Characterization of the heterogonous reservoir is complex representation and evaluation of petrophysical properties and application of the relationships between porosity-permeability within the framework of hydraulic flow units is used to estimate permeability in un-cored wells. Techniques of flow unit or hydraulic flow unit (HFU) divided the reservoir into zones laterally and vertically which can be managed and control fluid flow within flow unit and considerably is entirely different with other flow units through reservoir. Each flow unit can be distinguished by applying the relationships of flow zone indicator (FZI) method. Supporting the relationship between porosity and permeability by using flow zone indictor is carried out for evaluating the reservoir quality and identification of flow unit used in reservoir zonation. In this study, flow zone indicator has been used to identify five layers belonging to Tertiary reservoirs. Consequently, the porosity-permeability cross plot has been done depending on FZI values as groups and for each group denoted to reservoir rock types. On the other hand, extending rock type identification in un-cored wells should apply a cluster analysis approach by using well logs data. Reservoir zonation has been achieved by cluster analysis approach and for each group known as cluster which variation and different with others. Five clusters generated in this study and permeability estimated depend on these groups in un-cored wells by using well log data that gives good results compared with different empirical methods.
The aim of this study is to estimate the parameters and reliability function for kumaraswamy distribution of this two positive parameter (a,b > 0), which is a continuous probability that has many characterstics with the beta distribution with extra advantages.
The shape of the function for this distribution and the most important characterstics are explained and estimated the two parameter (a,b) and the reliability function for this distribution by using the maximum likelihood method (MLE) and Bayes methods. simulation experiments are conducts to explain the behaviour of the estimation methods for different sizes depending on the mean squared error criterion the results show that the Bayes is bet
... Show MoreKE Sharquie, AA Noaimi, MS Abass, American Journal of Dermatology and Venereology, 2019 - Cited by 4
Nutlets of 22 taxa of Stachys (13 species and seven subspecies and two varieties), representing seven of the currently recognized sections distributed in northern Iraq were examined by light microscope. The basic shape of nutlets in most taxa studied is Obovoid, but Oblong also found in S.megalodanta Hausskn.& Bornm. ex P.H.Davis, S.setirefa C.A.Mey. subsp daenensis (Gandog.) Rech.f.and S. kurdica Boiss.& Hohen. var.kurdica, while the Subgloboid shape found in S. iberica M.Bieb. and S. inflata Benth., more over the Broad triangular shape was found in S. nephrophylla Rech.f. and S.lanigera (Bornm.) Rech.f.., the biggest size of nutlets was found in S.inflata L. and the smallest was in S.melampyroides Hand.-Mzt. Regarding sculpturing pa
... Show MoreIn this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for
... Show MoreDifferent ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
Calendula officinalis L. (Asteraceae) known as marigold is known to have several pharmacological activities and used for the treatment of several diseases as measles, jaundice, constipation and several inflammations. Marigold flowers contain several chemical constituents mainly flavonoids, triterpenoids and essential oil. In this study marigold flowers cultivated in Iraq had been investigated for its flavonoids content. The study revealed the presence of quercetin and kaempferol glycosides and the absence of myricetin glycosides. The flowers were extracted with ethanol 70% fractionated with different solvent and the flavonoids were isolated by preparative HPLC. The isolated flavonoids were identified by measuring melting points, UV, IR,
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This study aims to identify the most important legislatures and legal frameworks pertaining to advertisement for children. It focuses on the western approach, which is characterized by the variety of its perspectives in presenting issues and in identifying problems. However, if studies show that there is a certain awareness about the advertisement impact on children, it is obvious that most of legislatures reject the laws restricting the broadcast advertising spots intended for children under 12 years of age, with the exception of the Swedish and the Canadian province of Quebec experiences, which opted for total ban on advertising spots broadcast messages targeting children. |
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for