scholarly journals A NOVEL FRACTAL MODEL FOR ESTIMATING PERMEABILITY IN LOW-PERMEABLE SANDSTONE RESERVOIRS

Fractals ◽  
2020 ◽  
Vol 28 (08) ◽  
pp. 2040005
Author(s):  
SHUNING DONG ◽  
LULU XU ◽  
ZHENXUE DAI ◽  
BIN XU ◽  
QINGYANG YU ◽  
...  
Keyword(s):  
Predictive Model ◽  
Water Inrush ◽  
Image Data ◽  
Theoretical Models ◽  
Underground Water ◽  
Fractal Model ◽  
Sem Images ◽  
Permeability Model ◽  
Microstructural Parameters ◽  
Sandstone Reservoirs

Permeability is one of the most important parameters for accurately predicting water flow in reservoirs and quantifying underground water inrush into coal mines. This study developed a predictive permeability model by considering the microstructural parameters and tortuosity effects of low-permeability sandstone. The model incorporates the fractal geometry theory, Darcy’s law, and Poiseuille equation into a multistep inversion framework for systematic interpretation of sandstone scanning electron microscopy (SEM) images. A threshold segmentation algorithm is applied to transform SEM images into binary images. Then, we used an improved statistical algorithm with binary image data to estimate the geometric parameters of each pore, such as the perimeter and area. The fractal parameters of pore microstructure were determined by fitting the data of pore perimeters and areas. Finally, the effects of tortuosity on microscopic percolation were considered, and a conventional model was modified for quantifying the relationship between microscopic pore structures parameters and macroscopic permeability. Eight groups of sandstone samples from the Xingdong coal mine in North China were collected for estimating permeability by the developed inversion framework. A direct permeability measurement was also conducted on each sample with an AP-608 automatic measuring instrument. The measured permeability values were compared with results from theoretical models, and we found that the accuracy of the newly developed predictive model is better than that of a conventional permeability model. The predictive model developed in this study provides a useful tool for estimating permeability in low-permeable sandstone reservoirs.

PERMEABILITY PREDICTION IN ROUGHENED FRACTURES UNDER STRESS CONDITION USING FRACTAL MODEL

Fractals ◽  
2019 ◽  
Vol 27 (03) ◽  
pp. 1950030 ◽  
Author(s):  
GANG LEI ◽  
NAI CAO ◽  
QINGZHI WEN
Keyword(s):  
Stress Condition ◽  
Fractal Model ◽  
Coupled Flow ◽  
Permeability Model ◽  
Microstructural Parameters ◽  
Rough Fracture ◽  
Proposed Model ◽  
Stress Dependent ◽  
Rock Lithology ◽  
Good Agreement

The prediction of permeability in rough fracture under stress condition presents ever more of a challenge in various scientific and engineering fields. However, up to now, the essential controls on stress-dependent permeability of rough fracture are not determined. In order to find a relationship between the microstructure and the permeability of rough fracture, an analytical method for the permeability of roughened fracture under stress condition is proposed based on the fractal model. The validity of the proposed model is obtained by the good agreement between the simulated results and the experimental data. Compared with the previous models, our model takes into account more factors, including the influence of the microstructural parameters of rough fracture and rock lithology. This paper presents that (1) the rock with soft lithology can yield smaller normalized permeability, (2) normalized permeability decreases with the increases of percent of smaller rough elements. The fractal permeability model can reveal more mechanisms that affect the coupled flow deformation behavior in the fractured porous media.

A FRACTAL PERMEABILITY MODEL FOR POROUS–FRACTURE MEDIA WITH THE TRANSFER OF FLUIDS FROM POROUS MATRIX TO FRACTURE

Fractals ◽  
2019 ◽  
Vol 27 (06) ◽  
pp. 1950121 ◽  
Author(s):  
TONGJUN MIAO ◽  
AIMIN CHEN ◽  
YAN XU ◽  
SUJUN CHENG ◽  
BOMING YU
Keyword(s):  
Fractal Dimension ◽  
Geothermal Energy ◽  
Theoretical Foundation ◽  
Flow Behavior ◽  
Porous Matrix ◽  
Fracture Aperture ◽  
Permeability Model ◽  
Microstructural Parameters ◽  
Dimension Formula ◽  
Proposed Model

