Search results for: Taylor dispersion

Authors: Joanna Szymanska, Paulina Wawulska-Marek, Jaroslaw Mizera

Abstract:

Nowadays, the rapid growth of global energy consumption and uncontrolled depletion of natural resources become a serious problem. Shale rocks are the largest and potential global basins containing hydrocarbons, trapped in closed pores of the shale matrix. Regardless of the shales origin, mining conditions are extremely unfavourable due to high reservoir pressure, great depths, increased clay minerals content and limited permeability (nanoDarcy) of the rocks. Taking into consideration such geomechanical barriers, effective extraction of natural gas from shales with plastic zones demands effective operations. Actually, hydraulic fracturing is the most developed technique based on the injection of pressurized fluid into a wellbore, to initiate fractures propagation. However, a rapid drop of pressure after fluid suction to the ground induces a fracture closure and conductivity reduction. In order to minimize this risk, proppants should be applied. They are solid granules transported with hydraulic fluids to locate inside the rock. Proppants act as a prop for the closing fracture, thus gas migration to a borehole is effective. Quartz sands are commonly applied proppants only at shallow deposits (USA). Whereas, ceramic proppants are designed to meet rigorous downhole conditions to intensify output. Ceramic granules predominate with higher mechanical strength, stability in strong acidic environment, spherical shape and homogeneity as well. Quality of ceramic proppants is conditioned by raw materials selection. Aim of this study was to obtain the proppants from aluminosilicates (the kaolinite subgroup) and mix of minerals with a high alumina content. These loamy minerals contain a tubular and platy morphology that improves mechanical properties and reduces their specific weight. Moreover, they are distinguished by well-developed surface area, high porosity, fine particle size, superb dispersion and nontoxic properties - very crucial for particles consolidation into spherical and crush-resistant granules in mechanical granulation process. The aluminosilicates were mixed with water and natural organic binder to improve liquid-bridges and pores formation between particles. Afterward, the green proppants were subjected to sintering at high temperatures. Evaluation of the minerals utility was based on their particle size distribution (laser diffraction study) and thermal stability (thermogravimetry). Scanning Electron Microscopy was useful for morphology and shape identification combined with specific surface area measurement (BET). Chemical composition was verified by Energy Dispersive Spectroscopy and X-ray Fluorescence. Moreover, bulk density and specific weight were measured. Such comprehensive characterization of loamy materials confirmed their favourable impact on the proppants granulation. The sintered granules were analyzed by SEM to verify the surface topography and phase transitions after sintering. Pores distribution was identified by X-Ray Tomography. This method enabled also the simulation of proppants settlement in a fracture, while measurement of bulk density was essential to predict their amount to fill a well. Roundness coefficient was also evaluated, whereas impact on mining environment was identified by turbidity and solubility in acid - to indicate risk of the material decay in a well. The obtained outcomes confirmed a positive influence of the loamy minerals on ceramic proppants properties with respect to the strict norms. This research is perspective for higher quality proppants production with costs reduction.

Keywords: aluminosilicates, ceramic proppants, mechanical granulation, shale gas

Procedia PDF Downloads 142

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

Abstract:

The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

Procedia PDF Downloads 484