A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited grids and used in the training and testing of the used network. A comparison between the calculated and observed cumulative oil production has been carried out through the testing steps of the constructed ANN, an absolute average percentage error of the used network was reached to 4.044%, and this is consider to be an acceptable limit within engineering applications, in addition to that, a good behavior was reached with (FFNNW) and suitable re-entry wells location were identified according to the reservoir configuration (pressure and saturation distribution) output from SRF simulation model at the end of 2005.
To identify the fungi associated with water hyacinth (Eichhornia crassipes [Mart.] Solms), an aquatic weed, which presents in Tigris river from Baghdad south ward. Five regions from middle and south of Iraq (Al-Noumanya, Saeid Bin-Jubier, Al-Azizia, Al-Reyfay and Al-Hay) were selected for this study. Twelve fungal species were isolated. Alternaria alternata, Acremonium sp and Cladsporium herbarum, were the most frequently species (91.66 % ,50 % and 25 %) respectively. The fungi Alternaria alternata, Acremonium sp. and Phoma eupyrena were more aggressive to water hyacinth as (91.66%,83,33%, and 75%) in pathogenicity test.
The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.
Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio
... Show MoreBiodiesel is becoming one of the most attractive alternative biofuels for petroleum-based diesel fuels. The castor plant is one of the abundant non-edible oils found in many countries. This paper aims to study Libyan castor oil and its potential for diesel conversion. Experiments were carried out in the laboratories of the Specific Center for Training in the Oil Industries in Al-Zawiya. The oil was extracted using a Soxhlet extractor and n-hexane solvent at 60 °C. Transesterification reactions were conducted in a batch reactor (a three-neck flask was used, where the middle opening carries a reflux condensation unit) at 65 °C. The methanol-to-castor oil molar ratio was 6:1, with a catalyst concentration of 1 wt.% relative to the ca
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
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This research include building mathematical models for aggregating planning and shorting planning by using integer programming technique for planning master production scheduling in order to control on the operating production for manufacturing companies to achieve their objectives of increasing the efficiency of utilizing resources and reduce storage and improving customers service through deliver in the actual dates and reducing delays.
The Khabour reservoir, Ordovician, Lower Paleozoic, Akkas gas field which is considered one of the main sandstone reservoirs in the west of Iraq. Researchers face difficulties in recognizing sandstone reservoirs since they are virtually always tight and heterogeneous. This paper is associated with the geological modeling of a gas-bearing reservoir that containing condensate appears while production when bottom hole pressure declines below the dew point. By defining the lithology and evaluating the petrophysical parameters of this complicated reservoir, a geological model for the reservoir is being built by using CMG BUILDER software (GEM tool) to create a static model. The petrophysical properties of a reservoir were computed using
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Used vegetable oil was introduced to transesterfication reaction to produce Biodiesel fuel suitable for diesel engines. Method of production was consisted of filtration, transesterfication, separation and washing. Transesterfication was studied extensively with different operating conditions, temperature range (35-80o C), catalyst concentration (0.5-2 wt. % based on oil), mixing time (30-120 min.) with constant oil/methanol weight ratio 5:1 and mixing speed 1300 rpm. The concentration of Fatty acid methyl esters (Biodiesel) was determined for the transesterficated oil samples, besides of some important physical properties such as specific gravity, viscosity, pour point and flash point. The behavior of methyl esters production and the
... Show MoreUsed vegetable oil was introduced to transesterfication reaction to produce Biodiesel fuel suitable for diesel engines. Method of production was consisted of filtration, transesterfication, separation and washing. Transesterfication was studied extensively with different operating conditions, temperature range (35-80oC), catalyst concentration (0.5-2 wt. % based on oil), mixing time (30-120 min.) with constant oil/methanol weight ratio 5:1 and mixing speed 1300 rpm. The concentration of Fatty acid methyl esters (Biodiesel) was determined for the transesterficated oil samples, besides of some important physical properties such as specific gravity, viscosity, pour point and flash point. The behavior of methyl esters production and the physica
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