scholarly journals Bi-Fractal Characterization of the Pore Network of Tight Sandstone

2021 ◽  
Vol 9 ◽  
Author(s):  
Zezhang Song ◽  
Junyi Zhao ◽  
Yuanyin Zhang ◽  
Dailin Yang ◽  
Yunlong Wang ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Pore Structure ◽  
Thin Section ◽  
Fractal Analysis ◽  
Pore Space ◽  
Fractal Dimensions ◽  
Pore Network ◽  
Physical Analysis ◽  
Tight Sandstone ◽  
Gas Bearing

Fluid seepage performance and accumulation in tight sandstone is a critical research topic for in-depth exploration and development, closely related to the heterogeneity of the pore network. The fractal characterization is one of the most compelling and direct ways for quantitative investigation of heterogeneity. However, only one kind of fractal is used in most studies, and the differences and relations between different fractal dimensions are rarely discussed. This paper chose one of the most representative tight sandstone formations in China, the second member of the Xujiahe Formation, as the research object. First, based on physical analysis and XRD analysis, we carried out a qualitative investigation on pore structure utilizing thin-section and scanning electron microscopy. Then, detailed pore structure parameters were obtained using high-pressure mercury intrusion (HPMI). Lastly, we combined two-dimensional fractal analysis on thin-section images and three-dimensional fractal analysis on HPMI data to characterize the pore network heterogeneity quantitatively. The Xu2 tight sandstone is mainly medium- to fine-grained lithic feldspathic sandstone or feldspathic lithic sandstone with low porosity and permeability. Also, the Xujiahe tight sandstone is mainly composed of quartz, feldspar, and clay. The pore types of Xu2 tight sandstones are primarily intergranular pores, micro-fractures, and intra- and intergranular dissolution pores. Moreover, most of the micro-fractures in gas-bearing formation are open-ended, while most are filled by clay minerals in the dry formation. The r50 (median pore radius) is the most sensitive parameter to seepage capability (permeability) and gas-bearing status. The 2D fractal dimension (Ds) of gas-bearing samples is significantly larger than that of dry samples, while the 3D fractal dimension (D1, D2) of gas-bearing samples is lower than that of dry samples. There is a strong negative correlation between D2 and gas-bearing status, permeability, quartz content, and r50, but a positive correlation between Ds and these parameters. D2 represents the heterogeneity of pore space, while the Ds indicates the development of the pore network. Tectonic movements that generate micro-fractures and clay cementation that blocks the seepage channels are the two main controlling factors on fractal dimensions. Combining 2D and 3D fractal analysis could give a more in-depth investigation of pore structure.

scholarly journals Nano-Scale Pore Structure and Its Multi-Fractal Characteristics of Tight Sandstone by N2 Adsorption/Desorption Analyses: A Case Study of Shihezi Formation from the Sulige Gas Filed, Ordos Basin, China

Minerals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 377
Author(s):  
Zhelin Wang ◽  
Xuewei Jiang ◽  
Mao Pan ◽  
Yongmin Shi
Keyword(s):  
Fractal Dimension ◽  
Specific Surface ◽  
Pore Structure ◽  
Surface Area ◽  
Mineral Composition ◽  
Fractal Dimensions ◽  
Contribution Rate ◽  
Tight Sandstone ◽  
N2 Adsorption ◽  
Adsorption Desorption

Fractal dimension is a critical parameter to evaluate the heterogeneity of complex pore structure in tight sandstone gas and other low permeability reservoirs. To quantify the fractal dimension of tight sandstone at various pore size classes and evaluate their implications on mineral composition and nano pore structure parameters, we conducted an integrated approach of N2 adsorption/desorption experiment (N2-GA), X-ray diffraction (X-RD), and field emission scanning electron microscopy (FE-SEM) on Sulige tight sandstone reservoirs. By comparing the nine types of fractal dimensions calculated from N2 adsorption data, we put forward the concept of “concentrated” fractal dimensions and “scattered” fractal dimensions (DN2, DN3, DN5, DN7 and DN8) for the first time according to its concentration extent of distribute in different samples. Result shows that mineral composition has a significant influence of a different level on specific surface area (SSA), pore volume (PV), and fractal dimensions (DN), respectively, where the “scattered” fractal dimension is more sensitive to certain specific property of the reservoir, including mineral content and the specific surface area contribution rate (Sr) of type II mesopores (Mesopore-II: 10~50nm). In addition, three type of hysteresis loops were distinguished corresponding to different pore shape combination of N2-GA isotherm curve, which reveals that pore structure heterogeneity is mainly controlled by inkbottle-shaped pores and the volume contribution rate (Vr) of mesopores in this study area. These findings could contribute to a better understanding of the controlling effect of pore heterogeneity on natural gas storage and adsorption.

