Arash Rabbani

University of Leeds · School of Computing

The 3D physical properties of porous rocks directly determine the subsurface flow and modelling. However, predicting a wide range of 3D physical rocks remains a formidable challenge and requires a large amount of input. Reliable microstructure‐property correlations can accurately predict 3D physical properties, avoiding time‐consuming experimental...

The meniscal tissue is a layered material with varying properties influenced by collagen content and arrangement. Understanding the relationship between structure and properties is crucial for disease management, treatment development, and biomaterial design. The internal layer of the meniscus is softer and more deformable than the outer layers, th...

Unsaturated solute transport was directly characterized with the use of Synchrotron-based X–ray Computed Tomography (s-XRCT). The spatial and temporal resolutions were 3.25 µm and 6 seconds, respectively.

In this study, a novel method of data augmentation has been presented for the segmentation of placental histological images when the labeled data are scarce. This method generates new realizations of the placenta intervillous morphology while maintaining the general textures and orientations. As a result, a diversified artificial dataset of images...

The acoustical behavior of porous materials is dictated by their underlying pore network geometry. Given the complexity of accurately characterizing the various pore network features, current acoustical models instead rely on indirectly incorporating these features by accounting for them within acoustical transport properties, such as tortuosity, v...

Previously CO2, as a heat-extraction fluid, has been proposed as a superior substitute for brine in geothermal energy extraction. Hence, the new concept of CO2-plume geothermal (CPG) is suggested to generate heat from geothermal aquifers using CO2 as the working fluid. In January 2015, a CPG-thermosiphon system commenced at the SECARB Cranfield Sit...

In this investigation, an image-based method has been developed to estimate the volume of the left ventricular cavity using cardiac magnetic resonance (CMR) imaging data. Deep learning and Gaussian processes have been applied to bring the estimations closer to the cavity volumes manually extracted. CMR data from 339 patients and healthy volunteers...

Conventional 2-D scanning electron microscopy (SEM) is commonly used to rapidly and qualitatively evaluate membrane pore structure. Quantitative 2-D analyses of pore sizes can be extracted from SEM, but without information about 3-D spatial arrangement and connectivity, which are crucial to the understanding of membrane pore structure. Meanwhile, e...

Spinodoid structures, also called spinodoid metamaterials, are non-periodic cellular structures that mimic spinodal topologies that are observed during diffusion-driven phase separation processes. Computationally efficient to model, spinodoid structures can be fabricated using additive techniques and offer an attractive route to the design of multi...

DeepAngle is a machine learning-based method to determine the contact angles of different phases in the tomography images of porous materials. Measurement of angles in 3--D needs to be done within the surface perpendicular to the angle planes, and it could become inaccurate when dealing with the discretized space of the image voxels. A computationa...

In this study, a novel method of data augmentation has been presented for the segmentation of placental histological images when the labeled data are scarce. This method generates new realizations of the placenta intervillous morphology while maintaining the general textures and orientations. As a result, a diversified artificial dataset of images...

CO2 geo-sequestration is a practical approach to achieve net-zero carbon target. However, one of the main challenges for successful CO2 geo-sequestration is the reduced coal permeability and injectivity that are caused by coal swelling. Coal has complex and heterogenous internal pore and fracture structure. The processes of gases adsorbing, desorbi...

In this study, a method has been developed to improve the resolution of histological human placenta images. For this purpose, a paired series of high- and low-resolution images have been collected to train a deep neural network model that can predict image residuals required to improve the resolution of the input images. A modified version of the U...

In this study, we have tailored a pixel tracking method for temporal extrapolation of the ventricular segmentation masks in cardiac magnetic resonance images. The pixel tracking process starts from the end-diastolic frame of the heart cycle using the available manually segmented images to predict the end-systolic segmentation mask. The superpixels...

Pore network is regarded as one of the most important aspects of FCC (Fluid Catalytic Cracking) catalysts for delivering reactants to active sites and transporting out products, and the structure of which can significantly influence the process efficiency. In this work, six characterization methods complementing each other were employed to study th...

Data science as a flourishing interdisciplinary domain of computer and mathematical sciences is playing an important role in guiding the porous material research streams. In the present narrative review, we have examined recent trends and issues in data-driven methods used in the image-based porous material research studies relevant to water resour...

