Investigating 3D geometry of porous media from high resolution images

Lindquist, W. Brent; Venkatarangan, A.

doi:10.1016/s1464-1895(99)00085-x

Cited by 268 publications

(166 citation statements)

References 6 publications

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“…Moreover, after long-term flooding in reservoir of the Jidong Oilfield, the separation of pore and throat becomes better, and microheterogeneity of reservoir gradually becomes weaker. The rule has not been reported before (Elliott and Dover 1982;Sorbie et al 1989;Lymberopoulos and Payatakes 1992;Xu et al 1999;Fredrich et al 1995;Fredrich 1999;Delerue et al 1999;Lindquist and Venkatarangan 1999;Liang et al 2000;Blunt (2001); Radlinski et al 2002;Siddiqui and Khamees 2004;Coenen et al 2004;Arns et al 2004Arns et al , 2005Knackstedt et al 2006;Al-Kharusi and Blunt 2007;Tomutsa et al 2007;Hou et al 2007;Youssef et al 2008;Dong and Blunt 2009;Mustafa et al 2009;Xu et al 2010;Peng et al 2012;Saurabh et al 2013;Theis et al 2014). …”

Section: D Model Of Pore Networkmentioning

confidence: 92%

“…Since the pore network model was proposed by Fatt (1956aFatt ( , b, c) in 1956, it has been a powerful tool to study microscopic reservoir structure and seepage characteristics. Elliott and Dover (1982), Sorbie et al (1989), Lymberopoulos and Payatakes (1992), Xu et al (1999), Fredrich et al (1995), Fredrich (1999, Delerue et al (1999), Lindquist and Venkatarangan (1999), Liang et al (2000), Blunt (2001), Radlinski et al (2002), Siddiqui and Khamees (2004), Coenen et al (2004), Knackstedt et al (2006), Al-Kharusi and Blunt (2007), Tomutsa et al (2007), Blunt (2009), Peng et al (2012), Saurabh et al (2013), Theis et al (2014), have researched the technologies and algorithms of constructing the digital core and 3D pore network model, and the 3D pore network model has been rapidly developed and widely applied. Among those technologies, the method of constructing 3D pore network model with digital core reconstructed by high-precision X-ray CT scanning is dominant, and it is future direction of researching microstructure of reservoir pore (Hou et al 2007;Arns et al 2004Arns et al , 2005Youssef et al 2008;Mustafa et al 2009).…”

Section: Introductionmentioning

confidence: 99%

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Study on microheterogeneity and seepage law of reservoir after long-term water flooding

Hua

Liu

Sun³

2017

J Petrol Explor Prod Technol

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In order to carry out research on variation of microheterogeneity in sandstone reservoir after long-term water flooding in the complex faulted oilfields, the cores are cut from typical wells of main oil layers of two blocks in the Jidong Oilfield, and the experiments of long-term water flooding are conducted. Based on the mercury-injection data at different water cut stages during water flooding and the digital core data reconstructed by X-ray CT scanning, the variation of microheterogeneity of reservoir at different water cut stages during long-term water flooding of core are quantitatively characterized through fractal dimension method and 3D pore network model, and the rule of oil-water seepage at different water cut stages is characterized. The study showed that the middle-high-permeability reservoir has a good fractal structure with fractal dimension between 2 and 3. The large pore has the less fractal dimension, and the better homogeneity and pore structure than the small one. After the cores are washed by long-term water flooding, and as the water cut increases, the fractal dimensions of large and small pore gradually decrease, mean and medium pore diameters increase, the relative sorting coefficient decreases, the distribution probability of throat radius of core generally increases, and the microheterogeneity of reservoir weakens. Moreover, the oil relative permeability curves are almost overlapped, and the water relative permeability curves result in a big difference. Under the same water saturation, as the water cut increases, the fractal dimension decreases, the water relative permeability increases, and the oil-water common seepage points shift to the left.

