The term "tight reservoir" is commonly used to refer to reservoirs with low permeability. Tight oil reservoirs have caused worry owing to its considerable influence upon oil output throughout the petroleum sector. As a result of its low permeability, producing from tight reservoirs presents numerous challenges. Because of their low permeability, producing from tight reservoirs is faced with a variety of difficulties. The research aim is to performing hydraulic fracturing treatment in single vertical well in order to study the possibility of fracking in the Saady reservoir. Iraq's Halfaya oil field's Saady B reservoir is the most important tight reservoir. The diagnostic fracture injection test is determined for HF55using GOHFER software. Models for petrophysics and geology were calibrated using the diagnostic fracture injection test results after the petrophysical and geomechanical parameters of the rock have been determined. The HF55 vertical well, which penetrates the Saady reservoir, has well logs that have been used to evaluate the petrophysical and geomechanical parameters. These estimates have been supported by findings from the diagnostic fracture injection test through the utilization of standard equations and correlations. The findings of the diagnostic fracture injection test, often known as the diagnostic fracture injection test, are very compatible with the findings of the well logs. The diagnostic fracture injection test pre-falloff test event was examined to determine the instantaneous shut-in pressure and fracture gradient. In the meantime, Closure pressure, process zone stress, fracturing fluid efficiency, closure gradient, critical fissure opening pressure, storage correction factor, permeability, and pressure-dependent leak-off coefficient were all determined using the G function on plot. With the help of a specific software, the petrophysical and geomechanical properties of a single vertical well [HF55] was found. Saady B reservoir's upper and lower sections, along with it are therefore predicted to have the full range of petrophysical and geomechanical features. With the use of DFIT analysis, these features serve as the foundation for developing fracturing models.
Multipoint forming process is an engineering concept which means that the working surface of the punch and die is produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, and a lot of expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. This paper presents an experimental investigation of the effect of three main parameters which are blank holder, rubber thickness and forming speed th
... Show MoreObjective: To evaluate the clinical significance of open diagnostic testicular biopsy as prognostic predictor of
successful sperm retrieval among azoospermic infertile patients.
Design: Prospective study.
Setting: Infertility clinic and assisted reproduction unit at the institute of embryo research and infertility
treatment, Baghdad University.
Patients: Sixty infertile azoospermic patients.
Intervention: Pieces of testicular tissue taking during open diagnostic multiple bilateral testicular biopsies was
prepared for histological examination and grouped according to well-defined histopathological patterns.
Measurement of testicular size and serum reproductive hormones (FSH, LH, Testosterone, and PRL) were done
In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation) structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of these procedures and compare them using generated data.
Through recent years many researchers have developed methods to estimate the self-similarity and long memory parameter that is best known as the Hurst parameter. In this paper, we set a comparison between nine different methods. Most of them use the deviations slope to find an estimate for the Hurst parameter like Rescaled range (R/S), Aggregate Variance (AV), and Absolute moments (AM), and some depend on filtration technique like Discrete Variations (DV), Variance versus level using wavelets (VVL) and Second-order discrete derivative using wavelets (SODDW) were the comparison set by a simulation study to find the most efficient method through MASE. The results of simulation experiments were shown that the performance of the meth
... Show MorePermeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy
... Show MoreChannel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T
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