Gas hydrate formation is considered one of the major problems facing the oil and gas industry as it poses a significant threat to the production, transportation and processing of natural gas. These solid structures can nucleate and agglomerate gradually so that a large cluster of hydrate is formed, which can clog flow lines, chokes, valves, and other production facilities. Thus, an accurate predictive model is necessary for designing natural gas production systems at safe operating conditions and mitigating the issues induced by the formation of hydrates. In this context, a thermodynamic model for gas hydrate equilibrium conditions and cage occupancies of N2 + CH4 and N2 + CO4 gas mixtures at different compositions is proposed. The van der Waals-Platteeuw thermodynamic theory coupled with the Peng-Robinson equation of state and Langmuir adsorption model are employed in the proposed model. The experimental measurements generated using a cryogenic sapphire cell for the pressure and temperature ranges of (5-25) MPa and (275.5-292.95) K, respectively, were used to evaluate the accuracy of this model. The resulting data show that increasing nitrogen mole percentage in the gas mixtures results in decreasing of equilibrium hydrate temperatures. The deviations between the experimental and predictions are discussed. Furthermore, the cage occupancies for the gas mixtures in hydrate have been evaluated. The results demonstrate an increase in the cage occupancy for both the small and large cavities with pressure.
In this study, a low-cost biosorbent, dead mushroom biomass (DMB) granules, was used for investigating the optimum conditions of Pb(II), Cu(II), and Ni(II) biosorption from aqueous solutions. Various physicochemical parameters, such as initial metal ion concentration, equilibrium time, pH value, agitation speed, particles diameter, and adsorbent dosage, were studied. Five mathematical models describing the biosorption equilibrium and isotherm constants were tested to find the maximum uptake capacities: Langmuir, Freundlich, Redlich-Peterson, Sips, and Khan models. The best fit to the Pb(II) and Ni(II) biosorption results was obtained by Langmuir model with maximum uptake capacities of 44.67 and 29.17 mg/g for these two ions, respectively, w
... Show MorePrecise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
... Show MoreThe research aims to shed light on the importance of Natural gas as a National wealth is not being used optimally to be a financial resource is important to Iraq in addition to Oil, as well as could be used as an important Source of Energy, instead of burning gas is a waste of wealth and Contribute to the contamination of the environment. Research Reviews the importance of Natural gas, where is currently about a quarter of global energy consumption. Then deals with the reality of the gas industry in Iraq and winning because of the volume of waste incineration, which reached a rate (45%) of the gas Associated with oil, where Iraq is fourth globally in Terms of the amount of gas Burned. Finally, this paper discusses the future of n
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show MoreThis contribution reports a comprehensive investigation into the structural, electronic and thermal properties of bulk and surface terbium dioxide (TbO2); a material that enjoys wide spectra of catalytic and optical applications. Our calculated lattice dimension of 5.36 Å agrees well with the corresponding experimental value at 5.22 Å. Density of states configuration of the bulk structure exhibits a semiconducting nature. Thermo-mechanical properties of bulk TbO2 were obtained based on the quasi-harmonic approximation formalism. Heat capacities, thermal expansions and bulk modulus of the bulk TbO2 were obtained under a wide range of temperatures and pressures. The dependency of these properties on operational pressure is very evident. Cle
... Show MoreTo study the response of the celery plant to nitrogen fertilization and spray with salicylic acid in the leaves content of nutrients, the research was conducted in one of the fields of the Department of Horticulture and Gardening Engineering / College of Agriculture / University of Baghdad within the 2019-2018 season. The research was carried out as a global experiment and with the design of complete randomized sectors (RCBD) and with three replicates, the first factor included the addition of nitrogen with three levels and its symbol (N) (N1 control), (N2) g / m2 18 ), (N3) 37 g / m2 and the second factor spraying acid salicylic is denoted by
The buildup factor was measured after irradiating Iraq carbon black powder using each of and sources respectively, using mixing ratios 40% & 50% for thickness range . The results showed that the buildup factor depends on energy and has limited dependence on the mixing ratio. The QIFT program succeeded accenting for the experimental results even for expected values more than 4 m.f.p outside the thickness range.
