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Relative permeability curves. e permeability to oil at the irreducible water saturation is about 40% of the absolute permeability. ese curves come from digital simulations.
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Digital experiments were conducted to define permeability that played a key role in reservoir flow simulation. It was revealed that absolute and relative permeability were key inputs for such flow simulation. The absolute permeability k Absolute was defined from Darcy's equation and it was observed that theoretically absolute permeability depended...
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Context 1
... permeability is usually plotted versus S w . Because these fl uxes of the fl uid phases at partial saturation are smaller than the fl ux measured in a sample fully saturated with water or oil, the relative permeability is always smaller than 1 and larger than or equal to 0. Typical k ro and k rt versus S w curves produced by digital two-phase fl ow simulations are displayed in Figure 2. ey are very similar to those obtained in the physical laboratory. ...
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... eff ect on oil recovery can be captured by a single value that is the harmonic average of the relative permeability to oil k ro in the direction of the chan- nel. By assuming that k ro is 0.4 of k Absolute at S wi (as shown in Figure 2), we calculate this value as 330 mD for the large-grain scenario and 130 mD for the small-grain scenario-a factor of 2.5 diff er- ence that will certainly aff ect the reservoir modeling and produc- tion forecast. ...
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... Comparison between rock porosity and permeability of this work and the literature (data from Shenhav, 1971;Strandenes, 1991;Blangy, 1992;Dvorkin et al., 2009). ...
In this day and age, the performance of oil and gas wells is severely affected by downhole and reservoir geomechanical problems. The key factor in predicting and solving these problems is a detailed study of the various aspects of the compressive and tensile behavior of the reservoir rock. In this study, the influence of mean sand grain size distribution as an important parameter influencing the petrophysical and geomechanical properties of the rock has been investigated using synthetic sandstone core samples. The results show that increasing the grain size range from 0.1 to 0.2 mm to 0.1–0.8 mm would result in a 23% and 64% decrease in rock porosity and permeability, respectively. However, such an unfavorable trend would be mitigated by the removal of fine particles from the rock composition. According to the results, there is a critical range of sand grains (i.e., 0.2–0.6 mm) above which rock permeability would be severely affected by a change in grain size. At the same compressive stress, the fine sandstones showed a more compressive deformation compared to the coarse specimens. In this regard, a direct relationship between rock compressive strength/Young's modulus and sand grain size was found. The results also indicate that fracture in the fine specimen initiates at lower stress conditions than in the coarse sample. This implies that the weakest grain to grain boundary (GGB) is weaker in the fine-grained samples than in the coarse-grained specimens.
... So, it is required to adopt higher resolution scanning methods, such as nano-CT (Tan et al. 2019), scanning electron microscope (SEM) (Andrä et al. 2013a(Andrä et al. , 2013bYue et al. 2011;Nie et al. 2016;Kelly et al. 2016), and MAPS . For rocks with small pore size and strong heterogeneity, the contradiction between image resolution and the rock size is a major challenge in numerical simulation of rock physical properties (Dvorkin et al. 2009a;Dvorkin and Nur 2009b;Kong et al. 2015). To solve it, a new approach to reconstruct 3D digital rock is the combination of multiple scanning experiments, such as a combination of static and dynamic micro-CT, SEM, and energy dispersive X-ray spectroscopy (Fogden et al. 2015), and a combination of micro-CT at different resolutions (Cui et al. 2020), which is more accurate than the traditional single scanning experiment. ...
The development of hot-dry rock (HDR) resources relies on the accurate evaluation of acoustic properties. The acoustic properties are usually measured by rock physical experiments. However, the high-temperature heating experiment is difficult because of high costs, long time-consumption, and complex operations. Hence, digital rock physics (DRP), a less time-consuming and more economical way, is used to analyze the acoustic properties. Here, multiple scanning experiments, including X-ray computed tomography (X-ray CT) for reconstructing 3D model, quantitative evaluation of materials by scanning electron microscopy (QEMSCAN), and modular automated processing system (MAPS), are conducted, and a fusion method of multiple scanning images is proposed to solve the contradiction between image resolution and the sample size caused by small pore size and complex mineral distribution and to generate the multiscale multicomponent digital rock. Then, the acoustic numerical modeling at high temperatures is conducted, where the essential idea is to derive the theoretical correlation between the elastic moduli of the minerals and the temperatures to obtain the elastic moduli of minerals at different temperatures. Finally, the acoustic properties of the digital rock are calculated, and the microscopic mechanism at high temperatures is studied in detail. The simulating results demonstrate that bulk modulus, shear modulus, Poisson's ratio, Young's modulus, P-wave velocity, and S-wave velocity decrease as the temperature rises. More importantly, the thermal cracking behavior of HDR is represented, and fractal Brown motion is utilized to generate the fractured digital rock. The simulation results of fractured digital rock illustrate that it is the fracture to cause rapid decline of acoustic properties after 250℃. Overall, this pore-scale work accurately illustrates the acoustic properties of HDR and provides a new idea to study the rock physics properties at high temperatures and a microscopic interpretation for geothermal fracturing development.
... So, it is required to adopt higher resolution scanning methods, such as nano-CT (Tan et al. 2019), scanning electron microscope (SEM) (Andrä et al. 2013a(Andrä et al. , 2013bYue et al. 2011;Nie et al. 2016;Kelly et al. 2016), and MAPS . For rocks with small pore size and strong heterogeneity, the contradiction between image resolution and the rock size is a major challenge in numerical simulation of rock physical properties (Dvorkin et al. 2009a;Dvorkin and Nur 2009b;Kong et al. 2015). To solve it, a new approach to reconstruct 3D digital rock is the combination of multiple scanning experiments, such as a combination of static and dynamic micro-CT, SEM, and energy dispersive X-ray spectroscopy (Fogden et al. 2015), and a combination of micro-CT at different resolutions (Cui et al. 2020), which is more accurate than the traditional single scanning experiment. ...
The development of hot-dry rock (HDR) resources relies on the accurate evaluation of acoustic properties. The acoustic properties are usually measured by rock physical experiments. However, the high-temperature heating experiment is difficult because of high costs, long time-consumption, and complex operations. Hence, digital rock physics (DRP), a less time-consuming and more economical way, is used to analyze the acoustic properties. Here, multiple scanning experiments, including X-ray computed tomography (X-ray CT) for reconstructing 3D model, quantitative evaluation of materials by scanning electron microscopy (QEMSCAN), and modular automated processing system (MAPS), are conducted, and a fusion method of multiple scanning images is proposed to solve the contradiction between image resolution and the sample size caused by small pore size and complex mineral distribution and to generate the multiscale multicomponent digital rock. Then, the acoustic numerical modeling at high temperatures is conducted, where the essential idea is to derive the theoretical correlation between the elastic moduli of the minerals and the temperatures to obtain the elastic moduli of minerals at different temperatures. Finally, the acoustic properties of the digital rock are calculated, and the microscopic mechanism at high temperatures is studied in detail. The simulating results demonstrate that bulk modulus, shear modulus, Poisson’s ratio, Young’s modulus, P-wave velocity, and S-wave velocity decrease as the temperature rises. More importantly, the thermal cracking behavior of HDR is represented, and fractal Brown motion is utilized to generate the fractured digital rock. The simulation results of fractured digital rock illustrate that it is the fracture to cause rapid decline of acoustic properties after 250℃. Overall, this pore-scale work accurately illustrates the acoustic properties of HDR and provides a new idea to study the rock physics properties at high temperatures and a microscopic interpretation for geothermal fracturing development.
... La petrofísica digital surge como una alternativa que permite extraer información a partir de la adquisición de imágenes digitales de la roca en cuestión. Históricamente, las dos limitantes principales que impedían el desarrollo de esta tecnología eran la capacidad de producir imágenes en alta resolución y la habilidad de ejecutar operaciones de cómputo a una alta velocidad (Dvorkin et al., 2009). Actualmente, existen instrumentos que escanean digitalmente en alta resolución y clusters computacionales que permiten ejecutar procesos de simulación en tiempos económicamente viables. ...
Los yacimientos no convencionales (roca generadora) representan una nueva etapa en la exploración y explotación de petróleo y gas a nivel mundial, y su caracterización petrofísica sigue siendo un desafío, debido a las bajas permeabilidades, los altos niveles de heterogeneidad y la dificultad de adaptación de las técnicas convencionales. La petrofísica digital surge como una alternativa que aprovecha los últimos avances en la microscopía electrónica, la tomografía computarizada y el procesamiento computacional para, a través de métodos numéricos y algoritmos de conteo de vóxel, estimar las propiedades petrofísicas en lo que se denomina un modelo de roca digital. En este trabajo se realiza una revisión de las técnicas de caracterización digital y su aplicación en muestras de yacimientos no convencionales pertenecientes a la Formación Vaca Muerta (Argentina) y Formación La Luna (Colombia). Con esta tecnología es posible visualizar el espacio poroso a escala micro- y nanométrica, con el fin de obtener información cualitativa (tipos de poro y microfracturas) y cuantitativa (porosidad, permeabilidad absoluta, distribución de tamaño de poro, cantidad de materia orgánica y propiedades petrofísicas avanzadas). Los resultados obtenidos indican que las muestras FIB-SEM se encuentran por debajo del volumen elemental representativo y que las muestras digitales con mayores dimensiones, aunque más representativas, requieren de una mayor capacidad computacional. El escalamiento de las propiedades petrofísicas, la falta de conectividad del medio poroso y la baja representatividad son las principales limitantes presentes en la tecnología. Sin embargo, su potencial aumenta conforme la inteligencia artificial, la simulación y el machine learning toman fuerza en la industria del petróleo.
... The pore-scale numerical simulations are necessary for theoretically comprehensive analysis. Dvorkin et al. (2009), 2012, Yue et al. (2011), Faisal et al. (2017 used the numerical simulation method to study various rock physical properties, including electrical properties, acoustic properties, and permeability. Nowadays, the finite element method (FEM) is an extensively used method to study electrical properties. ...
Fractures are common in carbonate formations, and it is challenging to characterize electrical properties and establish saturation models for the fractured rocks by conventional petrophysical experiments. Therefore, it is necessary to study the fractures' electrical conduction and establish water saturation models by pore-scale numerical simulation and microscopic analyses. First, a multi-composition digital rock is constructed by the X-ray CT scan, Maps, and quantitative evaluation of minerals by scanning electron microscopy multi-scale supporting experiments. Next, the fractal Brown motion is used to construct the fractured digital rocks, and the lattice Boltzmann method is used to simulate the oil-water distribution. Then, the resistivities of these digital rocks are calculated by the finite element method. Finally, the microscopic response mechanism of the electrical properties is studied in detail, and new water saturation models are established. The study shows that resistivity decreases as the fracture aperture, length, or quantities increase. Still, it has different changes in three directions with the rise of the fracture dip, indicating the fractures lead to electrical anisotropy of the rock. Additionally, the resistivity index (RI) is strongly correlated to the water saturation (Sw). In the highly water-saturated region, the RI-Sw curve conforms to Archie's law. However, the RI-Sw curve bends in the lowly water-saturated region, revealing the so-called ‘non-Archie’ behavior. Hence, we established new saturation models for fractured carbonate rocks and use one of the saturation models to calculate water saturation for formation evaluation in Tahe Oilfield. The calculated results are more consistent with the oil test results, demonstrating the proposed saturation model is more applicable in the fractured formation. In summary, the pore-scale numerical simulation in fractured carbonate rocks provides a microscopic theoretical basis for electrical mechanism analysis and a water saturation model for log interpretation.
... One of the main applications of DRP is creating advanced numerical models capable of simulating the core analysis experiments and estimating a wide range of parameters at an affordable expense and short time (Arns et al., 2005;Andrä et al., 2013). These models are still under development, showing the importance of verification and control of the growth based on prepared standard datasets (Dvorkin et al., 2009). ...
