The electric submersible pump, also known as ESP, is a highly effective artificial lift method widely used in the oil industry due to its ability to deliver higher production rates compared to other artificial lift methods. In principle, ESP is a multistage centrifugal pump that converts kinetic energy into dynamic hydraulic pressure necessary to lift fluids at a higher rate with lower bottomhole pressure, especially in oil wells under certain bottomhole condition fluid, and reservoir characteristics. However, several factors and challenges can complicate the completion and optimum development of ESP deployed wells, which need to be addressed to optimize its performance by maximizing efficiency and minimizing costs and uncertainties. To analyze the performance of ESP deployed wells, the objective function must include various factors associated with fluids, reservoir inflow and outflow characteristics, and pump parameters. In particular, the inflow and outflow parameters include well configuration, and types of completion string (e.g. tubing sizes, and download completion hardware) while reservoir and fluid parameters include pressure, temperature, and PVT properties. Pump parameters include gas vacuum fraction, electrical and mechanical constraints, power requirements, cable requirements, downhole conditions, etc. Despite these challenges, ESPs' importance and efficiency necessitate an in-depth understanding of its origins and evolution over time, as well as the difficulties encountered in the oil industry. This paper aims to provide a comprehensive review of ESP's origin and development, including all prior studies that have influenced optimum development. The literature review is divided into four main sections: experimental investigations, numerical simulation studies, mechanical modeling, and in-depth studies on production optimization. By providing an in-depth analysis of previous work in each area, this paper aims to contribute to ongoing efforts to enhance ESPs' performance and efficiency in the oil industry.
Chronic pain is a complex and persistent condition involving sustained nociceptive input, maladaptive neuroplastic changes, and neuroimmune interactions. Central to its pathophysiology is the dysregulation of neuromodulatory signaling pathways, including neurotransmitters (e.g., dopamine, serotonin, norepinephrine), neuropeptides (e.g., substance P, CGRP), and neurotrophic factors (e.g., BDNF), which modulate both central and peripheral sensitization mechanisms. In disorders such as fibromyalgia, altered monoaminergic transmission has been implicated in the attenuation of descending inhibitory control, thereby enhancing pain perception and reducing responsiveness to conventional therapies. Concurrently, neuroinflammation, driven by
... Show MoreHeterocycles are diverse compounds that have importance in medicinal chemistry [ 1, 2]. As part of a class of oxygen-containing benzoheterocycles (fused six membered)[3], coumarins (1) are natural lactones in which the benzene ring and α-pyrone are fused together [ 4] the conjugation of coumarin with different pharmacophores gives many hybrids with various pharmacological activities [5]. Sulfonamides (SN)(2), or sulfanilamides belong to a significant class of synthetic antimicrobial medications that are used as broad-spectrum pharmaceuticals to treat bacterial infections in humans and animals
In this work the structural, electrical and optical Properties of CuO semiconductor films had been studied, which prepared at three thickness (100, 200 and 500 nm) by spray pyrolysis method at 573K substrate temperatures on glass substrates from 0.2M CuCl2•2H2O dissolved in alcohol. Structural Properties shows that the films have only a polycrystalline CuO phase with preferential orientation in the (111) direction, the dc conductivity shows that all films have two activation energies, Ea1 (0.45-0.66 eV) and Ea2 (0.055-.0185 eV), CuO films have CBH (Correlated Barrier Hopping) mechanism for ac-conductivity. The energy gap between (1.5-1.85 eV).
The influence of process speed (PS) and tillage depth (TD) , on growth of corn (Zea mays L) yield, for Maha cultivar, were tested at two ranges of PS of 2.483 and 4.011 km.hr-1, and three ranges of TD of 15,20 and 25cm. The experiments were conducted in a factorial experiment under complete randomized design with three replications. The results showed that the PS of 2.483 km.hr-1 was significantly better than the PS of 4.011km.hr-1 in all studied conditions. The , slippage ratio (SR) and the machine efficiency (ME), the physical soil characteristics represented by the soil density and porosity (SBD and TSP), and the plant characteristics represented the roots dry weight, PVI and the crop productivity (CP), except adjective of the fu
... Show MoreThe effect of different doping ratio (0.3, 0.5, and 0.7) with thickness in the range 300nmand annealed at different temp.(Ta=RT, 473, 573, 673) K on the electrical conductivity and hall effect measurements of AgInTe2thin film have and been investigated AgAlxIn(1-x) Te2 (AAIT) at RT, using thermal evaporation technique all the films were prepared on glass substrates from the alloy of the compound. Electrical conductivity (σ), the activation energies (Ea1, Ea2), Hall mobility and the carrier concentration are investigated as a function of doping. All films consist of two types of transport mechanisms for free carriers. The activation energy (Ea) decreased whereas electrical conductivity increases with increased doping. Results of Hall Effect
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
... Show MoreA geological model was built for the Sadi reservoir, located at the Halfaya oil field. It is regarded as one of the most significant oilfields in Iraq. The study includes several steps, the most essential of which was importing well logs from six oil wells to the Interactive Petrophysics software for conducting interpretation and analysis to calculate the petrophysical properties such as permeability, porosity, shale volume, water saturation, and NTG and then importing maps and the well tops to the Petrel software to build the 3D-Geological model and to calculate the value of the original oil in place. Three geological surfaces were produced for all Sadi units based on well-top data and the top Sadi structural map. The reservoir has
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