Production logging is used to diagnose well production problems by evaluating the flow profile, entries of unwanted fluids and downhole flow regimes. Evaluating wells production performance can be easily induce from production logs through interpretation of production log data to provide velocity profile and contribution of each zone on total production. Production logging results supply information for reservoir modeling, provide data to optimize the productivity of existing wells and plan drilling and completion strategies for future wells. Production logging was carried out in a production oil well from Mishrif formation of West Qurna field, with the objective to determine the flow profile and fluid contributions from the perforations after the stimulation job. The measurements were made under shut-in and three choke sizes (60/64”, 46/64” and 32/64”) flowing conditions. Overall, the data quality is acceptable to generate a good analysis. From the flowing surveys, it was observed that just the intervals 2250-2285 m and 2335-2375 m are contributing to the total well production while the well was flowing through the chokes 60/64” and 46/64”. However, most production is coming from the interval 2250-2285 m for each choke. The flow profile changed with the 32/64”, the interval 2250-2285 remained producing but the interval 2335-2375 m started receiving fluid from the upper interval. This cross flow increased after the well was shut in. The temperature log shows a normal behavior while the well is flowing through the 60/64” and 46/64” chokes, but changes as result of the cross flow with the 32/64” choke and with the well shut in. From the capacitance readings and pseudo fluid density (density from differential pressure) only oil is being produced, and there is a static water column at the sump.
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<p>The current work investigated the combustion efficiency of biodiesel engines under diverse ratios of compression (15.5, 16.5, 17.5, and 18.5) and different biodiesel fuels produced from apricot oil, papaya oil, sunflower oil, and tomato seed oil. The combustion process of the biodiesel fuel inside the engine was simulated utilizing ANSYS Fluent v16 (CFD). On AV1 diesel engines (Kirloskar), numerical simulations were conducted at 1500 rpm. The outcomes of the simulation demonstrated that increasing the compression ratio (CR) led to increased peak temperature and pressures in the combustion chamber, as well as elevated levels of CO<sub>2</sub> and NO mass fractions and decreased CO emission values un
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Background: Obesity is a serious public health concern that has reached epidemic proportions; the prevalence, as well as the severity of obesity in adolescents is increasing at an alarming rate. A close relationship was found between weight status and dental caries. Thus this research aimed to assess the prevalence and severity of dental caries among overweight adolescent females in relation to physicochemical characteristics of stimulated whole saliva in comparison with normal weight adolescent females. Materials and methods: The total sample involved for nutritional status assessment is composed of 2678 females aged 13-15 years. This was performed using Body Mass Index specific for age and gender according to CDC growth chart (2000). The
... Show MoreCalcium carbonate is predominantly present in aqueous systems, which is
commonly used in industrial processes. It has inverse solubility characteristics
resulting in the deposition of scale on heat transfer surface. This paper focuses on
developing methods for inhibition of calcium carbonate scale formation in cooling
tower and air cooler system where scaling can cause serious problems, ZnCl 2 and ZnI
2 has been investigated as scale inhibitor on AISI 316 and 304. ZnCl 2 were more
effective than ZnI 2 in both systems, and AISI 316 show more receptivity to the
chlorides salt compared to AISI 304. The inhibitors were more effective in cooling
tower than air cooler system. AISI 316 show more constant inhibition effic
The present study analyzes the effect of couple stress fluid (CSF) with the activity of connected inclined magnetic field (IMF) of a non-uniform channel (NUC) through a porous medium (PM), taking into account the sliding speed effect on channel walls and the effect of nonlinear particle size, applying long wavelength and low Reynolds count estimates. The mathematical expressions of axial velocity, stream function, mechanical effect and increase in pressure have been analytically determined. The effect of the physical parameter is included in the present model in the computational results. The results of this algorithm have been presented in chart form by applying the mathematical program.
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Five subsurface sections covering the entire length of the Jeribe Limestone Formation (Early Middle Miocene) were studied from four oilfields in northern Iraq. It is hoped to unravel this formation microfacies ; depositional environment; diagenetic attributes and their parental processes; and the relationship between these processes and the observed porosity patterns. The microfacies were found to include mudstone, wackestone, packstone, and grainstone, which have been deposited respectively in open platform, restricted platform, and edge platform which represent the lagoonal environment, while the deposits of the lower parts of the Jeribe formation especially in well Hamrin- 2 reflect a deeper fore slope environment. By using the lithofac
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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