scholarly journals Low-Frequency Elastic Properties of a Polymineralic Carbonate: Laboratory Measurement and Digital Rock Physics

2021 ◽  
Vol 9 ◽  
Author(s):  
Ken Ikeda ◽  
Shankar Subramaniyan ◽  
Beatriz Quintal ◽  
Eric James Goldfarb ◽  
Erik H. Saenger ◽  
...  
Keyword(s):  
Elastic Property ◽  
Elastic Properties ◽  
Low Frequency ◽  
Rock Physics ◽  
Ct Images ◽  
Homogenization Theory ◽  
Laboratory Measurements ◽  
Static Compression ◽  
Digital Rock Physics ◽  
Digital Rock

We demonstrate that the static elastic properties of a carbonate sample, comprised of dolomite and calcite, could be accurately predicted by Digital Rock Physics (DRP), a non-invasive testing method for simulating laboratory measurements. We present a state-of-the-art algorithm that uses X-ray Computed Tomography (CT) imagery to compute the elastic properties of a lacustrine rudstone sample. The high-resolution CT-images provide a digital sample that is used for analyzing microstructures and performing quasi-static compression numerical simulations. Here, we present the modified Segmentation-Less method withOut Targets method: a combination of segmentation-based and segmentation-less DRP. This new method assigns the spatial distribution of elastic properties of the sample based on homogenization theory and overcomes the monomineralic limitation of the previous work, allowing the algorithm to be used on polymineralic rocks. The method starts by partitioning CT-images of the sample into smaller sub-images, each of which contains only two phases: a mineral (calcite or dolomite) and air. Then, each sub-image is converted into elastic property arrays. Finally, the elastic property arrays from the sub-images are combined and fed into a finite element algorithm to compute the effective elastic properties of the sample. We compared the numerical results to the laboratory measurements of low-frequency elastic properties. We find that the Young’s moduli of both the dry and the fully saturated sample fall within 10% of the laboratory measurements. Our analysis also shows that segmentation-based DRP should be used cautiously to compute elastic properties of carbonate rocks similar to our sample.

scholarly journals Electrical Formation Factor of Clean Sand from Laboratory Measurements and Digital Rock Physics

2019 ◽  
Author(s):  
Mohammed Ali Garba ◽  
Stephanie Vialle ◽  
Mahyar Madadi ◽  
Boris Gurevich ◽  
Maxim Lebedev
Keyword(s):  
Rock Physics ◽  
Small Samples ◽  
Sand Sample ◽  
Laboratory Measurements ◽  
Micro Computed Tomography ◽  
Formation Factor ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Computed Tomography Images ◽  
Average Grain Size

Abstract. Electrical properties of rocks are important parameters for well-log and reservoir interpretation. Laboratory measurements of such properties are time-consuming, difficult, and are impossible in some cases. Being able to compute them from 3-D images of small samples will allow generating massive data in a short time, opening new avenues in applied and fundamental science. To become a reliable method, the accuracy of this technology needs to be tested. In this study, we developed a comprehensive and robust workflow with clean sand from two beaches. Electrical conductivities at 1 kHz were first carefully measured in the laboratory. A range of porosities spanning from a minimum of 0.26 to 0.33 to a maximum of 0.39 to 0.44, depending on the samples. Such range was achieved by compacting the samples in a way that reproduces natural packing of sand. Characteristic electrical formation factor versus porosity relationships were then obtain for each sand type. 3-D micro-computed tomography images of each sand sample from the experimental sand pack were acquired at different resolutions. Image processing was done using global thresholding method and up to 96 sub-samples of sizes from (200)3 to (700)3 voxels. After segmentation, the images were used to compute the effective electrical conductivity of the sub-cubes using a Finite Element electrostatic modelling. For the samples, a good agreement between laboratory measurements and computation from digital cores was found, if the sub-cube size REV is reached that is between (1300 μm)3 and (1820 μm)3, which, with an average grain size of 160 μm, is between 8 and 11 grains. Computed digital rock images of the clean sands have opened a way forward in getting the formation factor within a shortest possible time; laboratory calculations take five (5) to thirty-five (35) days as in the case of clean and shaly sands respectively, whereas, the digital tomography takes just three (3) to five (5) hours.

3D rock minerals by correlating XRM and automated mineralogy and its application to digital rock physics for elastic properties

Geophysics ◽  
2021 ◽  
pp. 1-76
Author(s):  
Jin Hao ◽  
Guoliang Li ◽  
Jiao Su ◽  
Yuan Yuan ◽  
Zhongming Du ◽  
...  
Keyword(s):  
High Resolution ◽  
Elastic Properties ◽  
Rock Physics ◽  
Large Field ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Mineral Phases ◽  
Rock Structure ◽  
Shale Sample ◽  
Automated Mineralogy

Digital rock physics (DRP) is an emerging technique that has rapidly become an indispensable tool to estimate elastic properties. The success of DRP mainly depends on three factors: acquiring a 3D rock structure image, accurately identifying 3D minerals, and using a proper numerical simulation method. Shales present a substantial challenge for DRP owing to their heterogeneous structure, composition, and properties from micron to centimeter scale. To obtain a sufficiently large field-of-view (FOV) image of a sample that reflects the detailed and representative internal structure and composition, we have developed a new DRP workflow to obtain large-FOV high-resolution digital rocks with 3D mineralogical information. Using the “divide-and-stitch” technique, a long shale sample is divided into several subunits, imaged separately by high-resolution X-ray microscopy (XRM), and then stitched to obtain a large-FOV 3D digital rock. An FOV of a rock cylinder (736 μm in diameter, 2358 μm in height, and 1 μm resolution) is used as an example. By correlating XRM and automated mineralogy, a large-FOV 3D mineral digital rock is obtained from a shale sample. Six mineral phases are identified and verified by automated mineralogy, and four laminae are detected according to the grain size, which offer a new perspective to study sedimentary processes and heterogeneities at the millimeter scale. The finite-difference method is used to compute the elastic properties of the large-FOV 3D mineral digital rock, and the results of Young’s modulus are within the limit of the Voigt/Reuss bounds. It also reveals that there is a difference in simulated elastic properties in the four laminae. The large-FOV 3D mineral digital rock offers the potential to explore the relationship between elastic properties and mineral phases, as well as the heterogeneities of elastic properties at the millimeter scale.

Digital rock physics and laboratory considerations on a high-porosity volcanic rock

2020 ◽  
Author(s):  
Laura L. Schepp ◽  
Benedikt Ahrens ◽  
Martin Balcewicz ◽  
Mandy Duda ◽  
Mathias Nehler ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Elastic Properties ◽  
Effective Properties ◽  
Rock Physics ◽  
Numerical Results ◽  
High Porosity ◽  
Effective Elastic Properties ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Laboratory Investigations

<p>Microtomographic imaging techniques and advanced numerical simulations are combined by digital rock physics (DRP) to obtain effective physical material properties. The numerical results are typically used to complement laboratory investigations with the aim to gain a deeper understanding of physical processes related to transport (e.g. permeability and thermal conductivity) and effective elastic properties (e.g. bulk and shear modulus). The present study focuses on DRP and laboratory techniques applied to a rock called reticulite, which is considered as an end-member material with respect to porosity, stiffness and brittleness of the skeleton. Classical laboratory investigations on effective properties, such as ultrasonic transmission measurements and uniaxial deformation experiments, are very difficult to perform on this class of high-porosity and brittle materials.</p><p>Reticulite is a pyroclastic rock formed during intense Hawaiian fountaining events. The open honeycombed network has a porosity of more than 80 % and consists of bubbles that are supported by glassy threads. The natural mineral has a strong analogy to fabricated open-cell foams. By comparing experimental with numerical results and theoretical estimates we demonstrate the potential of digital material methodology with respect to the investigation of porosity, effective elastic properties, thermal conductivity and permeability</p><p>We show that the digital rock physics workflow, previously applied to conventional rock types, yields reasonable results for a high-porosity rock and can be adopted for fabricated foam-like materials. Numerically determined effective properties of reticulite are in good agreement with the experimentally determined results. Depending on the fields of application, numerical methods as well as theoretical estimates can become reasonable alternatives to laboratory methods for high porous foam-like materials.</p>