scholarly journals Fractal Characterization of Nanopore Structure in Shale, Tight Sandstone and Mudstone from the Ordos Basin of China Using Nitrogen Adsorption

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 583 ◽  
Author(s):  
Xiaohong Li ◽  
Zhiyong Gao ◽  
Siyi Fang ◽  
Chao Ren ◽  
Kun Yang ◽  
...  
Keyword(s):  
Pore Structure ◽  
Pressure Range ◽  
Ordos Basin ◽  
Fractal Dimensions ◽  
Nitrogen Adsorption ◽  
Relative Pressure ◽  
Tight Sandstone ◽  
Porosity And Permeability ◽  
The Ordos Basin ◽  
Nanopore Structure

The characteristics of the nanopore structure in shale, tight sandstone and mudstone from the Ordos Basin of China were investigated by X-ray diffraction (XRD) analysis, porosity and permeability tests and low-pressure nitrogen adsorption experiments. Fractal dimensions D1 and D2 were determined from the low relative pressure range (0 < P/P0 < 0.4) and the high relative pressure range (0.4 < P/P0 < 1) of nitrogen adsorption data, respectively, using the Frenkel–Halsey–Hill (FHH) model. Relationships between pore structure parameters, mineral compositions and fractal dimensions were investigated. According to the International Union of Pure and Applied Chemistry (IUPAC) isotherm classification standard, the morphologies of the nitrogen adsorption curves of these 14 samples belong to the H2 and H3 types. Relationships among average pore diameter, Brunner-Emmet-Teller (BET) specific surface area, pore volume, porosity and permeability have been discussed. The heterogeneities of shale nanopore structures were verified, and nanopore size mainly concentrates under 30 nm. The average fractal dimension D1 of all the samples is 2.1187, varying from 1.1755 to 2.6122, and the average fractal dimension D2 is 2.4645, with the range from 2.2144 to 2.7362. Compared with D1, D2 has stronger relationships with pore structure parameters, and can be used for analyzing pore structure characteristics.

scholarly journals The Impacts of Matrix Compositions on Nanopore Structure and Fractal Characteristics of Lacustrine Shales from the Changling Fault Depression, Songliao Basin, China

Minerals ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 127 ◽  
Author(s):  
Zhuo Li ◽  
Zhikai Liang ◽  
Zhenxue Jiang ◽  
Fenglin Gao ◽  
Yinghan Zhang ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Pore Structure ◽  
Fractal Dimensions ◽  
Organic Medium ◽  
Songliao Basin ◽  
Sem Images ◽  
Fractal Characteristics ◽  
Inorganic Mineral ◽  
Nanopore Structure ◽  
High Fractal Dimension

The Lower Cretaceous Shahezi shales are the targets for lacustrine shale gas exploration in Changling Fault Depression (CFD), Southern Songliao Basin. In this study, the Shahezi shales were investigated to further understand the impacts of rock compositions, including organic matters and minerals on pore structure and fractal characteristics. An integrated experiment procedure, including total organic carbon (TOC) content, X-ray diffraction (XRD), field emission-scanning electron microscope (FE-SEM), low pressure nitrogen physisorption (LPNP), and mercury intrusion capillary pressure (MICP), was conducted. Seven lithofacies can be identified according to on a mineralogy-based classification scheme for shales. Inorganic mineral hosted pores are the most abundant pore type, while relatively few organic matter (OM) pores are observed in FE-SEM images of the Shahezi shales. Multimodal pore size distribution characteristics were shown in pore width ranges of 0.5–0.9 nm, 3–6 nm, and 10–40 nm. The primary controlling factors for pore structure in Shahezi shales are clay minerals rather than OM. Organic-medium mixed shale (OMMS) has the highest total pore volumes (0.0353 mL/g), followed by organic-rich mixed shale (ORMS) (0.02369 mL/g), while the organic-poor shale (OPS) has the lowest pore volumes of 0.0122 mL/g. Fractal dimensions D1 and D2 (at relative pressures of 0–0.5 and 0.5–1 of LPNP isotherms) were obtained using the Frenkel–Halsey–Hill (FHH) method, with D1 ranging from 2.0336 to 2.5957, and D2 between 2.5779 and 2.8821. Fractal dimensions are associated with specific lithofacies, because each lithofacies has a distinctive composition. Organic-medium argillaceous shale (OMAS), rich in clay, have comparatively high fractal dimension D1. In addition, organic-medium argillaceous shale (ORAS), rich in TOC, have comparatively high fractal dimension D2. OPS shale contains more siliceous and less TOC, with the lowest D1 and D2. Factor analysis indicates that clay contents is the most significant factor controlling the fractal dimensions of the lacustrine Shahezi shale.

