This paper presents a study of the application of gas lift (GL) to improve oil production in a Middle East field. The field has been experiencing a rapid decline in production due to a drop in reservoir pressure. GL is a widely used artificial lift technique that can be used to increase oil production by reducing the hydrostatic pressure in the wellbore. The study used a full field model to simulate the effects of GL on production. The model was run under different production scenarios, including different water cut and reservoir pressure values. The results showed that GL can significantly increase oil production under all scenarios. The study also found that most wells in the field will soon be closed due to high water cuts. However, the application of GL can keep these wells economically viable. The economic evaluation of the study showed that the optimum GL design is feasible and can significantly improve oil production. This suggests that GL is a promising technology for improving oil production in fields that are experiencing a decline in production. The study also provides a new approach to GL optimization using a genetic algorithm, which can be used to find the optimal GL design for a given field.
Two field experiments were conducted during the spring seasons of 2000,2001.The aim was to study the effect of hardening to drought tolerance on moisture percentage in root and stem of sunflower plant during growth stages . Asplit-split plots design was used with three replications.The main plots included irrigation treatments:irrigation to100%(full irrigation),75and50%of available soil water.The sub plots were the cultivars Euroflor and Flame.The sub-sub plots represented four seed soaking treatments :Control(unsoaked),soaking in water ,Paclobutrazol solution(250ppm),and Pix solution(500ppm). The soaking continued for 24 hours then seeds were dried at room temperature until they regained their original weight. Amount of water
... Show MoreThe present paper is an experimental study to improve the productivity of the conventional solar still. This done by modifying conventional still in a way that the distilled basin is larger than distillation basin, thus providing an increase in the condensation surface and speeding up the condensation process. Moreover, increase in the dimensions of the distilled base helps coupling reflective panels to the distilled base to reflect incident solar radiation to the distillation basin. For this purpose , two solar stills were made, one conventional designand another made according to the proposed design. The two solar stills were tested during the period from February to July 2009 under varying weather conditions of Basra, Iraq (latitude o
... Show MoreWater/oil emulsion is considered as the most refractory mixture to separate because of the interference of the two immiscible liquids, water and oil. This research presents a study of dewatering of water / kerosene emulsion using hydrocyclone. The effects of factors such as: feed flow rate (3, 5, 7, 9, and 11 L/min), inlet water concentration of the emulsion (5%, 7.5%, 10%, 12.5%, and 15% by volume), and split ratio (0.1, 0.3, 0.5, 0.7, and 0.9) on the separation efficiency and pressure drop were studied. Dimensional analysis using Pi theorem was applied for the first time to model the hydrocyclone based on the experimental data. It was shown that the maximum separation efficiency; at split ratio 0.1, was 94.3% at 10% co
... Show MoreThe river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)
... Show MoreDissolution of gypsum rock in water is significant, which may result in hydrocarbon reservoir formation and evaporate deposits. However, the complexity of the gypsum dissolution process is still of interest because of its uncleanness that requires more critical analysis. The objectives of this experimental study are emphasis on the dissolution characteristics of gypsum rock under room temperature and by various types of water; namely: deionized, tap, fresh, acidic, well, and normal rainwatre. In addition, the influences of dissolution on gypsum rock's mechanical and physical characteristics. Gypsum rock was obtained from Agjalar area, in the southwest of Sulaymaniyah city, Northern Iraq. Experimental results show that we
... Show MoreWater Quality Index (WQI) as a tool to assess the water quality status provides advice related to the use of water quality monitoring data and it is a way for combining the complex water quality data into a single value or single statement.The present study was conducted on Al- Hilla river in the middle of Iraq from August 2012 to July 2013 at five selected stations in the river, from Al- Musaib city to Al- Hashimya at the south of Hilla to determine its suitability for aquatic environment (GWQI), drinking water (PWSI) and irrigation (IWQI).This index offers a useful representation of the overall quality of water for public or any intended use as well as indicating pollution, water quality management, and decision making. According to th
... Show MoreIn this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.
... Show More
This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).
The improvement in Direction of Arrival (DOA) estimation when the received signals impinge on Active-Parasitic Antenna (APA) arrays will be studied in this work. An APA array consists of several active antennas; others are parasitic antennas. The responses to the received signals are measured at the loaded terminals of the active element. The terminals of the parasitic element are shorted. The effect of the received signals on the parasites, i.e., the induced short-circuit current, is mutually coupled to the active elements. Eigen decomposition of the covariance matrix of the measurements of the APA array generates a third subspace in addition to the traditional signal and noise subspaces generated by the all-active ante
... Show MoreTransmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p
... Show More