Using digital rocks and simulations of pore-scale multiphysics to characterize a sandstone reservoir

2017 ◽  
Vol 5 (1) ◽  
pp. SB33-SB43
Author(s):  
Madhumita Sengupta ◽  
Mark G. Kittridge ◽  
Jean-Pierre Blangy
Keyword(s):  
Elastic Properties ◽  
Computational Methods ◽  
Laboratory Data ◽  
Rock Physics ◽  
Digital Rock Physics ◽  
Reservoir Rocks ◽  
Digital Rock ◽  
Physical Measurements ◽  
Reservoir Sandstones ◽  
Sandstone Reservoir

The modeling and prediction of transport and elastic properties for sandstones are critical steps in the exploration and appraisal of hydrocarbon reservoirs, particularly in deepwater settings where seismic data are abundant and well costs are high. Reliable multiphysics modeling of reservoir rocks requires robust models that respect the underlying geologic character and microstructure of the geomaterial and honor the measured properties. We have developed a case study that integrates traditional laboratory measurements with computational methods to quantify and relate physical properties of reservoir sandstones. We evaluate the complementary use of digital rock simulations as a practical technology that adds physical insight into the development and calibration of rock-property relationships. We also determine the challenges faced while applying digital rock physics to interpret laboratory data, and the steps taken to overcome those limitations. Combining physical and computational methods, we achieve an improved understanding of the link between geologic properties (sorting, microporosity) with transport (single-phase permeability, electrical conductivity) and elastic properties (moduli). Combining physical measurements with numerical computations has enhanced our understanding of multiphysics relationships in a heterogeneous sandstone reservoir.

scholarly journals Electrical formation factor of clean sand from laboratory measurements and digital rock physics

Solid Earth ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 1505-1517
Author(s):  
Mohammed Ali Garba ◽  
Stephanie Vialle ◽  
Mahyar Madadi ◽  
Boris Gurevich ◽  
Maxim Lebedev
Keyword(s):  
Rock Physics ◽  
Small Samples ◽  
Sand Sample ◽  
Laboratory Measurements ◽  
Formation Factor ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Average Grain Size ◽  
Short Time ◽  
Type 3

Abstract. Electrical properties of rocks are important parameters for well-log and reservoir interpretation. Laboratory measurements of such properties are time-consuming, difficult, and impossible in some cases. Being able to compute them from 3-D images of small samples will allow for the generation of a massive amount of data in a short time, opening new avenues in applied and fundamental science. To become a reliable method, the accuracy of this technology needs to be tested. In this study, we developed a comprehensive and robust workflow with clean sand from two beaches. Electrical conductivities at 1 kHz were first carefully measured in the laboratory. A range of porosities spanning from a minimum of 0.26–0.33 to a maximum of 0.39–0.44, depending on the samples, was obtained. Such a range was achieved by compacting the samples in a way that reproduces the natural packing of sand. Characteristic electrical formation factor versus porosity relationships were then obtained for each sand type. 3-D microcomputed tomography images of each sand sample from the experimental sand pack were acquired at different resolutions. Image processing was done using a global thresholding method and up to 96 subsamples of sizes from 2003 to 7003 voxels. After segmentation, the images were used to compute the effective electrical conductivity of the sub-cubes using finite-element electrostatic modelling. For the samples, a good agreement between laboratory measurements and computation from digital cores was found if a sub-cube size representative elemental volume (REV) was reached that is between 1300 and 1820 µm3, which, with an average grain size of 160 µm, is between 8 and 11 grains. Computed digital rock images of the clean sands have opened a way forward for obtaining the formation factor within the shortest possible time; laboratory calculations take 5 to 35 d as in the case of clean and shaly sands, respectively, whereas digital rock physics computation takes just 3 to 5 h.

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