scholarly journals Multifractal Analysis of Pore Structure and Evaluation of Deep-Buried Cambrian Dolomite Reservoir with Image Processing: A Case from Tarim Basin, NW China

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Xiaojun Zhang ◽  
Haodong Han ◽  
Jun Peng ◽  
Yingchun Gou
Keyword(s):  
Pore Structure ◽  
Thin Section ◽  
Tarim Basin ◽  
Clustering Analysis ◽  
Multifractal Analysis ◽  
Pore Space ◽  
Tectonic Activity ◽  
Petrophysical Properties ◽  
Nw China ◽  
Crystalline Dolomite

Reservoir pore space assessment is of great significance for petroleum exploration and production. However, it is difficult to describe the pore characteristics of deep-buried dolomite reservoirs with the traditional linear method because these rocks have undergone strong modification by tectonic activity and diagenesis and show significant pore space heterogeneity. In this study, 38 dolostone samples from 4 Cambrian formations of Tarim Basin in NW China were collected and 135 thin section images were analyzed. Multifractal theory was used for evaluation of pore space heterogeneity in deep-buried dolostone based on thin section image analysis. The physical parameters, pore structure parameters, and multifractal characteristic parameters were obtained from the digital images. Then, the relationships between lithology and these parameters were discussed. In addition, the pore structure was classified into four categories using K-means clustering analysis based on multifractal parameters. The results show that the multifractal phenomenon generally exists in the pore space of deep-buried dolomite and that multifractal analysis can be used to characterize the heterogeneity of pore space in deep-buried dolomite. For these samples, multifractal parameters, such as αmin, αmax, ΔαL, ΔαR, Δf, and AI, correlate strongly with porosity but only slightly with permeability. However, the parameter Δα, which is usually used to reveal heterogeneity, does not show an obvious link with petrophysical properties. Of dolomites with different fabrics, fine crystalline dolomite and medium crystalline dolomite show the best petrophysical properties and show significant differences in multifractal parameters compared to other dolomites. More accurate porosity estimations were obtained with the multifractal generalized fractal dimension, which provides a new method for porosity prediction. The various categories derived from the K-means clustering analysis of multifractal parameters show distinct differences in petrophysical properties. This proves that reservoir evaluation and pore structure classification can be accurately performed with the K-means clustering analysis method based on multifractal parameters of pore space in deep-buried dolomite reservoirs.

Micro-Nanopore Structure and Fractal Characteristics of Tight Sandstone Gas Reservoirs in the Eastern Ordos Basin, China

2021 ◽  
Vol 21 (1) ◽  
pp. 234-245
Author(s):  
Peng Qiao ◽  
Yiwen Ju ◽  
Jianchao Cai ◽  
Jun Zhao ◽  
Hongjian Zhu ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Pore Structure ◽  
Ordos Basin ◽  
Gas Storage ◽  
Main Peak ◽  
Storage Space ◽  
Tight Sandstone ◽  
Fractal Characteristics ◽  
Sandstone Reservoirs ◽  
Nanopore Structure

