The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in permeability prediction and compared its results with the flow zone indicator methods for a carbonate heterogeneous Iraqi formation. The methodology of the research can be Summarized by permeability was estimated by using two methods: Flow zone indicator and Artificial intelligence, two reservoir models are built, where the difference between them is in permeability method estimation, and the simulation run will be conducted on both of the models, and the permeability estimation methods will be examined by comparing their effect on the model history matching. The results showed that the model with permeability predicted by using artificial intelligence matched the observed data for different reservoir responses more accurately than the model with permeability predicted by the flow zone indicator method. That conclusion is represented by good matching between observed data and simulated results for all reservoir responses such for the artificial intelligence model than the flow zone indicator model.
Preparation of superposed thin film (CdTe)1-xSex / ZnS) with concentration of (x= 0.1, 0.3, 0.5) at a temperature of substrate (Ts= 80 0C) by using Thermal Vacuum Evaporation System. The measurement of X-ray diffraction shows that the compounds CdTe, ZnS, (CdTe)1-xSex and (CdTe)1-xSex / ZnS have a polycrystalline structure, the C-V characteristic shows that the capacitance degrease by increasing the concentration (x) in reverse bias, while the I-V characteristic shows the current dark (Id) increase in forward and reverse bias by increasing (x) and the photocurrent (Iph) increase in reverse bias by increasing the concentration (x), the values of photocurrent are greater than from the values of the dark current for all concentrations
... Show MoreThis paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima
... Show MoreThe effect of time (or corrosion products formation) on corrosion rates of carbon steel pipe in aerated 0.1N NaCl
solution under turbulent flow conditions is investigated. Tests are conducted using electrochemical polarization
technique by determining the limiting current density of oxygen reduction in Reynolds number range of 15000 to 110000
and temperature range of 30 to 60oC. The effect of corrosion products formation on the friction factor is studied and
discussed. Corrosion process is analyzed as a mass transfer operation and the mass transfer theory is employed to
express the corrosion rate. The results are compared with many proposed models particularly those based on the
concept of analogy among momentum, heat,
The first chapter the importance of research and need for education scientists see that the roots of the use of a specimen Wheatley in learning and teaching back to Grayson Wheatley, one of the largest supporters of a modern construction, which lay the groundwork for the specimen stage and the form in which it is. That was attributed to him, often called his name called while some educators based learning strategy on the issue. He sees the learner in this model make him a meaningful understanding of problems during his progress, thereby acting with his colleagues to find solutions to them in small groups. He
Borders Search: Search by students is determined by th
... Show MoreThis paper presents a three-dimensional Dynamic analysis of a rockfill dam with different foundation depths by considering the dam connection with both the reservoir bed and water. ANSYS was used to develop the three-dimensional Finite Element (FE) model of the rockfill dam. The essential objective of this study is the discussion of the effects of different foundation depths on the Dynamic behaviour of an embanked dam. Four foundation depths were investigated. They are the dam without foundation (fixed base), and three different depths of the foundation. Taking into consideration the changing of upstream water level, the empty, minimum, and maximum water levels, the results of the three-dimensional F
In this paper we study the effect of the number of training samples for Artificial neural networks ( ANN ) which is necessary for training process of feed forward neural network .Also we design 5 Ann's and train 41 Ann's which illustrate how good the training samples that represent the actual function for Ann's.