Iraqi Journal of Oil and Gas Research

The main purpose of this paper is to activate the death well called K22 (for confidential reasons) by injecting hot steam into the reservoir to reduce the viscosity of oil and increase the production rate. PVT, reservoir, well, completion and injection data are entered via prosper and Reveal software’s in order to analyze the performance of the initial well, to implement the hot steam injection method and to analyze the performance of the well K22 after the injection of hot steam using the nodal analysis method. The results initially obtained show that well K22 does not produce. To solve this problem, the injection of hot steam method provides from the nodal analysis for a liquid production rate of 2200 STB/day and a critical pressure of 2337.78 psi where the production rate of oil is 2187.8 STB/day, the water production rate is 21.1 STB/day and the gas production rate is 0.10894 STB/day for water cut of 0.92 %. The hot steam injection method is appropriate to put in production in well K22 because it reduces the density of the oil which facilitates its flow towards the production well. Therefore, it maximizes the oil production and it allows a profitability of $ 3158366.721 with a return on investment after 3 months and 3 days for 4 years of production.

The hydroisomerization process of light naphtha is the chief process to produce high-octane gasoline in petroleum refineries. The reaction mechanism is designed to produce branched hydrocarbons with high octane numbers.
The hydroisomerization reaction mechanism over bifunctional catalysts is influenced by both acid and metallic sites on the catalyst surface. Moreover, it was found that the product quality and distribution in this process are highly dependent on the catalyst type and operating conditions in the fixed-bed reactor. The feed quality (light naphtha) is the major challenge in this process due to its direct effect on the catalyst activity, selectivity, and deactivation mechanism (catalyst lifetime). According to the results of many authors, it has been observed that the pre-treatment processes usually carried out on the light naphtha feedstock provided high performance for the applied bifunctional catalysts.
Finally, the economic feasibility of this process is a function of the catalyst type and its resistance to the contaminants present in the light naphtha.

Soil is one of the main resources that human beings rely on to survive. Since petroleum hydrocarbons are used more widely over the world for energy and raw materials in many applications, a wide range of pollutants have been released into the environment. In addition, accidental emissions of petroleum products have been causing serious soil pollution and deteriorating soil quality. Numerous global ecological, environmental, and health problems are the outcome of this pollution. Efforts are intensifying today to develop methods for treating soil contaminated with petroleum essentially to restoring soil function and recover the ecosystem. This paper reviews several in situ or ex situ treatments techniques including thermal, physico-chemical, biological methods and these treatment methods involve other techniques and strategies that combine between two techniques in order to increase the removal efficiency also had been reviewed. Each technology has advantages and disadvantages and depends on several factors that affect its efficiency. Therefore, to choose the appropriate technology, it is important to study and understand each technology separately, and the other factors that affect it, and when we need to combine two or more technologies.

The study investigated the influence of the dynamic load of a 6061-T6 aluminum plate with two fixed edges with dimensions of 80 mm and two free edges at variable dimensions of 80 mm, and 160 mm. A crack was created in the middle of an aluminum plate using a laser beam of thickness 0.08mm. The crack had different lengths, 3mm, and 5mm, and was created at angles of 0, 45, and 90 degrees. The study focused on determining the initial crack growth caused by the dynamic impact load on the crack area of an aluminum plate caused by the free fall weight at a rate of 20 impacts per minute, the study performed experimental, numerical, and analytical investigations. Based on the experimental results, it was observed that increasing the crack length from 3 mm to 5 mm reduced the initial growth time by 45% in a plate with an aspect ratio of 1:1. However, in a plate with an aspect ratio of 1:2, the percentage of reduction in initial growth time was 16.5%. The results showed that increasing the crack angle from 0 to 90 degrees prolonged the crack growth in all samples with the same test conditions. The study aims to analyze crack growth in aluminum alloy 6061-T6 under dynamic impact loads with different boundary conditions. The research provides insights into material behavior in thin plates of an oil and gas alloy, contributing to developing better products and processes for the industry.

One of the most crucial phases in creating an accurate and ideal field development plan for oil and gas projects is evaluating the formation and characterizing the reservoir. Many different types of data are required for reservoir characterization and modeling, including wireline logs, LWD logs, SCAL data, geology and seismic data. Furthermore, sufficient understanding of the underlying physical interactions between each parameter. Recent developments in artificial intelligence and neural network-based petroleum exploration technology have opened up new possibilities for the sector in terms of reservoir characterization, that is more affordable, effective, and precise. Several research works pertaining to the application of artificial neural networks (ANNs) in the petroleum sector were examined, synthesized, and categorized into four main categories: applications in exploration, drilling, production, and reservoir engineering. An overview of applications of artificial neural networks in petroleum engineering was presented. An established process for using ANNs in any petroleum application was performed and displayed through a flowchart that may be used as a useful guide to implement ANNs for any petroleum application.

Sand production is a worldwide issue for all oil and gas wells are producing from sandstone reservoirs. Along past century many of authors and companies worked on putting suitable solutions for this situation that causing many problems as decreasing of fluid production reach to well shutdown. In present paper many published manuscripts that dealt with employment artificial intelligent approaches in predicting the onset of sand production are reviewed. The reviewed artificial intelligent approached are developed to perform one main target: the sand onset production prediction. This main target is detected by employment different ways such as artificial neural networks, generalized regression neural network, feedforward neural network, genetic algorithm, particle swarm optimization and support vector machine. Many influencing parameters on sand production initiation are used as inputs for these models likewise: total vertical depth, transit time, gas and water flowrates, formation cohesive strength, bottom-hole shut-in and flowing pressures, drawdown, critical drawdown pressure, effective overburden vertical stress, interval length, perforation density, and sand free production duration in years. The models results were in many terms including predicted critical drawdown pressure for sanding onset, or for making sand production probability in term of numbers (minus one, zero or positive one). The main conclusion from this review, the accurate artificial intelligent approach for sand onset production need to accurate and large data set as well as the results accuracy proportional to progress and development in artificial intelligent tools.

This study involves designing and constructing a simulated Fitcher-Tropich bubble column reactor (FTBCR) that features a real heat exchanger, to investigate the influence of a real heat exchanger into a bubble and slurry bubble column (BC and SBC). The investigations were conducted in a (0.15 m) inner diameter Plexiglas (BCR) with varying gas flow rates ranging from (0.14m/s to 0.35m/s).
To replicate the industrial (FTBCR), a real heat exchanger was vertically installed, occupying 25% of the column cross-section, and comprised 18 copper tubes, each with a diameter of (0.016 m). Glass beads represented the solid phase with an average size of (150 μm), which were loaded volume of 40%. Furthermore, this investigation employed an advanced heat transfer technique to quantify the impact of the tubes and solid particles on the local instantaneous heat transfer coefficient (LIHTC). The investigations were conducted at three axial locations (H/D = 2, 3, and 4) and six radial sites along the column's diameter (±0.18, ±0.46, and ± 0.74). The results indicated that the (LIHTC) decreased as the gas flow rates increased at all radial and axial positions. Moreover, the (LIHTC) in the central zone increased by 82% compared to near the wall in two and three phases.
The model's validation was assessed by comparing the predicted and experimental values of (LIHTC) using Minitab software and response surface methodology (RSM). The results were consistent with the experimental results.
The regression model achieved for (LIHTC) in two and three phases (BCR) was (R2) (95.90) and (97.49), respectively.