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.

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.

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 Construction of pore structure and lithology of digital rock physics based on laboratory experiments

2021 ◽  
Vol 11 (5) ◽  
pp. 2113-2125
Author(s):  
Chenzhi Huang ◽  
Xingde Zhang ◽  
Shuang Liu ◽  
Nianyin Li ◽  
Jia Kang ◽  
...  
Keyword(s):  
Pore Structure ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Laboratory Experiments ◽  
Rock Physics ◽  
Reconstruction Method ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
The Core

AbstractThe development and stimulation of oil and gas fields are inseparable from the experimental analysis of reservoir rocks. Large number of experiments, poor reservoir properties and thin reservoir thickness will lead to insufficient number of cores, which restricts the experimental evaluation effect of cores. Digital rock physics (DRP) can solve these problems well. This paper presents a rapid, simple, and practical method to establish the pore structure and lithology of DRP based on laboratory experiments. First, a core is scanned by computed tomography (CT) scanning technology, and filtering back-projection reconstruction method is used to test the core visualization. Subsequently, three-dimensional median filtering technology is used to eliminate noise signals after scanning, and the maximum interclass variance method is used to segment the rock skeleton and pore. Based on X-ray diffraction technology, the distribution of minerals in the rock core is studied by combining the processed CT scan data. The core pore size distribution is analyzed by the mercury intrusion method, and the core pore size distribution with spatial correlation is constructed by the kriging interpolation method. Based on the analysis of the core particle-size distribution by the screening method, the shape of the rock particle is assumed to be a more practical irregular polyhedron; considering this shape and the mineral distribution, the DRP pore structure and lithology are finally established. The DRP porosity calculated by MATLAB software is 32.4%, and the core porosity measured in a nuclear magnetic resonance experiment is 29.9%; thus, the accuracy of the model is validated. Further, the method of simulating the process of physical and chemical changes by using the digital core is proposed for further study.

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