Water flooding is one of the most important methods used in enhanced production; it was a pioneer method in use, but the development of technology within the oil industry, takes this subject toward another form in the oil production and application in oil fields with all types of oils and oil reservoirs. Now days most of the injection wells directed from the vertical to re-entry of full horizontal wells in order to get full of horizontal wells advantages.
This paper describes the potential benefits for using of re-entry horizontal injection wells as well as combination of re –entry horizontal injection and production wells. Al Qurainat productive sector was selected for study, which is one of the four main productive sectors of South Rumaila oil field. A simulation model – named as SRFQ was used in the present work to predict the re-entry horizontal wells performance.
Four scenarios were suggested to cover the full scope of the study; those scenarios are different in manner of wells combinations. Cumulative oil production, ultimate recovery percentage are two criteria were used to predict the performance and comparison of scenarios.
Results from simulation model (SRFQ) runs revealed that the productive sector can be continue to gain 1564.331 MMSTB till 2020, without changing to any existing injection and production wells status, which is called the base scenario. While scenario no.1 needs some of work over and remedies jobs, which gives more cumulative oil production reaches to 1698.481 MMSTB till 2020.
On another side, scenarios no. 2 and 4 are the most important scenarios because re-entry horizontal injection wells were implemented. Very good and encourage results were gained over the bas scenario from the sector under study.
At last, scenario no.3 was suggested just to predict the production capacity of the Al Qurainat sector with re-entry horizontal production wells and existing vertical injection and production wells, while the cumulative oil production reaches 3398.481MMSTB.
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
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AlPO4 solid acid catalyst was prepared in order to use it in transesterification reaction of edible oil after supporting it with tungsten oxide. The maximum conversion of edible oil was obtained 78.78% at catalyst concentration (5gm.), temperature 70°Ϲ, 30/1 methanol/edible oil molar ratio, and time 5hr. The study of kinetics of the transesterification reaction of edible oil indicates that the reaction has an order of 3/2, while the value of activation energy for transesterification reaction is 51.367 kJ/mole and frequency factor equal 26219.13(L/ mol.minute).
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AlPO4 solid acid catalyst was prepared in order to use it in transesterification reaction of edible oil after supporting it with tungsten oxide. The maximum conversion of edible oil was obtained 78.78% at catalyst concentration (5gm.), temperature 70°Ϲ, 30/1 methanol/edible oil molar ratio, and time 5hr. The study of kinetics of the transesterification reaction of edible oil indicates that the reaction has an order of 3/2, while the value of activation energy for transesterification reaction is 51.367 kJ/mole and frequency factor equal 26219.13(L/ mol.minute).
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KE Sharquie, AA Noaimi, ZN Al-Khafaji…, Journal of Cosmetics, Dermatological Sciences and Applications, 2016 - Cited by 2
(28)Bacterial local isolates of Bacillus sp. were obtained from soil samples. Isolates were tested for thermostable alpha- amylase production on solid media; fifteen isolates were able to develop clear zone around the bacterial growth after floating the plates with iodine reagent (Lugol's solution). There were further tested in submerged culture which led to selection of Bacillus sp. H14since it was the most efficient .Microbial and biochemical tests showed that the local isolate Bacillus sp.H14was refered to the species B.licheniformis that signed as H14 was refered to the species B.licheniformis H14 .,To get ahigher yield of alpha – amylase(48.70unit/mg protein) production from the local isolate B.licheniformis H14 . This study used
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In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H
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