A 2D geological model for Mauddud Formation in the Badra oil field is built using Rockworks 16 software. Mauddud Formation produces oil from limestone units; it represents the main reservoir in the Badra oil field. Six wells (BD-1, BD-2, BD-4, BD-5, P-15, and P-19) are selected to build facies and petrophysical (Porosity and Water saturation) models. Wells data are taken from the core and cutting samples and studied through the microscopic. The petrophysical data (effective porosity and water saturation) are derived from computer processes interpretation results that are calculated by using Interactive Petrophysics software. The 2D models are built to illustrate the vertical and horizontal distribution of petrophysical properties between we

Background: This in vitro study evaluated the fracture resistance of weakened endodontically treated premolars with class II MOD cavities restored with different composite restorations (Low-shrinkage Filtek P90, nanohybrid Filtek Z250 XT and SDR bulk fill). The type and mode of fracture were also assessed for all the experimental groups. Materials and Method: Fifty human adult maxillary premolar teeth were selected for this study. Standardized extensive class II MOD cavities with endodontic treatment were prepared for all teeth, except those that were saved as intact control. The teeth were divided into five groups of ten teeth each (n=10): (Group 1) intact control group, (Group 2) unrestored teeth with endodontic treatment, (Group 3) resto

Multilateral wells require a sophisticated type of well model to be applied in reservoir simulators to represent them. The model must be able to determine the flow rate of each fluid and the pressure throughout the well. The production rate calculations are very important because they give an indication about some main issues associated with multi-lateral wells such as one branch may produce water or gas before others, no production rate from one branch, and selecting the best location of a new branch for development process easily.                                &nbsp

Constructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distribution along

Constructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distri

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Empirical equation has been presented to predict the optimum hydrodynamic
pressure gradient with optimum mud flow rate (one equation) of five Iraqi oil wells
to obtain the optimum carrying capacity of the drilling fluid ( optimum transport
cuttings from the hole to the surface through the annulus).
This equation is a function of mud flow rate, mud density and penetration
rate without using any charts or graphs.
The correlation coefficient accuracy is more than 0.9999.

Background: Endodontically treated teeth have low resistance to fracture against occlusal forces. The strengthening effect of bonded esthetic onlay restoration on weakened tooth has been reported. This study aimed to assess the fracture resistance of endodontically treated premolars restored with composite with and without cuspal coverage by using direct and indirect techniques. Indirect technique done by CAD/CAM system (computer aided design –computer aided manufacturer) and laboratory processing. Material and methods: Forty human extracted maxillary premolars of approximately comparable sizes were divided into four groups: Group (A): Ten endodontically treated teeth directly filled with Filtek Z250xt without cuspal coverage. Group

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat