Yamama Formation (Valanginian-Early Hauterivian) is one of the most important oil production reservoirs in southern Mesopotamian Zone. The Yamama Formation in south Iraq comprises outer shelf argillaceous limestones and oolitic, pelloidal, pelletal and pseudo-oolitic shoal limestones. The best oil prospects are within the oolite shoals. Yamama Formation is divided into seven zones: Upper Yamama, Reservoir Units YR-A & YR-B separated by YB-1, and YR-B Lower & two Tight zones: low (porosity, permeability and oil saturation) with variable amounts of bitumen. These reservoir units are thought to be at least partially isolated from each other.
Gas hydrate formation poses a significant threat to the production, processing, and transportation of natural gas. Accurate predictions of gas hydrate equilibrium conditions are essential for designing the gas production systems at safe operating conditions and mitigating the problems caused by hydrates formation. A new hydrate correlation for predicting gas hydrate equilibrium conditions was obtained for different gas mixtures containing methane, nitrogen and carbon dioxide. The new correlation is proposed for a pressure range of 1.7-330 MPa, a temperature range of 273-320 K, and for gas mixtures with specific gravity range of 0.553 to 1. The nonlinear regression technique was applie
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 mix
A study to find the optimum separators pressures of separation stations has been performed. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid is discharged from a higher-pressure separator into the lower-pressure separator. The set of working separator pressures that yields maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures, which is the target of this work.
A computer model is used to find the optimum separator pressures. The model employs the Peng-Robinson equation of state (Peng and Robinson 1976) for volatile oil. The application of t
Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame