This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets. Overall, the findings highlight AI’s potential to improve productivity, lower carbon footprints, and support the transition toward more efficient and sustainable energy systems. This work provides strategic insights for stakeholders seeking to align technological advancement with sustainable energy transition objectives.
Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t
If the Industrial Revolution has enabled the replacement of humans with machines, the digital revolution is moving towards replacing our brains with artificial intelligence, so it is necessary to consider how this radical transformation affects the graphic design ecosystem. Hence, the research problem emerged (what are the effects of artificial intelligence on graphic design) and the research aimed to know the capabilities and effects of artificial intelligence applications in graphic design, and the study dealt in its theoretical framework with two main axes, the first is the concept of artificial intelligence, and the second is artificial intelligence applications in graphic design. The descriptive approach adopted a method of content
... Show MoreThe sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI genera
... Show MoreThe study explored applications of artificial intelligence and its dialectical relationship with international human rights law of individuals, which requires assessing the effects of this technology on human rights and freedoms. The problem of privacy of humanity, as AI technologies can control human rights and freedoms, while monitoring potential violations in this context. The study use of documentary research and qualitative lens to analyze the data. In conclusion, unawareness of the use of AI may impose significant hurdles on future generations and may infringe on human rights across all sectors of society. The government should mandate obligations for artificial intelligence businesses concerning education, health, human right
... Show MoreThis research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche
... Show MoreThe paper aims to build a model that supports organizational sustainability by analyzing the correlations and revealing the impact between the two main variables (entrepreneurial leadership) with its dimensions of proactive outlook, risk, and creativity (Van Zyl & Mathur-Helm, 2007), and (organizational sustainability) with its economic, environmental, and societal dimensions (Hansmann et al., 2012). As well as identifying the level of awareness and informing managers in the General Company for the Automotive and Equipment Industry, of the theoretical implications and performance, and its vital importance to society and the surrounding ecological environment, and drawing attention to that and improving performance, and indicatin
... Show MoreOptimization of gas lift plays a substantial role in production and maximizing the net present value of the investment of oil field projects. However, the application of the optimization techniques in gas lift project is so complex because many decision variables, objective functions and constraints are involved in the gas lift optimization problem. In addition, many computational ways; traditional and modern, have been employed to optimize gas lift processes. This research aims to present the developing of the optimization techniques applied in the gas lift. Accordingly, the research classifies the applied optimization techniques, and it presents the limitations and the range of applications of each one to get an acceptable level of accura
... Show MoreWith the spread of the use of liquefied petroleum gas (LPG) in developing countries for use in domestic cooking with the increase in the expansion and distribution of gas pipelines for residential buildings, the 2002 World Summit focused on sustainable development in clean energy for natural gas (NG) and LPG. The research aims to focus on the important aspects of design sustainability from an environmental point of view to reduce gas leakage, accidents, and explosions that occur socially to expand the distribution of LPG and motivate the consumers to use it instead of natural gas and other fuels, and from an economic point of view to take into account the annual cost and aesthetic imp
Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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