The complex pore system in tight sandstone reservoirs controls the storage and transport of natural gas. Thus, quantitatively characterizing the micro-nanopore structure of tight sandstone reservoirs is of great significance to determining the accumulation and distribution of tight gas. The pore structure of reservoirs was determined through polarizing microscopy, scanning electron microscopy (SEM), and the combination of mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) experiments on Late Paleozoic conventional and tight sandstone samples from the Linxing Block, Ordos Basin. The results show that in contrast to conventional sandstone, dissolution pores, with diameters less than 8 μm, are the main contributors to the gas storage space of tight sandstone reservoirs. The pore size distribution derived from the MICP experiment demonstrates that the main peak of tight sandstones corresponds to a pore radius in the range of 247 nm to 371 nm, while the secondary peak usually corresponds to 18 nm. The results of the NMR test illustrate that the T2 spectra of tight sandstones are unimodal, bimodal and multimodal, and the main NMR peak is highly related to the MICP peak. Fractal theory was proposed to quantitatively characterize the complex pore structure and rough porous surface. The sandstones show fractal characteristics including nanopore fractal dimension DN obtained from the MICP and large pore fractal dimension DL obtained from the NMR experiment. Both DN and DL are positively correlated with porosity and negatively correlated with permeability, demonstrating that complex and heterogeneous pore structure could increase the gas storage space and reduce the connectivity.

Nano/Micro Pore Structure and Fractal Characteristics of Baliancheng Coalfield in Hunchun Basin

2021 ◽  
Vol 21 (1) ◽  
pp. 682-692
Author(s):  
Youzhi Wang ◽  
Cui Mao
Keyword(s):  
Fractal Dimension ◽  
Specific Surface ◽  
Pore Structure ◽  
Surface Area ◽  
Specific Surface Area ◽  
Pore Diameter ◽  
Fractal Dimensions ◽  
Nitrogen Adsorption ◽  
Average Pore ◽  
Coal Reservoir

The pore structure characteristic is an important index to measure and evaluate the storage capacity and fracturing coal reservoir. The coal of Baliancheng coalfield in Hunchun Basin was selected for experiments including low temperature nitrogen adsorption method, Argon Ion milling Scanning Electron Microscopy (Ar-SEM), Nuclear Magnetic Resonance (NMR), X-ray diffraction method, quantitative mineral clay analysis method. The pore structure of coal was quantitatively characterized by means of fractal theory. Meanwhile, the influences of pores fractal dimension were discussed with experiment data. The results show that the organic pores in Baliancheng coalfield are mainly plant tissue pores, interparticle pores and gas pores, and the mineral pores are corrosion pores and clay mineral pores. There are mainly slit pore and wedge-shaped pore in curve I of Low temperature nitrogen adsorption. There are ink pores in curve II with characteristics of a large specific surface area and average pore diameter. The two peaks of NMR T2 spectrum indicate that the adsorption pores are relatively developed and their connectivity is poor. The three peaks show the seepage pores and cracks well developed, which are beneficial to improve the porosity and permeability of coal reservoir. When the pore diameter is 2–100 nm, the fractal dimensions D1 and D2 obtained by nitrogen adsorption experiment. there are positive correlations between water content and specific surface area and surface fractal dimension D1, The fractal dimension D2 was positively and negatively correlated with ash content and average pore diameters respectively. The fractal dimensions DN1 and DN2 were obtained by using the NMR in the range of 0.1 μm˜10 μm. DN1 are positively correlated with specific surface area of adsorption pores. DN2 are positively correlated volume of seepage pores. The fractal dimension DM and dissolution hole fractal dimension Dc were calculated by SEM image method, respectively controlled by clay mineral and feldspar content. There is a remarkable positive correlation between D1 and DN1 and Langmuir volume of coal, so fractal dimension can effectively quantify the adsorption capacity of coal.

scholarly journals FRACTAL ANALYSIS OF TRABECULAR BONE: A STANDARDISED METHODOLOGY

2011 ◽  
Vol 19 (1) ◽  
pp. 45 ◽  
Author(s):  
Ian Parkinson ◽  
Nick Fazzalari
Keyword(s):  
Fractal Dimension ◽  
Trabecular Bone ◽  
Fractal Analysis ◽  
Fractal Dimensions ◽  
Box Counting ◽  
Cell Tissue ◽  
Image Analyser ◽  
Model Independent ◽  
Box Counting Method ◽  
Image Orientation