In this study, we present three methods of predicting CO2 adsorption upon displacing CH4 in dehydrated fractured shale samples. These methods include a dynamic numerical approach, a steady state numerical approach, and a machine learning (ML)-based approach. We develop a coupled formulation for including the effects of gas competitive adsorption, d...

Permeability characterises flow in porous rocks/media for upscaling, while steady-state flow fields allow analysis of reactive transport, fines migration, and tight unconventional rocks. Fast calculation of permeability and flow fields obtained from Pore Network Models (PNM) and Laplace Semi-Analytical Solvers (SAS) deviate from computationally dem...

Conventional flow models based on Darcy's flow physics fail to model shale gas production data accurately. The failure to match field data and laboratory-scale evidence of non-Darcy flow has led researchers to propose various gas-flow models for the shale reservoirs. There is extensive evidence that suggests the size of the pores in shale is micros...

Drainage and diffusive coarsening are strongly interrelated mechanisms, which need to be studied in conjunction to acquire a thorough understanding of foam dynamics and stability. We show that microcomputed tomography (μ-CT) and pore network modeling (PNM) are valuable tools to characterize foam dynamics. Unlike existing technologies, the presented...

Coal is not only a combustible black sedimentary rock, but also a source and reservoir rock for natural gas, known as coal seam gas (CSG). A thorough understanding of gas transport through coal matrix micropores as well as coal cleats is of significance in both mining and CSG industries. Multiple physical mechanisms are identified during gas flow i...

Understanding fluid flow in complex fractured porous media requires an accurate representation of the pore space, especially in the presence of both granular pores and fractures, which significantly differ in their geometries. The effect of such a complex fluid pathway is prominent in fractured sandstones and carbonates, which store a significant a...

DeePore is a deep learning workflow for rapid estimation of a wide range of porous material properties based on the binarized micro–tomography images. By combining naturally occurring porous textures we generated 17,700 semi–real 3–D micro–structures of porous geo–materials with size of 2563 voxels and 30 physical properties of each sample are calc...

Significance Solute transport in porous materials is pertinent to many engineering and industrial applications. This research provides direct characterization of spatiotemporal behavior of solute transport in saturated and unsaturated porous media using high-resolution four-dimensional synchrotron X-ray imaging. This research has two key impacts: 1...

Though many studies pertaining to heap leaching have been carried out to study the reaction kinetics in cylindrical columns, in the scaled up variants the extraction efficiency has not always complemented the laboratory expectations. Since heap leaching is a hydrometallurgical process, the reactions are contingent on the effective interactions betw...

X-ray computed tomography (XCT) is a non-destructive 3-D imaging technique that permits visualisation of the internal structure within a sample, avoiding the stereological error found in conventional two-dimensional (2-D) image analysis. Its small-scale variant, in the present manuscript, referred to as X-ray micro-computed tomography (XMT) but mor...

DeePore is a deep learning workflow for rapid estimation of a wide range of porous material properties based on the binarized micro-tomography images. We generated 17700 semi-real 3-D micro-structures of porous geo-materials and 30 physical properties of each sample are calculated using physical simulations on the corresponding pore network models....

In this study, a novel triple pore network model (T-PNM) is introduced which is composed of a single pore network model (PNM) coupled to fractures and micro-porosities. We use two stages of the watershed segmentation algorithm to extract the required data from semi-real micro-tomography images of porous material and build a structural network compo...

Aggregates are the structural units of soils, and the physical stability is considered to be a keystone parameter of soil quality. However, little is known about the evolution of the pore system in aggregates and its importance in defining aggregate stability. In this paper, we investigated the pore system and stability of three dominant macroaggre...

Interphase mass‐transfer or dissolution coefficient of non‐aqueous phase liquids (NAPL) is an important parameter in predicting the transport of contaminant species in porous media. While the literature offers valuable insights into the dependence of this coefficient on different parameters at the continuum scale (e.g., contaminant saturation, Darc...

Pore network models (PNMs) offer a computationally efficient way to analyse transport in porous media. Their effectiveness depends on how well they represent the topology and geometry of real pore systems, for example as imaged by X-ray CT. The performance of two popular algorithms, maximum ball and watershed, is evaluated for three porous systems:...