The transfer of fluids from porous matrix to fracture is a key issue to accurately predict the fluid flow behavior in porous–fracture media. In this work, to take into account the transfer of fluids, the analytical model of dimensionless permeability is proposed based on the fractal geometry theory for porous media. The proposed model is expressed as a function of microstructural parameters of the porous matrix and fracture, such as the pore area fractal dimension [Formula: see text], fractal dimension [Formula: see text] for tortuosity of tortuous capillaries, the ratio [Formula: see text] of the maximum pore size in porous matrix to fracture aperture, as well as the ratio [Formula: see text] of the pressure difference along the fracture to that along the porous matrix layers. The model reveals that the ratios [Formula: see text] and [Formula: see text] have significant influences on the permeability contribution from the porous matrix to the seepage behavior of the fracture. While the contribution of porosity of leak-wall porous surface of the fracture to the permeability is less than 10%. The present results may provide an important theoretical foundation for exploration of petroleum, gas and geothermal energy extraction systems.

A new permeability predictive model based on NMR data for sandstone reservoirs

2020 ◽  
Vol 13 (20) ◽  
Author(s):  
Hongjun Xu ◽  
Changxi Li ◽  
Yiren Fan ◽  
Falong Hu ◽  
Jun Yu ◽  
...  
Keyword(s):  
Predictive Model ◽  
Model Based ◽  
Nmr Data ◽  
Sandstone Reservoirs

FRACTAL ANALYSIS OF SURFACE ROUGHNESS EFFECTS ON GAS DIFFUSION IN POROUS NANOFIBERS

Fractals ◽  
2020 ◽  
Vol 28 (07) ◽  
pp. 2050125
Author(s):  
QIAN ZHENG ◽  
HUILI WANG ◽  
JIAN JIANG ◽  
CHAO XU
Keyword(s):  
Surface Roughness ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Scaling Laws ◽  
Current Model ◽  
Fractal Model ◽  
Gas Diffusion ◽  
Fibrous Materials ◽  
Microstructural Parameters

Fractal model of gas diffusion in porous nanofibers with rough surfaces is derived, in which the porous structure is assumed to be composed of a bundle of tortuous capillaries whose pore size distribution and surface roughness follow the fractal scaling laws. The analytical expression for gas relative diffusion coefficient is a function of the relative roughness and the other microstructural parameters (porosity, the fractal dimension for pore size distribution and tortuosity, the maximum and minimum pore diameter and the characteristic length). The proposed fractal model is validated by comparison with available experimental data and correlations. At the same time, the effect of microstructural parameters of porous fibrous materials on gas diffusion has been studied in detail. It is believed that the current model may be extended to porous materials other than fibrous materials.

scholarly journals A New Model to Calculate Oil-Water Relative Permeability of Shaly Sandstone

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Huiyuan Bian ◽  
Kewen Li ◽  
Binchi Hou ◽  
Xiaorong Luo
Keyword(s):  
Relative Permeability ◽  
Oil Field ◽  
Permeability Model ◽  
Field Development ◽  
Oil Field Development ◽  
Oil Water ◽  
Sandstone Reservoir ◽  
Sandstone Reservoirs ◽  
Resistivity Logging ◽  
Shaly Sandstone

Oil-water relative permeability curves are the basis of oil field development. In recent years, the calculation of oil-water relative permeability in sandstone reservoirs by resistivity logging data has received much attention from researchers. This article first analyzed the existing mathematical models of the relationship between relative permeability and resistivity and found that most of them are based on Archie formula, which assumes the reservoir is clean sandstone. However, in view of the fact that sandstone reservoir is commonly mixed with shale contents, this research, based on the dual water conductivity model, Poiseuille’s equation, Darcy’s law, and capillary bundle model, derived a mathematical model (DW relative permeability model) for shaly sandstone reservoir, which calculates the oil-water relative permeability with resistivity. To test and verify the DW relative permeability model, we designed and assembled a multifunctional core displacement apparatus. The experiment of core oil-water relative permeability and resistivity was designed to prove the effectiveness of the DW relative permeability model in shaly sandstone reservoirs. The results show that the modified Li model can well express the transformational relation between resistivity and relative permeability in sandstone reservoir with low clay content. Compared with the modified Li model and the Pairoys model, the DW relative permeability model is more helpful to collect better results of relative permeability in shaly sand. These findings will play a significant role in the calculation of oil-water relative permeability in reservoirs based on resistivity logging data and will provide important data and theory support to the shaly sandstone reservoir characterized oil field development.

