Polyaniline organic Semiconductor polymer thin films have been prepared by oxidative polymerization at room temperature, this polymer was deposited on glass substrate with thickness 900nm, FTIR spectra was tested , the structural,optical and electrical properties were studied through XRD ,UV-Vis ,IR measurements ,the results was appeared that polymer thin film sensing to NH3 gas.
Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect beco
... Show MoreGas lift is one of the most important artificial lift methods for increasing oil production, as wells often require this method after the reservoir's energy has decreased. In this research, an optimal gas lift system is designed for five horizontal wells in the Ahdab oil field, which suffers from low production. At the same time, water cut in some of these wells reaches 66%, while the productivity index is low in others, which makes the challenges clear, and a deep analysis is needed to find an optimal system. The Pipesim program is used to design the optimal gas lift system, which contains features that facilitate the implementation of the appropriate design and provide the ability to analyze and determine the optimal design v
... Show MoreThis work deals with the production of light fuel cuts of (gasoline, kerosene and gas oil) by catalytic cracking treatment of secondary product mater (heavy vacuum gas oil) which was produced from the vacuum distillation unit in any petroleum refinery. The objective of this research was to study the effect of the catalyst -to- oil ratio parameter on catalytic cracking process of heavy vacuum gas oil feed at constant temperature (450 °C). The first step of this treatment was, catalytic cracking of this material by constructed batch reactor occupied with auxiliary control devices, at selective range of the catalyst –to- oil ratio parameter ( 2, 2.5, 3 and 3.5) respectively. The conversion of heavy vacuum gas
... Show MoreIn subterranean coal seam gas (CSG) reservoirs, massive amounts of small-sized coal fines are released during the production and development stages, especially during hydraulic fracturing stimulation. These coal fines inevitably cause mechanical pump failure and permeability damage due to aggregation and subsequent pore-throat blockage. This aggregation behavior is thus of key importance in CSG production and needs to be minimized. Consequently, such coal fines dispersions need to be stabilized, which can be achieved by the formulation of improved fracturing fluids. Here, we thus systematically investigated the effectiveness of two additives (ethanol, 0.5 wt % and SDBS, 0.001 and 0.01 wt %) on dispersion stability for a wide range of condit
... Show MoreThe extraction of pesticides is a critical and urgent issue in the preparation for and determination of pesticide residues. The lack of a quick, easy, and successful extraction process is the most critical and challenging problem, even if diagnostic tools have improved and pesticide residues have been better understood. This study contrasted the QuEChERS method, which uses gas chromatography with a flame ionization detector, with the LLE method, which uses liquid-liquid extraction, in order to extract pyridaben from cucumbers and spiromesifen from tomatoes. The GC-FID device was employed to ascertain the spiromesifen LOD and LOQ, which were 0.002 μg mL-1 and 0.00
This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.
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