Image-based Throat Permeability Model: Image-based tube/throat permeability model is a mean to find the absolute permeability of a tube with arbitrary cross-section this function can use 4 methods for estimating the absolute permeability: 1) Lattice Boltzmann simulation, 2) An artificial neural network with 1 input parameter, 3) Another artificia...

In this paper, a permeability calculation workflow is presented that couples pore network modeling (PNM) with a Lattice Boltzmann Method (LBM) to benefit from the strengths of both approaches. Pore network extraction is implemented using a watershed segmentation algorithm on 12 three-dimensional porous rock images. The permeabilities of all throats...

Advancement of X-ray micro-computed tomography (micro-CT) imaging technologies demands more efficient numerical methods that are capable of handling huge 3D images of porous material. We present a workflow for extraction of a pore network model using domain decomposition. This method enables us to analyze huge micro-CT images with minimal computati...

Filtrate and solid invasion from drilling fluids are two key sources of formation damage, and can result in formation permeability impairment. Typically, spurt invasion of mud solids causes the evolution of an external mud cake which tends to reduce further solids and filtrate influx. However, uncontrolled spurt and filtrate invasion are detrimenta...

Changes of morphological parameters of oil shale under thermal conditions are investigated. Analyses are based on 26 micro-computed tomography (micro-CT) images of Green River immature shale rock available under creative commons license. Several image processing and characterization algorithms are applied to sequential high-resolution micro-CT imag...

Since developing the first discovered reservoirs in the United States with sucker rod pumps to the modern deep-water oil production in frozen arctic areas, we concern the improvement of hydrocarbon recovery. Improved Hydrocarbon Recovery is not a new concept while it is studied in the present book through a new point of view. Instead of classic pre...

Petrography and image analysis have been widely used to identify and quantify porous characteristics in carbonate reservoirs. This paper uses the thin section images of 200 carbonate rock samples to predict the absolute permeability using intelligent and empirical methods. For each thin section, several pore network parameters are extracted from th...

In the present paper, a dynamic modeling is presented for deposition of the mud solid particles over and through the porous sandstones during permeability plugging experiments. Scanning electron microscopy (SEM) coupled with image processing are utilized to find the porosity and pore size distribution of the mud cake. The structure of the porous ro...

In this paper, the effect of highly conductive copper oxide nanoparticles on the effective thermal conductivity (ETC) of rock samples was mathematically investigated. To solve the governing conservation equations for the ETC a commercial finite element package (COMSOL Multiphysics) was used. It should be stressed that the single-phase approach was...

This study presents a novel approach for bundle of tubes modeling of permeability impairment due to asphaltene-induced formation damage attenuated by ultrasound which has been rarely attended in the available literature. Model uses the changes of asphaltene particle size distribution (APSD) as a function of time due to ultrasound radiation, while c...

The grain-size distribution (GSD) of porous rocks is important in order to better understand their hydrodynamic behavior. Clear and precise GSD data can be used to computationally reconstruct rock structure for further analysis. In this study, three main algorithms for image analysis have been examined to estimate the GSD of clastic rocks. The main...

Using 3-D scanned data to analyze and extract pore network plays a vital role in investigation of porous media's chrateristics. In this paper, a new simple method is developed to detect pores and throats for analyzing the connectivity and permeability of the network. This automated method utilizes some of the common and well-known image processing...

Specific surface is an important parameter for predicting permeability of porous rocks. Many digital methods have been invented to extract the rock properties via imaging such as Micro-CT. With utilizing 3D volume data, this helps in precise investigation; however, it is neither economically efficient nor can be applied for different situations. In...

Although there are evidences on efficiency of the ultrasonic waves in asphaltene damage removal, a little is known about the modeling of permeability enhancement due to ultrasonic waves radiation towards the asphaltene-induced damaged formations. This study presents a novel analytical stimulation on formation asphaltene damage with an approach to t...

Fractures are the vital arteries of the reservoir. In the low permeability formations such as tight carbonates and shale gases, fracture conductance plays an undeniable role. In the present study, a computational method in rock surface reconstruction has been presented in order to consider the effect of rock roughness in the fracture permeability....