Petroleum Business Review

Abstract This study aims to map the knowledge structure and elucidate the research trends related to the “sustainable supply chain” in the petrochemical industry. To this end, a total of 906 documents indexed in the Scopus database from 2000 to 2025 were collected and subjected to bibliometric analysis using VOSviewer and Biblioshiny tools. The results indicate that the scientific output in this field has experienced significant growth since 2010 and reached a maturity stage after 2019. Collaboration network analysis highlights the prominent role of the United States, the United Kingdom, and China in shaping the literature of this domain, alongside the gradually increasing contributions of countries such as Iran, Malaysia, and Brazil. Co-occurrence analysis of keywords reveals several established thematic clusters and interdisciplinary linkages among engineering, management, and environmental studies. By providing a comprehensive overview of the intellectual, conceptual, and social structure of the field, the findings of this study can serve as a foundation for guiding future research and supporting practical decision-making aimed at enhancing sustainability in the petrochemical supply chain.

Abstract In the context of the energy transition and increasingly stringent climate policies, understanding oil demand requires a product-specific perspective that goes beyond aggregate indicators. This study examines naphtha, a key feedstock linking the refining and petrochemical sectors, and analyzes the factors associated with its demand across ten major oil-consuming countries during 2000–2024. Using long-term panel data, naphtha prices are first modeled as a function of crude oil prices through an ARMA specification, after which a naphtha demand equation is estimated with cross-section fixed effects and a lagged dependent variable. The results indicate that naphtha demand is significantly associated with economic growth and downstream petrochemical product prices, especially olefins and aromatics. The positive and statistically significant lagged demand term suggests persistence and gradual adjustment in consumption, consistent with structural inertia in petrochemical feedstock use. Overall, the findings suggest that the energy transition may reshape the composition of oil demand rather than lead to a uniform decline across all petroleum products. The results provide policy-relevant insights for product-specific energy-transition strategies, refinery reconfiguration, and refinery–petrochemical integration, while underscoring that the estimated relationships should be interpreted as conditional associations rather than causal effects.

Abstract Iran’s oil refining industry, which serves as the backbone of the national economy and supplies over 95% of domestic transportation fuel requirements, is situated at the intersection of geopolitical challenges, global energy transition dynamics, and increasing environmental pressures. Adopting a foresight studies approach, this research identifies and analyzes the strategic drivers and uncertainties that will influence the design and development of Iran’s petroleum refineries through 2050. Utilizing a mixed-methods methodology encompassing a systematic literature review, analysis of international reports (OPEC, Shell, IEA), macro-level (PESTEL) and micro-level (Porter’s Five Forces) analyses, semi-structured expert interviews, and MICMAC (Matrix of Cross-Impact Multiplications Applied to a Classification) structural analysis, 34 key factors were extracted and ranked. The findings indicate that foreign policy, domestic governance, demographic trends, global energy transition, emerging technologies in the oil, gas, and petrochemical sectors, environmental policies and regulations, and domestic consumption patterns are the eight principal drivers steering the system. Furthermore, the results demonstrate that the confluence of environmental pressures (decarbonization, stringent environmental regulations), shifting demand patterns toward petrochemical products, and restricted access to advanced technologies owing to sanctions reinforces the strategic imperative to transform conventional refineries into integrated “petro-refinery” complexes. This study provides a dynamic roadmap for policymakers and industry leaders to enhance sectoral resilience, decarbonization, and global competitiveness through integrated petro-refineries, novel technologies, and smart governance while capitalizing on opportunities arising from the eastward shift of global energy gravity.

