The Core Sample and Its Commercial Limitations
Reservoir characterisation has depended on the physical analysis of rock core samples extracted during drilling for as long as the oil and gas industry has sought to understand the subsurface formations that contain its production targets. A core sample, typically a cylindrical section of rock thirty centimetres in diameter and up to ninety metres in length extracted from a target formation during drilling, provides the physical material whose laboratory analysis determines the porosity, permeability, wettability, and fluid saturation properties that reservoir engineers need to predict how a formation will produce under different development scenarios. The physical measurements performed on core samples, including mercury injection capillary pressure testing, gas permeability measurement, nuclear magnetic resonance analysis, and thin section petrographic examination under optical microscopy, are the conventional rock physics inputs that reservoir simulation models use to predict field performance. These measurements are accurate, well-validated against field production data, and regarded as the authoritative source of rock property data for reservoir characterisation. They are also slow, expensive, destructive of the core sample, and limited to the specific samples that were extracted during drilling, which represent a tiny and potentially unrepresentative fraction of the total formation volume whose properties the measurements are meant to characterise.
The commercial cost of conventional core analysis reflects both the laboratory time required for the measurements and the drilling decision economics whose tight timing windows create pressure on core analysis that the laboratory turnaround of weeks to months cannot always accommodate. A development well drilling programme whose completion design depends on core analysis data that arrives after the completion has already been installed cannot benefit from the core data in the way that the upstream investment in core extraction was intended to support. Digital rock physics addresses this timing problem by dramatically compressing the time from core extraction to quantitative rock property data through the use of high-resolution CT scanning and computational simulation that can generate the pore-scale physics models used to compute rock properties in hours rather than weeks.
CT Scanning and the Digital Core
High-resolution X-ray computed tomography scanning of rock core samples creates three-dimensional images of the pore network geometry that determines the rock's physical properties at resolutions down to the micrometre scale. The CT image reveals the pore size distribution, pore connectivity, grain geometry, and mineral distribution that govern how fluids flow through the rock and how the rock responds to changes in effective stress and fluid saturation. From the three-dimensional CT image, computational fluid dynamics simulations using lattice Boltzmann methods or finite element flow solvers calculate the absolute permeability, relative permeability to oil and water, and capillary pressure curves that reservoir engineers need without performing any physical fluid flow experiment on the core sample. The computed rock properties can be calculated faster, at lower cost, and for a larger number of sample locations along the core than physical laboratory measurements could practically provide, because the CT scanning is non-destructive and the computation is repeatable on the same digital dataset at different simulated reservoir conditions without consuming any physical material.
The validation of computed rock properties against conventional laboratory measurements is the scientific foundation whose robustness determines whether digital rock physics can substitute for rather than merely supplement physical core analysis in reservoir characterisation workflows. The comparison of lattice Boltzmann-computed permeability values with gas permeability measurements on the same core plugs, across the range of formation types and permeability values that reservoir characterisation encounters in different geological settings, has accumulated a body of evidence that supports the use of digital rock physics for primary rock property determination in many formation types where the pore scale that CT imaging resolves is the dominant control on permeability. The formation types where digital rock physics computation is least reliable are those where the pore network geometry contains features at multiple length scales whose combined contribution to permeability requires imaging at resolutions that current CT technology cannot achieve across a representative sample volume simultaneously.
Workflow Integration and the Operational Impact
The commercial value of digital rock physics in oil and gas operations extends beyond the acceleration of core analysis turnaround to the integration of digital core data into real-time drilling and completion decision workflows that physical core analysis cannot support at the timescales that operational decision-making requires. A drilling programme that delivers CT-scanned core data and preliminary computed permeability profiles within twenty-four hours of core extraction can use that data to guide perforation design, stimulation intensity decisions, and completion staging in ways that weeks-delayed physical core analysis cannot influence. The integration of digital rock physics with logging-while-drilling data and seismic attribute analysis through machine learning models that predict rock properties from indirect measurements calibrated against digital core analysis creates the reservoir characterisation workflow that reduces dependence on the sparse direct measurements that core extraction can practically provide across the formation volume of interest.
Top 10 Companies in Digital Rock Physics Globally
- FEI (Thermo Fisher Scientific): CT scanning and electron microscopy equipment manufacturer whose Helios and Avizo digital rock physics workflow software are the imaging and analysis tools most widely used in commercial digital rock physics; its hardware and software integration creates the end-to-end digital core analysis workflow that service companies and operator rock physics laboratories use.
- Ingrain (Halliburton): Digital rock physics service company acquired by Halliburton whose micro-CT scanning and lattice Boltzmann simulation capabilities are integrated into Halliburton's reservoir characterisation service portfolio; its large library of digital core datasets and its operator relationships create the commercial depth that an independent digital rock physics company cannot achieve outside the major oilfield service company structure.
- SLB: Oilfield services company with digital rock physics capabilities integrated into its PETREL reservoir modelling platform; its combination of core analysis services, petrophysical interpretation, and reservoir simulation creates the integrated subsurface characterisation workflow that operator companies use to connect digital core data to field-scale production predictions.
- Numerical Rocks: Norwegian digital rock physics company providing pore-scale simulation services to oil and gas operators; its academic heritage from Norwegian petroleum research and its specialisation in carbonates and tight sandstones create the geological expertise that digital rock physics computation requires beyond the image processing and fluid simulation software capabilities.
- Petrolia Energy: Digital rock technology company providing automated CT scanning and pore-scale flow simulation services; its focus on rapid turnaround digital core analysis for completion design optimisation creates the operational workflow integration that well construction decision timescales require.
- iRock Technologies: Chinese digital rock physics company providing micro-CT scanning and computational rock physics for Chinese domestic oil and gas operators; its domestic Chinese market focus and its reservoir characterisation services for tight gas and unconventional formations create the digital rock physics capability that Chinese operators are deploying in their most technically challenging production environments.
- Delft University of Technology: Academic digital rock physics research group whose lattice Boltzmann simulation codes and validation datasets are the foundational research that commercial digital rock physics services build their computational methods on; its collaboration with Shell, Equinor, and other operators creates the industry-academic research partnership that keeps commercial digital rock physics methods at the frontier of computational capability.
- RGL Reservoir Management: Reservoir management company integrating digital rock physics with production data analytics for enhanced oil recovery optimisation; its data-driven reservoir management approach that combines digital core properties with production history creates the field-scale application of digital rock physics that well-level pore-scale simulation alone cannot provide.
- Digital Rocks Portal (UT Austin): Open-access digital rock data repository providing CT image datasets and pore-scale simulation results for research and commercial validation; its role as the industry reference dataset collection for validating digital rock physics methods creates the neutral benchmark that both commercial service providers and operator rock physics teams use to assess the accuracy of new computational approaches.
- CGG GeoSoftware: Geoscience software company with digital rock and petrophysical modelling capabilities integrated into its reservoir characterisation software suite; its JASON petrophysical modelling platform and its rock physics template analysis tools create the bridge between digital core measurements and the seismic-scale rock physics models that exploration and development geophysics requires.