scholarly journals The Effect of Micro-Segregation on the Quantification of Microstructural Parameters in Grade 91 Steel

2020 ◽  
Vol 52 (1) ◽  
pp. 426-437
Author(s):  
Sharhid Jabar ◽  
John A. Siefert ◽  
Martin Strangwood ◽  
Geoff D. West
Keyword(s):  
Phase Particle ◽  
High Sensitivity ◽  
Compositional Variation ◽  
Chemical Mapping ◽  
Sem Images ◽  
Chemical Homogeneity ◽  
Micro Scale ◽  
Microstructural Parameters ◽  
Grade 91 ◽  
Grade 91 Steel

AbstractThe quantification of key microstructural parameters as a function of aging or creep exposure time is commonplace in the assessment of 9Cr Creep Strength Enhanced Ferritic (CSEF) power-plant steels. In these studies, the sample is either assumed chemically homogenous at the micro-scale or that a material average will be achieved by collecting enough images at random locations. In this paper, the micro-scale chemical homogeneity of two ex-service boiler components, a pipe and a forging, are quantitatively assessed using high sensitivity chemical mapping from µ-XRF. The compositional variation was as expected most pronounced in the larger elements Mo and Nb, where a > 20 pct difference in composition was present between positively and negatively segregated areas. The effect of this micro-segregation on local variations in Laves phase particle characteristics was investigated using SEM images. This showed a factor of two difference in the number of particles and the area coverage between positively and negatively Mo-segregated regions. This result was consistent with the thermodynamic equilibrium predictions of the phase content based on the observed level of segregation.

Xinhe Mine water inrush risk assessment based on quantification theoretical models

2010 ◽  
Vol 16 (4) ◽  
pp. 386-388 ◽  
Author(s):  
Hui Li ◽  
Guo-xun Jing ◽  
Zheng-long Cai ◽  
Jian-chun Ou
Keyword(s):  
Risk Assessment ◽  
Mine Water ◽  
Water Inrush ◽  
Theoretical Models

A prediction model for pathological findings after neoadjuvant chemoradiotherapy for resectable locally advanced esophageal cancer based on PET images using radiomics and machine-learning.

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 456-456
Author(s):  
Yuji Murakami ◽  
Yasushi Nagata ◽  
Daisuke Kawahara
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Predictive Model ◽  
Test Data ◽  
Locally Advanced ◽  
Neoadjuvant Chemoradiotherapy ◽  
Image Data ◽  
Ct Images ◽  
Pathological Findings ◽  
Planning Ct

456 Background: The pathologic complete response (PCR) rate by neoadjuvant chemoradiotherapy (NCRT) for resectable locally advanced esophageal squamous cell carcinoma (ESCC) is about 40%. If we could predict a PCR from pre-treatment image data, it might be possible to select patients who can be cured by organ-preserving CRT. The purpose of this study is to construct a predictive model for PCR by NCRT in patients with locally advanced ESCC using radiomics and machine-learning. Methods: We used data of 98 ESCC patients who underwent NCRT and surgery from 2003 to 2016. Firstly, we fused the radiotherapy treatment planning CT images and PET images scanned before treatment. Then using target delineations on planning CT images, we created eight kinds of target regions on PET images. Secondly, we generated a total of 6968 features per patient using the PET image data within these target regions that were preprocessed by radiomics technique. Among them, we extracted the optimal features for machine-learning using the least absolute shrinkage and selection operator (LASSO) logistic regression. Thirdly, artificial neural networks were used as a machine-learning method to create a predictive model. The extracted radiomics features were used as input values, and the information of ‘PCR’ or ‘not PCR’ was used as output values. We used data of randomly selected 58 patients for training and constructed a predictive model. Then we used data of 15 patients to validate the models and created the optimal model. Finally, we evaluated the predictive model using the test data of 25 patients. Results: By the LASSO analysis, 32 radiomics features were extracted for machine-learning classification. This predictive model predicted pathological findings after NCRT in 24 of 25 test data. The accuracy, specificity and sensitivity in the prediction of PCR after NCRT by this predictive model were 96.0%, 93.8%, and 100%, respectively. Conclusions: A prediction model based on PET images using radiomics and machine-learning could predict pathological findings after NCRT for resectable locally advanced ESCC.

