Journal of Petroleum Research & Studies

A geophysical study investigation was conducted in the southern part of Iraq bounded by coordinates; longitudes (39◦ - 48◦) East and latitude (29◦ - 32◦) North. This study includes analysis and interpretation of the potential data (gravity and magnetic) derived from the Bouguer anomaly map and Aeromagnetic total field intensity map of Iraq both of them is within the scale of (1: 1,000,000) and do comparison with the information available from geological maps, which include Tectonic, Hydrological and Geological information.
Gravity and Magnetic maps of the study area were digitized at a grid interval of (1×1) cm which is equivalent to (10×10) km on the land. The trend surface technique was applied on the Bouguer anomaly map of the area. Through these analyses there are three tectonic boundaries have been proposed (A, B, and C). Results were compared with potential analyses of available geological information which match some faults proposed through data analysis with other geological information.

Drilling soft and fragile areas such as (high permeable, cavernous, fractured, and sandy formations) have several problems. One of the most critical problems is the loss of drilling fluid into these formations in whole or part of the well. The loss of drilling fluid can lead to more significant and complex problems, such as pipe sticking, well kick, and closing the well. The drilling muds are relatively expensive, especially oil-based mud or those that contain special additives, so it is not economically beneficial to waste and lose these muds. Artificial neural networks (ANN) can predict drilling fluid losses before they occur based on drilling parameters data and drilling fluid properties of wells effected by lost circulation problems located in the same area. This paper developed two artificial neural network models to predict drilling fluid losses in the Dammam formation- Rumaila oil field in southern Iraq. The two models have the same topology and structure. The first model used the early stopping technique to stop the training when we get the global minimum and the second model used specific epochs to complete the training. The models could predict various types of losses with high accuracy. The accuracy of implementing R2 for the first and second models was 0.9302 and 0.9493, respectively. The early stopping technique lead to obtain a model with acceptable accuracy in a short time without relying on a specific number of epochs.

The injection of Low Salinity Water (LSWI) as an Enhanced Oil Recovery (EOR) method has recently attracted a lot of attention. Extensive research has been conducted to investigate and identify the positive effects of LSWI on oil recovery.
In order to demonstrate the impact of introducing low salinity water into a reservoir, simulations on the ECLIPSE 100 simulator are being done in this work. To simulate an actual reservoir, an easy static model was made. In order to replicate the effects of injecting low salinity water and normal salinity, or seawater, the reservoir is three-phase with oil, gas, and water. It has one injector and one producer.
Five cases were suggested to investigate the effect of low salinity water injection with different concentrations and the period of injection.
The low salinity injection period varied from twenty-five years in case one and reduced five years in each case until reached to five years in final case.
Higher oil recovery factor obtained in case one with injection time twenty-five years and lower recovery factor for case five with injection time of low salinity water injection five years.
Lower water concentration gives higher oil recovery for all cases where this study investigated the effect of low-salinity water flooding as slug injection.
From the five cases presented, field oil recovery factor (FOE), field oil production rate (FOPR), field oil production total (FOPT), field pressure (FP), and field water cut (FWCT) were observed. Oil recovery is 56.6 percent in high salinity water flooding (HSWF), and 71.8 percent in low salinity water flooding (LSWF) for 0 percent salt concentration and 62.40 percent for 20 percent salt concentration as in case one.

Heterogeneity refers to a not uniform distribution of reservoir properties. To overcome the problem of heterogeneity, most reservoir studies split the reservoir into different zones. In general, this disparity affects all log tools. Sonic shear wave time (SSW) is a critical metric in geomechanical modeling that is strongly influenced by reservoir heterogeneity and the kind of porous fluid composition. To detect the effect of reservoir heterogeneity on SSW prediction, an artificial neural network (ANN) was applied as an intelligent technique. One Iraqi vertical well that penetrated the Asmari reservoir was selected for this study. It contains 2462 SSW measured points as well as the following seven log parameters: Gamma Ray, Caliper, Density, Neutron, Compressional sonic, and True resistivity log over measured depth. Based on formation assessment and available well data, the Asmari reservoir was classified into six zones (with different lithology and different fluid content): A, B1, B2, B3, B4, and C. To investigate the effect of lithology on SSW, two runs of ANN had been conducted in this study.
Initially, we developed a single ANN for all 2462 measured points, while in the second, six ANNs were built, one for each zone. The optimum structure for all the developed ANNs was obtained with one hidden layer of 12 neurons (7-12-1). The statistical parameters used for comparison are average percent error (APE), absolute average percent error (AAPE), standard deviation (SD), mean square error (MSE), and correlation coefficient (R2). It was observed that these parameters are approximately close to each other for the developed seven ANNs. The R2 values of the seven ANNs are 0.98 for all zones, and 0.99, 0.99, 0.99, 0.99, 0.99 and 0.96 for each zone respectively. The insignificant differences of results can be explained by the fact that the log readings (i.e. inputs variables) are already reflected the effect of lithology. Therefore, we recommended using the ANN based on 2462 for predicting SSW to any lithology zone. A mathematical model for representing the suggested ANN to simplify the calculation.

Increasing demand for cooling operations in the oil and other sectors, this has led to an increase in electrical energy consumption. The most sustainable solution is to use absorption cooling technology by utilizing solar heat as driving energy instead of electricity. The primary advantage of absorptive cooling is lower electricity costs. In this study, the effect of changing the thermal storage capacities of hot and cold storage tanks and the solar collector area on the performance of the absorption air conditioning cycle was investigated. The optimum operating conditions, the maximum number of processing hours, and the optimum performance coefficient of the absorption conditioning cycle system were selected. The water-lithium bromide solution was used as a fluid in the sorption cycle, and glycerin was used in the hot and cold tank cycle and in the solar collector because it can with stands both high and low temperatures.
The simulation process was carried out using (Fortran 90) program with the help of (Port log) program, (Carrier HAP420) program and (Curve Expert) program. The absorption conditioning cycle was simulated during the day to choose the best capacity for hot and cold storage tanks, as well as to choose the solar collector with the best performance factor. Changing the area of the solar collector (from 9.6 m2 to 16.7 m2), and the volume of the hot tank (from 0.55 m3 to 1.4 m3) have been done to provide the maximum temperature that the hot tank can reach with varying expected cooling load per hour, as well as the size of the tank cold (from 0.9 m3 to 1.6 m3) which gets additional cooling capacity, since the effect of these variables was tested separately.
According to the research results, the best and most suitable volume for the hot tank is (0.55 m3), and for the cold tank is (1.5 m3), and the best and appropriate area for a solar concentric collector is (11.7 m2), which can provide longer running hours. Finally, the higher the generator's temperature, the higher the system's coefficient of performance (COP). The lowest COP value (0.68) is used to guarantee that the system runs for longer periods of time.

Corrosion is a major problem in the petroleum industry, which often occurs to crude oil production equipment and to petroleum product transportation pipelines as well. In order to protect these parts from corrosion, much small quantities of inhibitors are constantly injected, which gradually formulate a fluffy layer of inhibitor over the metal surface so as to protect it from corrosion. Recently, the impact of corrosion inhibitors on the environment has been raising more attention and concern. New regulations related to environment have been designated, imposing a change in the use of toxic chemicals to the utilization of the so-called “green chemicals”. Experiments on carbon steel corrosion protection have been conducted in a medium of crude oil has an API gravity of 30.6 by using different concentrations, ranging between 100 – 400 ppm of different green inhibitors such as corn oil, sunflower oil, flaxseed oil and castor oil with a different rotation speeds, namely, 0, 500, 1250 and 2000 rpm. The weight loss outcomes have showed that the rate of carbon steel corrosion in the crude oil decreases with the rise of inhibitors’ concentration, while corresponds with the increase of the rotational speed. In addition, it was found that the maximum inhibition efficiency achieved for the inhibitors corn oil, sunflower oil, flaxseed oil and castor oil in crude oil was using a concentration of 400 ppm, a rotation speed of 0 rpm and an ambient temperature (25 °C) is 41.85%, 50.76%, 63.55% and 92.63%, respectively.

This study determines the effects of UV radiation and heat treatment on many flow and mechanical parameters of PEG 4000, including flow time and viscosity (specific, reduced, relative, and intrinsic). Solubility time and shore D hardness are among the mechanical characteristics. By adjusting the concentrations of solutions in the range (0.01–0.03) g/ml of heating and non-heating PEG powders, and examining the polymer's solubility at the same time, the flow characteristics of the polymer are explored. Random glass fiber reinforcement in the range of 0.1–0.4 wt has also been studied to indicate the effect on shore hardness. After exposing the produced plates to ultraviolet light, the efficacy of the plates in purifying the oil from contaminants was investigated. The results show that increasing the concentration increases all types of viscosity and flow time, with the exception of intrinsic viscosity, which decreases as concentrations increase. Other parameters decrease after the first UV ray and heat treatment, but increase as the time of UV ray treatment increases. Furthermore, increasing the weight ratio of glass fibers from 0.1 to 0.4 wt lowered shore hardness, whereas increasing the weight ratio at the same previous range increased it after UV rad. While solubility data refers to increasing polymer weight and radiation help increase solubility time. The filtration efficacy of the small particles of the produced filters increased after the overlapping plates were exposed to UV radiation, owing to the smaller pore diameters.

Adsorption is kinetically time-dependence controlled retention/ release mobility as a natural phenomenon in base and applicable in industry or in science. It is well-studied and modulated by known Langmuir, Temkin, Freundlich, and other models to describe how it occurred and explains kinetic- thermodynamic material behaviour.
Linear and/ or non- linear expressions may take place according to the theoretical base of these models to conclude the layer formation, uniformity besides reaction reversibility, and favourability from kinetic- thermodynamic principles.
Coefficient of determination (R2) is a mean variation of data or a degree of proper or fitting as mostly used in kinetic and isotherm literatures. In adsorption investigations, experimental physical- chemical conditions and error sources are the main influenced factors, for example, at surface coverage (or inhibition efficiency) in corrosion treatments or adsorption capacity in pollution subject. Linearity variation will govern R2 to predict adsorbate behaviour on adsorbent surface that is highly influenced by concentration, temperature, pH, type of measuring method, physical and chemical structures of the adsorbent and adsorbate, and error sources in each experiment.

This study sought to uncover factors affecting access to clean energy in the Arab region requiring. The exploration of new clean energy sources, thus the objectives of the present article are to study the impact of green investment and renewable energy sources (Solar, bioenergy, hydropower and wind energy) on sustainable development in the region in terms of guiding policymakers to develop clean and sustainable development policies to build a green economy. The study found that the reflection of sustainable development Goal 7 requires global access to modern, reliable, sustainable and affordable energy by 2030. It also seeks to increase the share of renewable energy in the global energy mix, improve energy efficiency by 100% and then expand infrastructure and improve supply technology.

Oil wealth is one of the important topics that have received wide attention at the international and regional level due to its importance in all fields, and on the other hand because it poses a threat to the environment, public health and biological diversity due to its wrong use, so the Iraqi legislator was keen to criminalize pouring oil on the surface of the earth or injecting it into Classes that are used for human and agricultural purposes, and then he arranged punitive provisions on the perpetrator of the crime and made them fall under penalty of misdemeanor in terms of severity with the penalty of imprisonment, and his provisions represented by the legal basis for them were mentioned in the Iraqi Environmental Law No 27 of 2009 in force.