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Section: D Model Of Pore Networkmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Study on microheterogeneity and seepage law of reservoir after long-term water flooding

Hua

Liu

Sun³

2017

J Petrol Explor Prod Technol

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“…X-ray CT images of the specimen which experienced each loading step are taken after loading. Subsequently, the Three Dimensional Medial Axis Analysis (3DMA) (Lindquist et al 1996(Lindquist et al , 1999) is applied to the three-dimensional CT data of the specimen. The porosity P idx , burn number and medial axis of the parameters in the 3DMA are used in order to represent micro-damage to the specimen.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Micro-damage of Concrete Specimens under Cyclic Uniaxial Loading by X-ray CT Method

Tanikura

Jung

Shintani

et al. 2016

ACT

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The X-ray CT method was applied to evaluate micro-damage -namely, deterioration of concrete specimens under cyclic uniaxial loading tests. The μ-focus X-ray CT scanner was used. Concrete cylinders with a diameter of 50 mm and a length of 100 mm were prepared as specimens. Cyclic uniaxial loading tests were conducted on the specimens. The X-ray CT images of the specimens were taken at the loading level 0, 60, 70, 80 and 90 percent of their uniaxial compressive strength. For three dimensional CT images of the specimen, the Three Dimensional Medial Axis Analysis (3DMA) method was applied to evaluate porosity and width, length, persistence of cracks which represent deterioration of the specimen. As the results, slight micro-fracturing occurs until a loading level R = 60%, and starts to increase at R of 60% to 70%. The cracking occurs in a part of the mortar near boundary between aggregate and mortar, and the crack links to another crack with increasing loading level. The degree of cracking varies according to the position dependent on the final apparent fracture surface of the specimen. It is concluded that the X-ray CT method with 3DMA is effective for not only evaluating the state of micro-cracking within the specimen, but also estimating the process of deterioration of the specimen with an increasing loading level.

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“…A simple thresholding based on matching a predetermined bulk measurement (phase fraction) is often used to segment a tomographic image. We use a kriging-based thresholding method [37] to give a binary pore-solid image [23,24]. The images are also corrected for noise by re-identifying the phase type of all isolated grain and void voxel clusters.…”

Section: Experimental Images From Microtomographymentioning

confidence: 99%

“…The reconstructed images have a resolution of 5.68 µm resulting in 795 × 795 × 512 imaged sections. Due to limitations in computational hardwareat the time the image was initial processed and segmented [22,23] -the original image was divided into 4 subsamples of size 450 × 450 × 512 by Lindquist, overlapping by 50 pixels on the inner sides. The kriging was carried out on these subsamples, which then were recombined to a single binary image (see Fig.…”

Section: Experimental Images From Microtomographymentioning

confidence: 99%

Characterising the Morphology of Disordered Materials

Arns

Knackstedt

Mecke

2002

Morphology of Condensed Matter

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Abstract. We introduce Minkowski functionals to characterise, reconstruct and discriminate different complex material microstructures, for instance, experimental data sets generated from X-ray computer tomography imaging; samples include a suite of Fontainebleau sandstone, and a heterogeneous cross-bedded sandstone. Three distinct classes of digitised complex microstructure are considered: particle based Boolean models, structures generated by level-cuts through Gaussian fields, and models based on a Voronoi tesselation of space. One can define a set of measures for random composite media from a single image at any phase fraction φ which allows one to accurately reconstruct the medium for all other phase fractions and to predict, for instance, the percolation threshold pc. The evolution of the Minkowski functions during erosion and dilation operations on non-convex morphologies leads to a very accurate discrimination of morphologybetter than commonly used techniques such as structure functions or chord length distributions. Spatial Structures: Experimental Data and Stochastic ModelsThe structure of a disordered material -an oil bearing rock, a piece of paper, or a polymer composite -is a remarkably incoherent concept. Despite this, scientists and engineers are asked to predict the properties of a disordered material based on the "structure" of its constituent components. A major shortcoming in the understanding of processes involving complex materials has been an inability to accurately characterize microstructure. The specification of "structure" requires topological as well as geometric descriptors to characterize the connectivity and the shape of the spatial configuration. In oil recovery from petroleum reservoir rocks, an area of particular interest to the authors, recovery depends crucially on the topology of the pore space and on the mean curvature of the surfaces where immiscible phases meet at a contact angle. To determine accurate flow models and to devise intelligent recovery strategies requires an accurate characterization of reservoir rocks in terms of topology and geometry.To date, the main toolkit used to quantify complex structures has been primarily that of the statistical physicist and not the advanced techniques developed in spatial statistics [11,59]

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Investigating 3D geometry of porous media from high resolution images

Cited by 268 publications

References 6 publications

Study on microheterogeneity and seepage law of reservoir after long-term water flooding

Study on microheterogeneity and seepage law of reservoir after long-term water flooding

Evaluation of Micro-damage of Concrete Specimens under Cyclic Uniaxial Loading by X-ray CT Method

Characterising the Morphology of Disordered Materials

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