A standardised methodology for the fractal analysis of histological sections of trabecular bone has been established. A modified box counting method has been developed for use on a PC based image analyser (Quantimet 500MC, Leica Cambridge). The effect of image analyser settings, magnification, image orientation and threshold levels, was determined. Also, the range of scale over which trabecular bone is effectively fractal was determined and a method formulated to objectively calculate more than one fractal dimension from the modified Richardson plot. The results show that magnification, image orientation and threshold settings have little effect on the estimate of fractal dimension. Trabecular bone has a lower limit below which it is not fractal (λ<25 μm) and the upper limit is 4250 μm. There are three distinct fractal dimensions for trabecular bone (sectional fractals), with magnitudes greater than 1.0 and less than 2.0. It has been shown that trabecular bone is effectively fractal over a defined range of scale. Also, within this range, there is more than 1 fractal dimension, describing spatial structural entities. Fractal analysis is a model independent method for describing a complex multifaceted structure, which can be adapted for the study of other biological systems. This may be at the cell, tissue or organ level and compliments conventional histomorphometric and stereological techniques.

scholarly journals Quantitative Characterization of Heterogeneity in Different Reservoir Spaces of Low-Permeability Sandstone Reservoirs and Its Influence on Physical Properties

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Fengjuan Dong ◽  
Na Liu ◽  
Zhen Sun ◽  
Xiaolong Wei ◽  
Haonan Wang ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Pore Structure ◽  
Fractal Theory ◽  
Fractal Dimensions ◽  
Low Permeability ◽  
Quantitative Characterization ◽  
Average Value ◽  
Porosity And Permeability ◽  
Sandstone Reservoirs

The complex pore structure of low-permeability sandstone reservoir makes it difficult to characterize the heterogeneity of pore throat. Taking the reservoir of Sanjianfang formation in QL oilfield as an example, the fractal dimension of different storage spaces is calculated by using fractal theory based on casting thin section, scanning electron microscope, and high-pressure mercury injection, and the correlation between porosity, permeability, and contribution of different storage space permeabilities is analyzed. The results show that the reservoir of Sanjianfang formation in QL oilfield mainly develops small pores, fine pores, and micropores, and the fractal dimension of micropore structure is between 2.6044 and 2.9982, with an average value of 2.8316. The more complex the pore structure is, the stronger the microheterogeneity is. The higher the fractal dimension, the more complex the pore structure and the smaller the porosity and permeability. The fractal dimensions of small pores, fine pores, and micropores increase successively with the decrease in pore radius, and the microstructure heterogeneity of large pores is weaker than that of small pores. It provides a theoretical basis for the exploration and development of low-permeability sandstone reservoirs.

scholarly journals Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system

2016 ◽  
Author(s):  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer ◽  
Susana Ochoa Rodriguez ◽  
Patrick Willems ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Fractal Analysis ◽  
Fractal Dimensions ◽  
Hydrological Models ◽  
Scale Invariant ◽  
Sewer System ◽  
Distributed Models ◽  
Urban Catchments ◽  
Distributed Hydrological Models ◽  
Dimension Characteristic

Abstract. Fractal analysis relies on scale invariance and the concept of fractal dimension enables to characterise and quantify the space filled by a geometrical set exhibiting complex and tortuous patterns. Fractal tools have been widely used in hydrology but seldom in the specific context of urban hydrology. In this paper fractal tools are used to analyse surface and sewer data from 10 urban or peri-urban catchments located in 5 European countries. The aim was to characterise urban catchment properties accounting for the complexity and inhomogeneity typical of urban water systems. Sewer system density and imperviousness (roads or buildings), represented in rasterized maps of 2 m × 2 m pixels, were analysed to quantify their fractal dimension, characteristic of scaling invariance. The results showed that both sewer density and imperviousness exhibit scale invariant features and can be characterized with the help of fractal dimensions ranging from 1.6 to 2, depending on the catchment. In a given area consistent results were found for the two geometrical features, yielding a robust and innovative way of quantifying the level of urbanization. The representation of imperviousness in operational semi-distributed hydrological models for these catchments was also investigated by computing fractal dimensions of the geometrical sets made up of the sub-catchments with coefficients of imperviousness greater than a range of thresholds. It enabled to quantify how well spatial structures of imperviousness were represented in the urban hydrological models.

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