Gas compressibility factor or z-factor plays an important role in many engineering applications related to oil and gas exploration and production, such as gas production, gas metering, pipeline design, estimation of gas initially in place (GIIP), and ultimate recovery (UR) of gas from a reservoir. There are many z-factor correlations which are either derived from Equation of State or empirically based on certain observation through regression analysis. However, the results of the z-factor obtained from different correlations have high level of variance for the same gas sample under the same pressure and temperature. It is quite challenging to determine the most accurate correlation which provides accurate estimate for a range of pressures,

   The petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli

Resource estimation is an essential part of reservoir evaluation and development planning which highly affects the decision-making process. The available conventional logs for 30 wells in Nasiriyah oilfield were used in this study to model the petrophysical properties of the reservoir and produce a 3D static geological reservoir model that mimics petrophysical properties distribution to estimate the stock tank oil originally in place (STOOIP) for Mishrif reservoir by volumetric method. Computer processed porosity and water saturation and a structural 2D map were utilized to construct the model which was discretized by 537840 grid blocks. These properties were distributed in 3D Space using sequential Gaussian simulation and the variation in

Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe

Reservoir study has been developed in order to get a full interesting of the Nahr Umr formation in Ratawi oil field. Oil in place has been calculated for Nahr Umr which was 2981.37 MM BBL. Several runs have been performed to get matching between measured and calculated of oil production data and well test pressure. In order to get the optimum performance of Nahr Umr many strategies have been proposed in this study where vertical and horizontal wells were involved in addition to different production rates. The reservoir was first assumed to be developed with vertical wells only using production rate of (80000–125000) STB/day. The reservoir is also proposed to produce using horizontal wells besides vertical wells with production rat

Twenty nine core samples were taken from Ratawi 7 Oil well according to the presence of oil in formation and availability of core samples. This well is located in the province of Basra/southern Iraq. The samples were collected from Yamama Formation. The core samples are taken from the well at different depths, ranging between (3663m-3676m). The range of Vp for these core samples is (668-4017 m/sec) and its average is (1779 m/sec), While the range of Vs is (291-1854 m/sec) and its average is (796 m/sec). In the current study the ultrasonic method is conducted to measure Vp, Vs as well as some petrophysical properties for core samples and some elastic moduli such as (Young's modulus, Bulk modulus, Shear modulus, Poisson's ratio and Lame's

     Since oil is the primary source of vanadium in the environment and crude oil has a correspondingly high percentage of vanadium. Vanadium is crucial as a sign of oil contamination. Twenty soil samples were taken from various locations surrounding the East Baghdad oil field in Iraq during February 2022 and then analyzed to determine the effects of industrialization along with urbanization-related pollutants. The soil samples were analyzed using spectrophotometry analysis. In soil samples taken from the research area, vanadium concentrations range from (0.26 to 1.2 ppm). The contamination (CF), geoaccumulation (Igeo) and Enrichment factors (EF) indicated that all the soil samples are uncontaminated.

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological