Search Results (5)

Previously conducted studies have established that deep underground rock masses have complex pore structures and face complex geological conditions. Therefore, the seepage problem of such rock masses seriously affects engineering safety. To better explore the seepage law of deep rock masses and ensure engineering safety, indoor experimental methods such as casting thin sections, scanning electron microscopy, and mercury intrusion testing were utilized in this study. The microscopic pore shape, size, distribution, and other structural characteristics of sandstone in coal bearing strata were analyzed. The tortuosity calculation formula was obtained by the theoretical derivation method. And a numerical model was established for seepage numerical simulation research through microscopic digital image methods. The seepage law of surrounding rocks in the Tangkou Coal Mine roadway under different conditions is discussed. The research results indicate that the complexity of the pore structure in porous media leads to an uneven distribution of flow velocity and pressure within the medium. Meanwhile, with the change of physical properties, the fluid flow characteristics also undergo significant changes. The research results can effectively guide micropore water blocking, reduce the impact of groundwater on the environment, ensure the environment and safety of the project, and provide guidance for other geological projects. Full article

We investigated the interaction of silica nanostructured particles and sandstone rock using various experimental approaches, such as fluid compatibility, batch sorption and single-phase core-floods. Diol and polyethylenglycol (PEG) surface-modified nanostructured silica materials were tested using two brines differing in ionic strength and with the addition of sodium carbonate (Na₂CO₃). Berea and Keuper outcrop materials (core plug and crushed samples) were used. Core-flood effluents were analysed to define changes in concentration and a rock’s retention compared to a tracer. Field Flow Fractionation (FFF) and Dynamic Light Scattering (DLS) were performed to investigate changes in the effluent’s size distribution. Adsorption was evaluated using UV–visible spectroscopy and scanning electron microscopy (SEM). The highest adsorption was observed in brine with high ionic strength, whereas the use of alkali reduced the adsorption. The crushed material from Berea rock showed slightly higher adsorption compared to Keuper rock, whereas temperature had a minor effect on adsorption behaviour. In core-flood experiments, no effects on permeability have been observed. The used particles showed a delayed breakthrough compared to the tracer, and bigger particles passed the rock core faster. Nanoparticle recovery was significantly lower for PEG-modified nanomaterials in Berea compared to diol-modified nanomaterials, suggesting high adsorption. SEM images indicate that adsorption spots are defined via surface roughness rather than mineral type. Despite an excess of nanomaterials in the porous medium, monolayer adsorption was the prevailing type observed. Full article

Deep neural networks have received considerable attention in clinical imaging, particularly with respect to the reduction of radiation risk. Lowering the radiation dose by reducing the photon flux inevitably results in the degradation of the scanned image quality. Thus, researchers have sought to exploit deep convolutional neural networks (DCNNs) to map low-quality, low-dose images to higher-dose, higher-quality images, thereby minimizing the associated radiation hazard. Conversely, computed tomography (CT) measurements of geomaterials are not limited by the radiation dose. In contrast to the human body, however, geomaterials may be comprised of high-density constituents causing increased attenuation of the X-rays. Consequently, higher-dose images are required to obtain an acceptable scan quality. The problem of prolonged acquisition times is particularly severe for micro-CT based scanning technologies. Depending on the sample size and exposure time settings, a single scan may require several hours to complete. This is of particular concern if phenomena with an exponential temperature dependency are to be elucidated. A process may happen too fast to be adequately captured by CT scanning. To address the aforementioned issues, we apply DCNNs to improve the quality of rock CT images and reduce exposure times by more than 60%, simultaneously. We highlight current results based on micro-CT derived datasets and apply transfer learning to improve DCNN results without increasing training time. The approach is applicable to any computed tomography technology. Furthermore, we contrast the performance of the DCNN trained by minimizing different loss functions such as mean squared error and structural similarity index. Full article

In this paper, we consider an important problem for modeling complex coupled phenomena in porous media at multiple scales. In particular, we consider flow and transport in the void space between the pores when the pore space is altered by new solid obstructions formed by microbial growth or reactive transport, and we are mostly interested in pore-coating and pore-filling type obstructions, observed in applications to biofilm in porous media and hydrate crystal formation, respectively. We consider the impact of these obstructions on the macroscopic properties of the porous medium, such as porosity, permeability and tortuosity, for which we build an experimental probability distribution with reduced models, which involves three steps: (1) generation of independent realizations of obstructions, followed by, (2) flow and transport simulations at pore-scale, and (3) upscaling. For the first step, we consider three approaches: (1A) direct numerical simulations (DNS) of the PDE model of the actual physical process called BN which forms the obstructions, and two non-DNS methods, which we call (1B) CLPS and (1C) LP. LP is a lattice Ising-type model, and CLPS is a constrained version of an Allen–Cahn model for phase separation with a localization term. Both LP and CLPS are model approximations of BN, and they seek local minima of some nonconvex energy functional, which provide plausible realizations of the obstructed geometry and are tuned heuristically to deliver either pore-coating or pore-filling obstructions. Our methods work with rock-void geometries obtained by imaging, but bypass the need for imaging in real-time, are fairly inexpensive, and can be tailored to other applications. The reduced models LP and CLPS are less computationally expensive than DNS, and can be tuned to the desired fidelity of the probability distributions of upscaled quantities. Full article

Understanding the microstructure of rhyolites may greatly promote exploration efforts on rhyolitic hydrocarbon reservoirs; however, related studies are sparse. In this contribution, the microstructure and related porosity of oil-bearing rhyolitic lavas from the Hailar Basin (NE China) were investigated using a combination of optical microscopy, fluorescence image analysis, and scanning electron microscopy. The direct visual and quantitative analyses show that the rhyolites are heterogeneous and porous rocks and have complex microstructures. Phenocryst-rich rhyolitic lava, perlitic lava, and spherulitic rhyolite may be favorable targets for rhyolitic hydrocarbon exploration. For the phenocryst-rich rhyolitic lavas, embayment pores, cleavages, cavitational and shear fractures, and intracrystalline sieve pores are commonly observed in the phenocrysts; while flow-parallel laminar and micropores are ubiquitous in the groundmass. Perlitic lavas are characterized by the occurrence of numerous perlitic fractures which can also be produced in the glassy groundmass of other lavas. Spherulitic rhyolites mainly consist of small-sized (<1 mm) clustered or large-sized (>1 mm) isolated spherulites. Clustered spherulites are characterized by the development of interspherulite pores. Isolated spherulites contain numerous radiating micropores. Both types of spherulites may have water expulsion pores formed in the spherulite–glass border. The formation of the microstructure and related porosity of rhyolites is controlled by pre-, syn- (e.g., deuteric crystal dissolution, cavitation, ductile–brittle deformation, and high-T devitrification), and post-volcanic (e.g., hydration and low-T devitrification) processes. Although pores with diameters > 50 μm are often observed, small pores dominate in pore-size distribution. Small (<15 μm) and large (>300 μm) pores give the most volumetric contribution in most cases. Medium-sized pores with diameters ranging from ~150–300 μm are the least developed and contribute the least to the total volume. The results of this paper can be beneficial to further the understanding of the microstructure and pore system of rhyolites and may be applied to rhyolitic lava hydrocarbon reservoirs elsewhere. Full article