Description of Fracture Network of Hydraulic Fracturing Vertical Wells in Unconventional Reservoirs

Based on the distribution of complex fractures after volume fracturing in unconventional reservoirs, the fractal theory is used to describe the distribution of volume fracture network in unconventional reservoirs. The method for calculating the fractal parameters of the fracture network is given. The box dimension method is used to analyze a fracturing core, and the fractal dimension is calculated. The fractal index of fracture network in fracturing vertical wells are also firstly calculated by introducing an analysis method. On this basis, the conventional dual-media model and the fractal dual-media model are compared, and the distribution of reservoir permeability and porosity are analyzed. The results show that the fractal porosity/permeability can be used to describe the reservoir physical properties more accurately. At the same time, the flow rate calculating by conventional dual-media model and the fractal dual-media model were calculated and compared. The comparative analysis found that the flow rate calculated by the conventional dual-media model was relatively high in the early stage, but the flow rate was not much different in the later stage. The research results provide certain guiding significance for the description of fracture network of volume fracturing vertical well in unconventional reservoirs.

Towards Efficient Big Data Storage With MapReduce Deduplication System

In the big data era, there is a high requirement for data storage and processing. The conventional approach faces a great challenge, and de-duplication is an excellent approach to reduce the storage space and computational time. Many existing approaches take much time to pinpoint the similar data. MapReduce de-duplication system is proposed to attain high duplication ratio. MapReduce is the parallel processing approach that helps to process large number of files in less time. The proposed system uses two threshold two divisor with switch algorithm for chunking. Switch is the average parameter used by TTTD-S to minimize the chunk size variance. Hashing using SHA-3 and fractal tree indexing is used here. In fractal index tree, read and write takes place at the same time. Data size after de-duplication, de-duplication ratio, throughput, hash time, chunk time, and de-duplication time are the parameters used. The performance of the system is tested by college scorecard and ZCTA dataset. The experimental results show that the proposed system can lessen the duplicity and processing time.

Fractal Pull-in Stability Theory for Microelectromechanical Systems

Pull-in instability was an important phenomenon in microelectromechanical systems (MEMS). In the past, MEMS were usually assumed to work in an ideal environment. But in the real circumstances, MEMS often work in dust-filled air, which is equivalent to working in porous media, that's mean fractal space. In this paper, we studied MEMS in fractal space and established the corresponding model. At the same time, we can control the occurrence time and stable time of pull-in by adjusting the value of the fractal index, and obtain a stable pull-in phenomenon.

Laboratory Investigation on Particle Breakage Characteristics of Calcareous Sands

Many studies have demonstrated the fragility of calcareous sands even under small stresses. This bears an adverse influence on their engineering properties. A series of laboratory tests were carried out on poor-graded calcareous sands to investigate the crushability mechanism. Einav’s relative breakage and fractal dimension were used as the particle breakage indices. The results show that the particles broke into smaller fragments at the low-stress level by attrition which was caused by friction and slip between particles. In contrast, particles broke in the form of crushing at the relatively higher stresses. The evolution of the particle size was reflected by the variation in Einav’s relative breakage and fractal dimension. As testing commenced, the breakage index rapidly increased. When the stress was increased to 400 kPa, the rate of increase in the breakage index was retarded. As the stress was further increased beyond 800 kPa, the rate of increase in the fractal index became much smaller. This elucidated that the well-graded calcareous sands could resist crushing depending on the range of applied stresses. Based on the test findings, a new breakage law is proposed.

Clasificación Automática de Sujetos con Deterioro Cognitivo Leve mediante la Caracterización Fractal 3D en Imágenes Cerebrales de Resonancia Magnética

Sixty brain volumes were analyzed from separate magnetic resonance images in two populations: healthy control subjects and subjects with mild cognitive impairment. For each element, the Box Counting algorithm was applied to obtain the characterization of the 3D Fractal Dimension that it presented. In addition, other morphological indices of volume, discrete compactness and surrounding area were added. Finally, a classification strategy is implemented using the Gaussian Process with a radial-based Kernel to compare the correct discrimination in the populations studied. The classifier model after the validation process gave a 60% success rate for the fractal dimension and for the morphological indices. The highest hit rate was when both metrics were combined with 80%. With these results, it is believed that the fractal index could become a biomarker for the prediagnosis of Alzheimer's disease, although for this, more studies are needed in the future.

An index of the fractal characteristic of an airway tree is associated with airflow limitations and future body mass index reduction in COPD patients

An airway tree is a fractal object. We showed that the distribution of minimal inner cross-sectional area (iCSA) of airway branches can be expressed by a fractal index, D, of minimal iCSA. This D was correlated with airflow limitation and future body mass index reduction in chronic obstructive pulmonary disease patients, as predicted by Hess–Murray’s law.

FRACTAL ANALYSIS OF TEMPERATURE TIME SERIES FROM BATCH SUGARCANE CRYSTALLIZATION

Batch crystallization is an important process in many industries, for example, fine chemicals, foods, and pharmaceuticals. Monitoring of the main process variables is essential for process understanding, diagnosis, and for product quality control. It is known that temperature has a critical effect on crystallization. Temperature measurements from crystallization systems display fluctuations with apparently random and complex behavior. Fractal analysis of complex time series has received significant attention in the last few years due to its capability for extraction of hidden useful information of the underlying phenomena behind the time-series complexity. In this work, the potential of fractal analysis of time series for diagnosis of industrial crystallization processes is investigated using temperature measurements from a typical batch sugarcane crystallization system. The crystallizer was operated at different cooling profiles, finding that fractal index is directly related to crystal mean diameter dynamics. Thus, we establish that fractal analysis is a simple and robust alternative for the characterization of batch crystallization.