Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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

This study aims to evaluate reservoir characteristics of Hartha Formation in Majnoon oil field based on well logs data for three wells (Mj-1, Mj-3 and Mj-11). Log interpretation was carried out by using a full set of logs to calculate main petrophysical properties such as effective porosity and water saturation, as well as to find the volume of shale. The evaluation of the formation included computer processes interpretation (CPI) using Interactive Petrophysics (IP) software.  Based on the results of CPI, Hartha Formation is divided into five reservoir units (A1, A2, A3, B1, B2), deposited in a ramp setting. Facies associations is added to well logs interpretation of Hartha Formation, and was inferred by a microfacies analysis of th

Nasryia oil field is located about 38 Km to the north-west of Nasryia city. The field was discovered in 1975 after doing seismic by Iraqi national oil company. Mishrif formation is a carbonate rock (Limestone and Dolomite) and its thickness reach to 170m. The main reservoir is the lower Mishrif (MB) layer which has medium permeability (3.5-100) md and good porosity (10-25) %. Form well logging interpretation, it has been confirmed the rock type of Mishrif formation as carbonate rock. A ten meter shale layer is separating the MA from MB layer. Environmental corrections had been applied on well logs to use the corrected one in the analysis. The combination of Neutron-Density porosity has been chosen for interpretation as it is c

The Middle Cenomanian-Early Turonian Mishrif Formation includes important carbonate reservoirs in Iraq and some other surrounding countries due to their high reservoir quality and wide geological extension. The 2D models of this study for facies, effective porosity and water saturation indicate the vertical and lateral heterogeneity of the Mishrif Formation reservoir properties in the Majnoon oil field. Construction of 2D reservoir model of the Mishrif Formation to explain the distribution of facies and petrophysical properties (effective porosity and water saturation) by using RockWorks software. The increase of effective porosity is attributed to the presence of shoal facies.The high water saturation is attributed to the existence of rest

The reservoir units of Mishrif Formation in Majnoon oil field were studied by using available wireline logs (gamma ray, porosity and resistivity) and facies that derived from core and cutting samples for three wells including Mj-1, Mj-15, and Mj-20. The reservoir properties were determined and interpreted by using IP software. The results showed that unit D have the best reservoir properties due to high effective porosity, low water saturation and very low volume of shale. Furthermore, a large part of this unit was deposited in shoal environment. The other reservoir units are then graded in reservoir properties including units B, A, F & E respectively, except unit C, which is considered as a cap unit, because it consists of rest

The reservoir units of Mishrif Formation in Majnoon oil field were studied by using available wireline logs (gamma ray, porosity and resistivity) and facies that derived from core and cutting samples for three wells including Mj-1, Mj-15, and Mj-20. The reservoir properties were determined and interpreted by using IP software. The results showed that unit D have the best reservoir properties due to high effective porosity, low water saturation and very low volume of shale. Furthermore, a large part of this unit was deposited in shoal environment. The other reservoir units are then graded in reservoir properties including units B, A, F & E respectively, except unit C, which is considered as a cap unit, because it consists of restricte

     The main goal of this study is to evaluate Mishrif Reservoir in Abu Amood oil field, southern Iraq, using the available well logs. The sets of logs were acquired for wells AAm-1, AAm-2, AAm-3, AAm-4, and AAm-5. The evaluation included the identification of the reservoir units and the calculation of their petrophysical properties using the Techlog software. Total porosity was calculated using the neutron-density method and the values were corrected from the volume of shale in order to calculate the effective porosity. Computer processed interpretation (CPI) was accomplished for the five wells. The results show that Mishrif Formation in Abu Amood field consists of three reservoir units with various percentages of h