Innovative characterization of tight sandstones from Paleozoic basins in Poland using X-ray computed tomography supported by nuclear magnetic resonance and mercury porosimetry

Krakowska, P.; Puskarczyk, Edyta; Jędrychowski, Mariusz; Habrat, Magdalena; Madejski, Paweł; Dohnalik, M.

doi:10.1016/j.petrol.2018.03.052

Cited by 30 publications

(15 citation statements)

References 28 publications

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“…Segmentation was done by threshold method, using a single threshold value determined by the choice of the interpreter, comparing the results of total porosity from CT with the results from the other laboratory techniques, such as FIB-SEM (Focused Ion Beam-Scanning Electron Microscope), helium pycnometry (HeP). Interpretation of the CT images was done using poROSE (poROus materials examination SoftwarE) computer system, developed at the AGH UST, FGGEP, Department of Geophysics [27][28][29].…”

Section: Methodsmentioning

confidence: 99%

Diverse Scale Data for Shale Gas Formation Description—Why Is Digital Shale Rock Model Construction Difficult? The Polish Silurian and Ordovician Rocks Case Study

Krakowska-Madejska

Jarzyna

2020

Minerals

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The aim of the study was to show that the petrophysical parameters, characterizing the shale gas formation, obtained from the various scale well logging and laboratory methods, correlated among themselves. Relationships determined on the basis of mesoscale (logs) and microscale outcomes (laboratory experiments on plugs or crumbs) were also recognizable in nanoscale in the computed tomography results. Selected logs (spectral gamma ray, resistivity, density, neutron, geochemical and acoustic logs) and laboratory methods turned out to be effective in rock typing and description of petrophysical parameters. Nanoscale results processing and interpretation was supported by the sophisticated special software poROSE (version 3.18, AGH University of Science and Technology, Kraków, Poland) to determine special parameters, which correlated with the standard laboratory outcomes. Results of the mercury injection porosimetry, together with adsorption/desorption of nitrogen at 77 K and pressure decay permeability, were used as the basal parameters for building a digital model of shale rock and a detailed description of the Silurian and Ordovician shale formation, treated as the hydrocarbon prospective unconventional reservoirs. Including the computed X-ray tomography results in the correlation analyses, gave the platform to extend the standard 2D approach in building the rock model to novel, 3D and more detailed presentations of rock characteristics.

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Section: Methodsmentioning

confidence: 99%

Diverse Scale Data for Shale Gas Formation Description—Why Is Digital Shale Rock Model Construction Difficult? The Polish Silurian and Ordovician Rocks Case Study

Krakowska-Madejska

Jarzyna

2020

Minerals

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“…Highly specialized algorithms are necessary to obtain the proper visualization and quantitative information from objects. Firstly, CT data were processed (Feldkamp et al 1984;Jędrychowski et al 2017) and next analyzed in newly developed software poROSE Krakowska et al 2018), in which many geometrical parameters were implemented for the proper 3D analysis of porous materials. poROSE software contains algorithms, which allow to parametrize the selected objects, e.g., pores, microcracks or minerals, and were built upon basis of the knowledge from different disciplines, as material engineering, medicine, petroleum geology and petrophysics ).…”

Section: Methodsmentioning

confidence: 99%

Detailed parametrization of the pore space in tight clastic rocks from Poland based on laboratory measurement results

Krakowska

2019

Acta Geophys.

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Computed X-ray tomography (CT), together with nuclear magnetic resonance spectroscopy, pulse-and pressure-decay permeability methods, is a source of comprehensive information about the geometrical parameters of the pore space. Geological material consists of 31 samples of tight, gas-bearing, clastic rocks from different wells and formations. The purpose was to parametrize in detail the pore structure, revealing the relationships between the various parameters and estimating the equation for assessing the fluid flow ability of analyzed tight rocks. Following parameters were taken into consideration in the pore space characterization: thickness mean, equivalent diameter, anisotropy, elongation, sphericity, Feret diameter, Feret coefficient, Feret shape; shape factors: 2nd circularity coefficient, Malinowska coefficient and Danielsson coefficient; as well as parameters from 3D skeleton analysis: junctions, branches, coordination number. It was captured the dependence of logarithmic T2 mean from NMR on junction count from CT, as well as T2 cutoff from NMR on elongation from CT for the all samples. Logarithm of absolute permeability was estimated based on multiple linear regression analysis using only geometrical parameters from X-ray nanotomography, which is a benefit in the times of coring material decrease.

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“…Region labelling is a standard segmentation problem in two-dimensional (2D) and three-dimensional (3D) image processing, in which groups of pixels that form contiguous domains are identified and each discrete domain is given a unique label [ 1 ]. Region labelling is needed across disciplines, for example, to identify pores in sintered polymers [ 2 ], soil [ 3 ], rock [ 4 , 5 ], cement [ 6 ], noodle dough [ 7 ], teeth [ 8 ] or bone [ 9 ], from images obtained by modalities such as X-ray microtomography (XMT), confocal microscopy or serial sectioning microscopy. It is also useful to perform region labelling to remove small particles from images prior to calculating the Euler characteristic of a connected structure, for example, to calculate trabecular bone's connectivity density (Conn.D), a measure of the number of trabecular struts [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Multithreaded two-pass connected components labelling and particle analysis in ImageJ

Doube

2021

R. Soc. open sci.

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Sequential region labelling, also known as connected components labelling, is a standard image segmentation problem that joins contiguous foreground pixels into blobs. Despite its long development history and widespread use across diverse domains such as bone biology, materials science and geology, connected components labelling can still form a bottleneck in image processing pipelines. Here, I describe a multithreaded implementation of classical two-pass sequential region labelling and introduce an efficient collision resolution step, ‘ bucket fountain’ . Code was validated on test images and against commercial software (Avizo). It was performance tested on images from 2 MB (161 particles) to 6.5 GB (437 508 particles) to determine whether theoretical linear scaling ( O (n)) had been achieved, and on 1–40 CPU threads to measure speed improvements due to multithreading. The new implementation achieves linear scaling ( b = 0.905–1.052, time ∝ pixels b ; R 2 = 0.985–0.996), which improves with increasing thread number up to 8–16 threads, suggesting that it is memory bandwidth limited. This new implementation of sequential region labelling reduces the time required from hours to a few tens of seconds for images of several GB, and is limited only by hardware scale. It is available open source and free of charge in BoneJ.

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Innovative characterization of tight sandstones from Paleozoic basins in Poland using X-ray computed tomography supported by nuclear magnetic resonance and mercury porosimetry

Cited by 30 publications

References 28 publications

Diverse Scale Data for Shale Gas Formation Description—Why Is Digital Shale Rock Model Construction Difficult? The Polish Silurian and Ordovician Rocks Case Study

Diverse Scale Data for Shale Gas Formation Description—Why Is Digital Shale Rock Model Construction Difficult? The Polish Silurian and Ordovician Rocks Case Study

Detailed parametrization of the pore space in tight clastic rocks from Poland based on laboratory measurement results

Multithreaded two-pass connected components labelling and particle analysis in ImageJ

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