This study aims to present a simple method to calculate the permeability of porous materials using μ-CT images and an approximation based on the solution of Laplace's equation for pressure. For this purpose, an in-house computer program was developed based on finite difference method to determine the distribution of pressure in voxelated pore space. Afterwards, approximate permeability was obtained using Euclidean distance map of the pore space and a simple upscaling scheme for a range of porous media including idealized channels of elementary cross sections, Boolean models of spherical grains, bundles of capillary tubes and digital rocks obtained from μ-CT imaging. Next, a comparison was made between the Laplace permeability approximation and the analytical solutions of idealized microstructure and digitally-computed permeability of a number of rock samples using the Stokes solver and the lattice-Boltzmann method. It has been revealed that the estimated permeability values are in good agreement over the investigated range of porosity. The developed Laplace permeability solver was also well matched with the results of experimental measurement on a real rock sample. As an illustration of the applicability of the proposed method, the anisotropy of permeability at pore scale and the cross-correlation between permeability and connected macro-porosity was analyzed for the experimentally investigated rock sample. In conclusion, the results of this paper suggest that the proposed permeability solver is suitable for rough estimation of permeability and hence rough evaluation of heterogeneity/anisotropy from μ-CT images of rocks, particularly for large datasets with high number of pore voxels.
... In this manner, high resolution X-ray computed tomography (micro-CT) has become a standard technique in reservoir characterization workflows [5,11,27] because it allows for a representative description of microstructure and contributes to the understanding of the physical phenomena of fluid flow [13,38] and estimation of mechanical properties [6,28]. ...
In addition to the ongoing development, pre-salt carbonate reservoir characterization remains a challenge, primarily due to inherent geological particularities. These challenges stimulate the use of well-established technologies, such as artificial intelligence algorithms, for image classification tasks. Therefore, this work intends to present an application of deep learning techniques to identify lithological patterns in Brazilian pre-salt carbonate rocks using microtomographic images. Four convolutional neural network models were proposed. The first model includes three convolutional layers, followed by a fully connected layer. This model is used as a base model for the following proposals. In the next two models, we replace the max pooling layer with a spatial pyramid pooling and a global average pooling layer. The last model uses a combination of spatial pyramid pooling followed by global average pooling in place of the final pooling layer. All models are compared using original images, when possible, as well as resized images. The dataset consists of 6,000 images from three different classes. The model performances were evaluated by each image individually, as well as by the most frequently predicted class for each sample. According to accuracy, Model 2 trained on resized images achieved the best results, reaching an average of 75.54% for the first evaluation approach and an average of 81.33% for the second. We developed a workflow to automate and accelerate the lithology classification of Brazilian pre-salt carbonate samples by categorizing microtomographic images using deep learning algorithms in a non-destructive way.
... DRP technology can characterize the microstructure of rock at the pore scale and allow a quantitatively study of the relation between rock physical parameters and rock physical properties. Dvorkin et al. (2009) andKuntz et al. (2000) used digital cores to study various rock physical properties (DRP), including acoustic properties, electrical properties, nuclear magnetic resonance relaxation, and permeability. With the development of CT scanning technology, DRP technology has progressed rapidly. ...
The development and stimulation of oil and gas fields are inseparable from the experimental analysis of reservoir rocks. Large number of experiments, poor reservoir properties and thin reservoir thickness will lead to insufficient number of cores, which restricts the experimental evaluation effect of cores. Digital rock physics (DRP) can solve these problems well. This paper presents a rapid, simple, and practical method to establish the pore structure and lithology of DRP based on laboratory experiments. First, a core is scanned by computed tomography (CT) scanning technology, and filtering back-projection reconstruction method is used to test the core visualization. Subsequently, three-dimensional median filtering technology is used to eliminate noise signals after scanning, and the maximum interclass variance method is used to segment the rock skeleton and pore. Based on X-ray diffraction technology, the distribution of minerals in the rock core is studied by combining the processed CT scan data. The core pore size distribution is analyzed by the mercury intrusion method, and the core pore size distribution with spatial correlation is constructed by the kriging interpolation method. Based on the analysis of the core particle-size distribution by the screening method, the shape of the rock particle is assumed to be a more practical irregular polyhedron; considering this shape and the mineral distribution, the DRP pore structure and lithology are finally established. The DRP porosity calculated by MATLAB software is 32.4%, and the core porosity measured in a nuclear magnetic resonance experiment is 29.9%; thus, the accuracy of the model is validated. Further, the method of simulating the process of physical and chemical changes by using the digital core is proposed for further study.
