Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

In the present work, bentonite clay was used as an adsorbent for the removal of a new prepared mono azo dye, 4-[6-bromo benzothiazolyl azo] thymol (BTAT) using batch adsorption method. The effect of many factors like adsorption time, adsorbent weight, initial BTAT concentration and temperature has been studied. The equilibrium adsorption data was described using Langmuir and frundlich adsorption isotherm. Based on kinetics study, it was found that the adsorption process follow pseudo second order kinetics. Thermodynamics data such as Gibbes Free energy ∆Gᵒ, entropy ∆Sᵒ and ∆Hᵒ were also determined using Vant Hoff plot.

Stable isotopes 18O/16O and 13C/12C in the carbonate rocks of the Mishrif Formation are examined here to define the depositional characters in the basin includes paleo temperatures and paleo depth.      The Mishrif formation (Cenomanian – Early Turonian) has extensive distribution in Iraq and Middle East. Mishrif Formation composed of organic detrital limestone. Four boreholes in four oilfields, Noor – well (11), Amarah – well (14), Buzurgan – well (24), Halfaya – well (8), in south east of Iraq have been studied. The studied samples have negative δ18O isotope values studied well, with Average (-4.11‰), (-4.47‰), (-4.48‰), (-4.18‰) in the studied wells res

In recent years, non-oil primary balance indicator has been given considerable financial important in rentier state. It highly depends on this indicator to afford a clear and proper picture of public finance situation in term of appropriate and sustainability in these countries, due to it excludes the effect of oil- rental from compound of financial accounts which provide sufficient information to economic policy makers of how economy is able to create potential added value and then changes by eliminating one sided shades of economy. In Iraq, since, 2004, the deficit in value of this indicator has increased, due to almost complete dependence on the revenues of the oil to finance the budget and the obvious decline of the non-oil s

The objective of this in vivo study is to investigate the effects of 337.1 nm pulsed N2 laser on cellular immune response represented by lymphocyte transformation capacity and phagocytosis activity in laboratory animals. The samples include 60 adult male BALB/c mice, were divided into control group and experimental groups. The experimental groups were divided into two main groups according to the time period after N2 laser irradiation. Each group was divided into 9 subgroups which exposed to N2 laser radiation at different values of pulse repetition rates and exposure times. The results of immunological tests demonstrated that the exposure to 180 J/cm2 of N2 laser radiation induce adverse effect to cellular immune response. The results o

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin

Massive multiple-input multiple-output (massive-MIMO) is considered as the key technology to meet the huge demands of data rates in the future wireless communications networks. However, for massive-MIMO systems to realize their maximum potential gain, sufficiently accurate downlink (DL) channel state information (CSI) with low overhead to meet the short coherence time (CT) is required. Therefore, this article aims to overcome the technical challenge of DL CSI estimation in a frequency-division-duplex (FDD) massive-MIMO with short CT considering five different physical correlation models. To this end, the statistical structure of the massive-MIMO channel, which is captured by the physical correlation is exploited to find sufficiently

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl^-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor

Background: Insulin resistance is associated with metabolic syndrome , type 2 diabetes and representing a risk factor for cardiovascular disease . This relationship may be modulated to some extent by age related changes in sex hormone status.. In particular, reduced total testosterone (TT) levels have been associated with insulin resistance and subsequent risk for developing type 2 diabetes. Aim of study: we examined whether low total testosterone level were associated with insulin resistance in young adult men. Methods: a total of 83 men (young adult men) divided into 2 group : (group1 ) 49 men with a risk factor for insu