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 the notion of hydraulic units, and there are a number of basic steps to building a geological model, beginning with the creation of a single well model and then moving on to the distribution of properties. Depending on the variance in petrophysical parameters, the reservoirs were separated into seven zones. The Ordovician Formation (Khabour Formation) is penetrated by well Akk-1, which is included in the single well geological model to focus on studying the impact of gas condensate on gas production. The prediction of gas condensate wells production will strongly depend on oil banking evaluation and modeling. For this reason, well Akk-1 was chosen to build the model. Upper and lower sandstone units characterized as the most important due to containing of gas. The cost and risk to develop these reservoirs under severe conditions of pressure and temperature highlight the need to be able to confidently predict the recovery of gas and liquid drop-outs from Khabour reservoirs so, it is so necessary to predict the cost of this step in another paper
Materials recycling has a significant economic and environmental impact; as a result, steel, aluminium, plastic, and other recyclable materials have been pushed for use in construction materials. One of these recyclable materials is the crumb rubber, has been considered as a pavement component. The general behaviour of the composite rubber-hot mix asphalt system would be varied from that of the conventional rubber free mix. In this review, desirable characteristics of hot mix asphalt are highlighted first. Also, effect of gradation and the main types of rubber are specified. Afterward, many studies that considered the crumb rubber as a waste product and its associated mixture and modifiers are reviewed. The factors affect the crumb
... Show MoreThin films of CdTe were prepared with thickness (500, 1000) nm on the glass substrate by vacuum evaporation technique at room temperature then treated different annealing temperatures (373,473,and 573)K for one hour. Results of the Hall Effect and the electrical conductivity of (I-V) characteristics were measured in darkness and light.at different annealing temperature results show that the thin films have ability to manufacture solar cells, and found that the efficient equal to (2.18%) for structure solar cell (Algrid / CdS / CdTe /glass/ Al) and the efficient equal to (1.12%) for structure solar cell (Algrid / CdS / CdTe /Si/ Al) with thick ness of (1000) nm with CdTe thin films at RT.
In this work, a deep computational study has been conducted to assign several qualities for the graph . Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.
In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.
Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi
... Show MoreMachine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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