the pore system (permeability and pore throats) but not the pore bodies. Other 3-D printing methods, such as resin-based stereolithography and photopolymerization, may have the potential to reproduce reservoir rock porosity more accurately.

Understanding pore-scale flow and transport processes is important for understanding flow and transport within rocks on a larger scale. Flow experiments on small-scale micromodels can be used to experimentally investigate pore-scale flow. Current manufacturing methods of micromodels are costly and time consuming. 3D printing is an alternative method for the production of micromodels. We have been able to visualise small-scale, single-phase flow and transport processes within a 3D printed micromodel using a custom-built visualisation cell. Results have been compared with the same experiments run on a micromodel with the same geometry made from polymethyl methacrylate (PMMA, also known as Perspex). Numerical simulations of the experiments indicate that differences in experimental results between the 3D printed micromodel and the Perspex micromodel may be due to variability in print geometry and surface properties between the samples. 3D printing technology looks promising as a micromodel manufacturing method; however, further work is needed to improve the accuracy and quality of 3D printed models in terms of geometry and surface roughness.