... In this manner, micro-CT has become a standard technique in reservoir characterization workflows [27,5,11] because it allows for a representative description of microstructure and contributes to the understanding of the physical phenomena of fluid flow [13,38] and estimation of mechanical properties [6,28]. ...
In addition to the ongoing development, pre-salt carbonate reservoir characterization remains a challenge, primarily due to inherent geological particularities. These challenges stimulate the use of well-established technologies, such as artificial intelligence algorithms, for image classification tasks. Therefore, this work intends to present an application of deep learning techniques to identify patterns in Brazilian pre-salt carbonate rock microtomographic images, thus making possible lithological classification. Four convolutional neural network models were proposed. The first model includes three convolutional layers followed by fully connected layers and is used as a base model for the following proposals. In the next two models, we replace the max pooling layer with a spatial pyramid pooling and a global average pooling layer. The last model uses a combination of spatial pyramid pooling followed by global average pooling in place of the last pooling layer. All models are compared using original images, when possible, as well as resized images. The dataset consists of 6,000 images from three different classes. The model performances were evaluated by each image individually, as well as by the most frequently predicted class for each sample. According to accuracy, Model 2 trained on resized images achieved the best results, reaching an average of 75.54% for the first evaluation approach and an average of 81.33% for the second. We developed a workflow to automate and accelerate the lithology classification of Brazilian pre-salt carbonate samples by categorizing microtomographic images using deep learning algorithms in a non-destructive way.
... Direct numerical simulation on digital pore microstructures has been used in estimating physical properties of rocks such as porosity, permeability, electrical conductivity, and seismic velocity (Arns et al., 2002;Keehm, 2003;Dvorkin et al., 2011;Andrä et al., 2013a). Since it uses realistic pore geometry without significant modification and simplification, this technique has strength in quantifying changes in physical properties and their interrelations for many areas, such as characterization of oil & gas reservoirs, or geological carbon storage (Keehm et al., 2001;Avseth et al., 2005;Dvorkin et al., 2009;Silin et al., 2010;Middleton et al., 2012). This technique typically consists of the acquisition of high-resolution pore microstructures and the numerical calculation using pore-scale simulators. ...
Numerical estimation of physical properties from digital pore microstructures has drawn great attention and is being used for quantifying interrelation between various physical properties. The pore microstructures are commonly obtained by the X-ray microtomographic technique, which can give fairly accurate pore geometry. However, there is minor distortion due to the limited resolution or smoothing. This distortion can cause errors in estimating physical properties by pore-scale simulation techniques. Among the properties, seismic velocity would have relatively large errors since a small amount of change in grain contacts can cause significant over-estimation. In this paper, we analyzed the errors in seismic velocity by resolution and smoothing of pore geometry using three samples: an unconsolidated sand pack and two medium-porosity sandstones with different degrees of consolidation. As the resolution becomes poor, the calculated velocity increases linearly, while smoothing gives nonlinear trends; higher errors in the early stage of smoothing. As we expected, soft rocks have higher sensitivity, since the grain contacts are small and are sensitive to minor distortion. Within similar ranges, the resolution causes larger errors than smoothing. In addition, smoothing does not cause velocity over-estimation once the resolution becomes poor, while the resolution can create considerable errors in velocity even after significant smoothing. We conclude that the resolution should be considered in the first place when obtaining digital pore microstructures to minimize errors in velocity estimation. We can also suggest that a good care should be taken when applying smoothing filters, if a sample is suspected to be poorly-consolidated or to have high porosity. © 2017 The Association of Korean Geoscience Societies and Springer-Verlag Berlin Heidelberg
