The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Increasing world demand for renewable energy resources as wind energy was one of the goals behind research optimization of energy production from wind farms. Wake is one of the important phenomena in this field. This paper focuses on understanding the effect of angle of attack (α) on wake characteristics behind single horizontal axis wind turbines (HAWT). This was done by design three rotors different from each other in value of α used in the rotor design process. Values of α were (4.8˚,9.5˚,19˚). The numerical simulations were conducted using Ansys Workbench 19- Fluent code; the used turbulence model was (k-ω SST). The results showed that best value for extracted wind energy was at α=19˚, spread distance of wak

Acetophenone sulfamethoxazole and 3-Nitrobenzophenone sulfamethoxazole were prepared from the reaction of sulfamethoxazole with two ketones. The prepared ligands were identified by (C.H.N) analysis and UV-VIS, FT-IR spectroscopic techniques. Metal complexes of the two ligands were prepared in an aqueous alcohol with Zn (II), Mn (II) and Cu (II) ions with a molar ratio1:1. The proposed general formula for the resulting complexes was [ML.CL2.H2O]H2O .The complexes were characterized by (C.H.N) technique , spectroscopic methods ,conductivity, atomic absorption ,magnetic susceptibility measurements and melting point. According to the results obtained, the suggested geometry is to be octahedral for all the complexes.

A new ligand (H4L) and its complexes with (CoII, NiII, CuII and PdII). This ligand was prepared in two steps, in the first step a solution of terephthaldehyde in methanol reacted under refluxe with 1,2-phenylenediamine to give precursore compound which reacted in the second step with 2,4- dihydroxybenzaldehyde to give the ligand. The complexes were synthesized by direct reaction of the corresponding metal chloride with the ligand. The ligand and complexes were characterized by spectroscopic methods [FT-IR, UV-vis, 1HNMR, HPLC and atomic absorption], chloride contant in addition to conductivity measurement. The stability constant K and Gibbs free energy ∆G were calculated for [[Ni2(H2L)Cl2], [Cu2(H2L)Cl2] complexes using spectrophoto

New metal complexes of the ligands 2-benzamido benzothiazole(B1), and 2-actamido benzothiazole(B2) with metal ions Ni(II),and Co(II) were prepared in alcoholic medium. The prepared complexes were characterized by FT-IR and electronic spectroscopy, Magnetic susceptibility, Flame Atomic Absorption technique as well as elemental analysis and conductivity measurement. From the spectral studies, an octahedral monomer structure proposed for Ni(II) complexes, and a tetrahedral monomer structure for Co(II)complexes.Semi-empirical methods (PM3,and ZINDO/1)were carried out to evaluate the heat formation( ?H?f)binding energy(?Eb) and dipole moment(µ)for all metal complexes. Also vibration frequencies, Electrostatic potential, HOMO and LUMO

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

The first molecular research on Iraqi centipede fauna is presented in this article. Between October 2022 and May 2023, during various climatic circumstances, centipedes were collected from several locations in four provinces of Iraq. Three families, represented by four genera, underwent molecular identification, and five species were found. From the order Scolopendromorpha family Scolopendridae, two species were recorded, Scolopendra morsitans Linnaeus, 1758, and S. cingulata Latreille, 1829, Cormocephalus sp.; while from the order Lithobiomorpha, family Lithobiidae, one species was recorded for first time in Iraq; Lithobius crassipes L. Koch, 1862 from the order Geophilomorpha family Himantariidae, one species Bothriogaster Signata

Thermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.