The Yamama Formation was studied in three wells (Fh-1, Fh-2, and Fh-3) within Faihaa oil field, south Iraq. Thin sections were studied by using the polarizing microscope examination in order to determine microfossils and biozone. Thirty-five species of benthic foraminifera were recognized, including four index species. In addition,  twelve species of calcareous green algae were recognized, including  two index species. Other fossils that were recognized in Yamama Formation include Gastropoda, Bryozoa, Coral, Rudist, and Pelecypoda.

Six biozones were observed, which are Charentia cuvillieri sp. (Range Zone of Berriasian age), Psudochryalidina infracretacea

     A geological model is a spatial representation of the distribution of sediments and rocks in the subsurface. Where this study on Halfaya oil field; it is located in Missan governorate, 35 km southeast of the city of Amara. It is one of the main  fields in Iraq because it is production high oil. This model contains the structure, and petrophysical properties (porosity,  water saturation) in three directions. To build 3D geological models of petroleum reservoirs. Khasib, Tanuma, and Sa’di formations in Halfaya oil field have been divided into many layers depending on petrophysical properties and facies. 

Within this research, The problem of scheduling jobs on a single machine is the subject of study to minimize the multi-criteria and multi-objective functions. The first problem, minimizing the multi-criteria, which include Total Completion Time, Total Late Work, and Maximum Earliness Time (∑𝐶𝑗, ∑𝑉𝑗, 𝐸𝑚𝑎𝑥), and the second problem, minimizing the multi-objective functions ∑𝐶𝑗 + ∑𝑉𝑗 +𝐸𝑚𝑎𝑥 are the problems at hand in this paper. In this study, a mathematical model is created to address the research problems, and some rules provide efficient (optimal) solutions to these problems. It has also been proven that each optimal solution for ∑𝐶𝑗 + ∑𝑉𝑗 + 𝐸𝑚𝑎𝑥 is an effic

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

Well integrity is a vital feature that should be upheld into the lifespan of the well, and one constituent of which casing, necessity to be capable to endure all the interior and outside loads. The casing, through its two basic essentials: casing design and casing depth adjustment, are fundamental to a unique wellbore that plays an important role in well integrity. Casing set depths are determined based on fracturing pressure and pore pressure in the well and can usually be obtained from well-specific information. Based on the analyzes using the improved techniques in this study, the following special proposition can be projected: The selection of the first class and materials must be done correctly and accurately in accordance with

Visualization of subsurface geology is mainly considered as the framework of the required structure to provide distribution of petrophysical properties. The geological model helps to understand the behavior of the fluid flow in the porous media that is affected by heterogeneity of the reservoir and helps in calculating the initial oil in place as well as selecting accurate new well location. In this study, a geological model is built for Qaiyarah field, tertiary reservoir, relying on well data from 48 wells, including the location of wells, formation tops and contour map. The structural model is constructed for the tertiary reservoir, which is an asymmetrical anticline consisting of two domes separated by a saddle. It is found that

The research amid to measure the extent of the Suggested procedures of the internal control in accordance with the updated COSO framework in improving the procedures for internal control work in Iraqi oil companies. As the research problem was represented in suggesting procedures for internal control according to the updated COSO framework and finding out the relationship of correlation and influence between the suggested procedures and the internal control procedures that are done in the Iraqi oil companies. The research followed the quantitative approach to handling and analysing data by designing a Questionnaire to represent the research tool for collecting data. The study population was represented in the Iraqi oil companies,

Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent $\left({}\right)$

Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica