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.
A particulate composite material was prepared by adding the Titanium dioxide (TiO2) with a particle size of (75-150) µm to Epoxy resin at weight percentage of (10%,20%,30%,40%,50%).The following some mechanical properties were studied,fracture toughness, hardness.casting preparation methods were used in this study includes preparing plate of matrix and composites. specimens were prepared according to ASTM for the Mechanical properties tests. After that Another samples were heat treated for three and six hour at 65C?. Fracture toughness (Kic) represent for stress intensity factor results were showed that the curve of three hours aging increases in fracture toughness (Kic) for composites but for six hours aging increases fracture tough
... Show MoreA study was conducted at the University of Baghdad-College of Agricultural Engineering Sciences - Department of Agricultural Machinery and Equipment for the agricultural season 2023 with the aim of designing, manufacturing and testing a machine used to planting agricultural nursery tray with different types of vegetable or horticultural seeds or forest seeds of various forms, and using different agricultural media where they are conducted The planting process is by pulling the seeds with a negative pressure vacuum system, and then they are feding to the dishes in their right place to complete the planting process. The study included three factors: The speed of the main belt in three l
A load flow program is developed using MATLAB and based on the Newton–Raphson method,which shows very fast and efficient rate of convergence as well as computationally the proposed method is very efficient and it requires less computer memory through the use of sparsing method and other methods in programming to accelerate the run speed to be near the real time.
The designed program computes the voltage magnitudes and phase angles at each bus of the network under steady–state operating conditions. It also computes the power flow and power losses for all equipment, including transformers and transmission lines taking into consideration the effects of off–nominal, tap and phase shift transformers, generators, shunt capacitors, sh
Porosity and permeability are the most difficult properties to determine in subsurface reservoir characterization. The difficulty of estimating them arising from the fact that porosity and permeability may vary significantly over the reservoir volume, and can only be sampled at well location. Secondly, the porosity values are commonly evaluated from the well log data, which are usually available from most wells in the reservoir, but permeability values, which are generally determined from core analysis, are not usually available. The aim of this study is: First, to develop correlations between the core and the well log data which can be used to estimate permeability in uncored wells, these correlations enable to estimate reservoir permeabil
... Show MoreA geological model was built for the Sadi reservoir, located at the Halfaya oil field. It is regarded as one of the most significant oilfields in Iraq. The study includes several steps, the most essential of which was importing well logs from six oil wells to the Interactive Petrophysics software for conducting interpretation and analysis to calculate the petrophysical properties such as permeability, porosity, shale volume, water saturation, and NTG and then importing maps and the well tops to the Petrel software to build the 3D-Geological model and to calculate the value of the original oil in place. Three geological surfaces were produced for all Sadi units based on well-top data and the top Sadi structural map. The reservoir has
... Show MoreThe present work investigates the effect of magneto – hydrodynamic (MHD) laminar natural convection flow on a vertical cylinder in presence of heat generation and radiation. The governing equations which used are Continuity, Momentum and Energy equations. These equations are transformed to dimensionless equations using Vorticity-Stream Function method and the resulting nonlinear system
of partial differential equations are then solved numerically using finite difference approximation. A thermal boundary condition of a constant wall temperature is considered. A computer program (Fortran 90) was built to calculate the rate of heat transfer in terms of local Nusselt number, total mean Nusselt number, velocity distribution as well as te
The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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