RECENT ADVANCES ON FRACTAL MODELING OF PERMEABILITY FOR FIBROUS POROUS MEDIA

Fractals ◽  
2015 ◽  
Vol 23 (01) ◽  
pp. 1540006 ◽  
Author(s):  
JIANCHAO CAI ◽  
LIANG LUO ◽  
RAN YE ◽  
XIANGFENG ZENG ◽  
XIANGYUN HU
Keyword(s):  
Porous Media ◽  
Pore Structure ◽  
Fractal Geometry ◽  
Influence Factor ◽  
Fractal Model ◽  
Fibrous Materials ◽  
Permeability Model ◽  
Fractal Modeling ◽  
Fibrous Porous Media ◽  
Future Work

Permeability is an important hydraulic parameter for characterizing heat and mass transfer properties of fibrous porous media. However, it is difficult to be quantitatively predicted due to the complex and irregular pore structure of fibrous porous media. Fractal geometry has been verified to be an effective method for determining the permeability of fibrous porous media. In this study, recent works on the permeability of fibrous porous media by means of fractal geometry are reviewed, the advances for each presented fractal model are analyzed and summarized, parameter equations used in available fractal permeability models are also briefly compared and reviewed. Future work for more generalized permeability model of fibrous porous media need to conducted by considering the special characters of fibrous materials, uniform pore structure parameter model and the influence factor of capillary pressure, electrokinetic phenomena, etc.

scholarly journals Three-Dimensional Numerical Simulation of Multiscale Fractures and Multiphase Flow in Heterogeneous Unconventional Reservoirs with Coupled Fractal Characteristics

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hong Li ◽  
Haiyang Yu ◽  
Nai Cao ◽  
Shiqing Cheng ◽  
He Tian ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Multiphase Flow ◽  
Water Saturation ◽  
Three Dimensional ◽  
Horizontal Wells ◽  
Simulation Method ◽  
Fractal Model ◽  
Point Pattern ◽  
Permeability Model ◽  
Heterogeneous Model

A simulated reservoir model, based on the permeability fractal model and three-dimensional (3D) Gaussian filter, was established to account for in-layer and interlayer heterogeneity so that the result conforms to the law of geological statistics. Combined with an embedded discrete fracture method (EDFM), a multiscale fracture system was established, forming the numerical simulation method of multiphase flow in horizontal wells in heterogeneous reservoirs with complex fractures. The heterogeneity and saturation of the reservoir mixed five-point pattern of vertical and horizontal wells and the injection and production of horizontal wells were discussed. The results show that it is difficult to characterize complex reservoirs using a homogeneous permeability model. Thus, it is best to use a heterogeneous model that considers permeability differences in tight reservoirs. Formation fluids coexist in multiple phases, and water saturation has a direct effect on the production. Thus, a multiphase flow model is needed and can play a greater role in injection and production technology. The mixed five-point pattern of vertical and horizontal wells can improve productivity to a certain extent, but the dual effects of heterogeneity and fracturing will cause a decline in production by accelerating the communication of injected fluid. The reservoir is heterogeneous between wells, and there are differing effects on adjacent wells. Therefore, near-well natural microfractures are opened because of fracturing in horizontal wells, and the heterogeneity cannot be ignored, especially when multiple wells are simultaneously injected and produced.

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