Rock and fluid analysis services in the laboratory and at the wellsite
Petricore is the pioneer of digital rock technology, and through decades of continuous research and development, we stand at the forefront of delivering quality digital rock analysis.
By providing unique SCAL programs, that combine laboratory and digital rock analysis as complementary solutions, Petricore is offering the next generation core analysis.
Scanning Electron Microscope (SEM) images allow us to make a detailed characterization of the material surfaces with a focused beam of electrons. Different imaging techniques give qualitative and quantitative descriptions of:
Micro-CT is used to characterize the 3-dimensional structures at the micrometer scale. This technology allows our clients to make a detailed characterization of plugs, which together with our Digital Rock Analysis tools allow us to calculate petrophysical properties as well as SCAL properties. These images technology allow us to quantify the effect of the pore-scale structure in global properties (e.g., micro fractures, small vugs, clay contents, anomalies). Micro-CT imaging can be applied to a wide range of core materials (cores, core plugs, unconsolidated samples, core fragments, drill cuttings) to facilitate advanced rock characterization for wells where conventional core plugs are not available.
Dual Energy CT provides a detailed 3-dimensional volume of the scanned core, which is used to obtain logs showing bulk density, porosity, and lithology variations. Special clustering techniques allow us to convert this information into different lithotypes. Dual-energy scanning can also be used in fluid flow visualization studies. These interesting qualitative and quantitative results can improve the understanding of complex rocks, especially carbonates.
Applications of DECT include subsample selection, direct high-resolution density and atomic number images, porosity, lithotypes, etc.
Advanced image processing tools are applied to transform a greyscale image, such as a micro-CT scan, into a labeled model which facilitates calculation of rock properties. Artificial intelligence (AI) is implemented to maximize the value of digital images, from increasing the image resolution through accurate segmentation of pores and minerals. Images of different modalities (2D-3D) and different states (3D-3D) can be spatially registered to extend the information derived from digital images. 2D to 3D registration is typically SEM images registered to micro-CT volumes for increased image resolution, while 3D to 3D registration allows for generating difference images (3D porosity maps) from micro-CT images acquired with and without a contrast agent in the pore space.
Petricore’s suite of digital rock solutions covers a complete characterization of the reservoir rock based on a digital model of the internal structure of the rock, constructed from digital image. These solutions include digital SCAL properties like capillary pressure and relative permeability and require only small fragments of rock.
Petricore’s digital rock analysis is validated and benchmarked, and the pioneering development of the technology continues through research projects co-funded by the leading oil and gas operators in the industry.
Petrophysical properties are calculated in X, Y and Z-direction both on the complete 3D model and for non-overlapping sub-volumes of various sizes. The sub-volume calculations provide a heterogeneity analysis of the sample for better understanding of cross-property relationships.
Multiphase fluid flow is simulated on the extracted pore network model. Primary drainage, imbibition, and secondary drainage displacements are simulated to provide accurate data across the complete saturation range. The numerical simulations have been benchmarked and validated for a wide range of lithologies and rock types to ensure the pore scale physics and transport mechanisms are accurately replicated in the digital models.
Advanced fluid flow experiments are often time-consuming and technically challenging to conduct correctly. The speed and accuracy of numerical simulations allow for the inclusion of sensitivity studies as a standard in formation evaluation programs. Sensitivity to Swi for characterizing flow behavior and trapping in transition zones are, together with wettability sensitivity studies, highly regarded tools for reducing uncertainties in formation evaluation.
The multi-scale pore network is extracted based on the 3D porosity map generated by micro-CT images. Resolved pores as characterized directly, while micro-porous phases are classified as various rock types subject to high-resolution imaging and modeling. The multi-scale pore network integrates all rock types into one global model, which is used for calculation of petrophysical properties and multiphase simulations. This technology allows for more representative models as the volumes are larger, as well as the possibility of characterizing more difficult rock types with the integration of models of the micro-structures.
Generation of representative 3D models from 2D SEM images allows for characterization of micro-structures below the image resolution of micro-CT images. In-house algorithms apply artificial intelligence to ensure the generated pore space is correctly replicating the volumetric and topological characteristics of the physical rock. The reconstructed 3D models are used to calculate petrophysical properties and SCAL parameters, which are integrated into multiscale pore network models to obtain complete characterization of reservoir rocks with wide pore size distributions.
Hybrid laboratory/digital SCAL studies take advantage of both disciplines to derive rock properties with high accuracy, while still shortening the time for final deliverables. By constraining or anchoring multiscale DRA to more easily-to-obtain experimental data, DRA simulations are used to calculate much more costly-to-measure and time-consuming parameters such as the imbibition relative permeability curve.
Petricore is the only provider that conducts this advanced solution in-house, developing the next generation core analysis.