Abstract Purpose: This study examines the impact of product diversification on asset returns in petrochemical companies using a kernel density approach, addressing contradictory findings in the diversification-performance literature within this capital-intensive sector.
Design/methodology/approach: Employing an ex-post facto research design, we analyzed data from petrochemical companies listed on the Tehran Stock Exchange from 2011 to 2021. The study utilized a two-stage analytical approach: first classifying companies into life cycle stages (growth, maturity, decline) using discriminant analysis, then testing hypotheses through multivariate regression and cross-sectional analysis. The kernel density estimation provided a non-parametric assessment of diversification effects.
Results: The results demonstrate that product diversification significantly enhances asset returns in petrochemical firms, with the Herfindahl index revealing seven distinct market concentration levels. The positive effect of diversification was particularly pronounced in monopolistic market structures. Empirical evidence confirms that diversification serves as an effective strategy for improving financial performance and mitigating market dependence.
Originality/value: This research contributes to the literature by introducing kernel density estimation to diversification analysis, providing a more nuanced understanding of return distributions beyond traditional parametric methods. The study also offers unique insights into the petrochemical sector's dynamics in emerging economies, highlighting how market structure moderates the diversification-performance relationship.
Practical implications: The findings suggest that managers should prioritize diversification strategies, especially in monopolistic environments, to enhance asset utilization and financial resilience. Policymakers can use these insights to design industrial policies that encourage strategic diversification in response to Iran's economic conditions.

Abstract The need to speed up the creation of innovation in the oil industry and support it properly in order to respond to the increasing needs of the world today has caused activists in this field to use various forms of protection. Patent systems and trade secrets are the main ways of protecting intellectual achievements in the oil industry. In recession conditions such as the Corona epidemic, which had a negative impact on the production and income generation of oil companies, intangible assets such as trade secrets or registered inventions could be a very good source of income for these companies. The complexity and longevity of technology in the upstream field of the oil industry has caused the reluctance of companies active in this field to register patents, which will slow down the dissemination of knowledge, creation and development of innovation. Therefore, due to the necessity of energy production, lack of resources and the need for complex and combined technologies in this field, patenting becomes inevitable.

Abstract The present study examines the investment model of the National Development Fund (NDF) in the upstream oil and gas industries, focusing on the risks associated with field development. Given the NDF's recent entry into the investment arena, the challenges in this field have been analyzed in this article. Furthermore, the NDF 's investment policies and guidelines, project prioritization, and the Non-Meddle Investment model (I-HOPE) as the NDF’s main strategy to reduce risk and increase resource effectiveness are introduced and analyzed in detail. Finally, alongside a comparative review of the NDF’s investment model and field development challenges, solutions are proposed to improve the NDF’s investment process in this sector. This study, by evaluating the strengths and weaknesses of the I-HOPE model in confronting the inherent risks of field development, provides a framework for optimizing future investments. These measures help the NDF to optimally manage risks, increase resource returns, and play a more effective role in the country's economic development.
Keywords: Non-Meddle Investment Model, Risk, Uncertainty

Abstract West Texas Intermediate (WTI) crude oil is a pivotal benchmark in the global energy market, exerting a decisive influence on economic expectations and national macroeconomic policies. As the primary pricing basis on the New York Mercantile Exchange and numerous energy futures contracts, WTI is subject to persistent and severe price volatility. Such fluctuations, often appearing as abrupt upward or downward shocks, profoundly affect key macroeconomic indicators. These include inflation, economic growth, trade balances, corporate profitability, production costs, and government budgets. Consequently, variations in WTI prices influence oil and gas markets, financial stability, energy security, and even international geopolitical relations. To address these challenges, this study develops a hybrid VMD+SVR framework to model and forecast WTI crude oil futures prices across short-, medium-, and long-run horizons. Empirical findings reveal that across all three horizons, the proposed hybrid model consistently achieves the lowest forecasting errors compared with alternative approaches. Moreover, the Diebold–Mariano and Wilcoxon tests statistically confirm the superior predictive performance of the hybrid VMD+SVR model. These results highlight the importance of integrating advanced adaptive signal decomposition (VMD) with powerful nonlinear learning algorithms (SVR) for accurate oil price forecasting. The proposed approach not only enhances forecasting accuracy but also provides practical insights for policymakers in managing economic risks, stabilizing budgets dependent on oil revenues, and formulating sustainable energy strategies. It opens a new avenue for developing financial forecasting models inspired by advanced signal processing.

Abstract Financing upstream oil and gas projects in Iran—particularly for non-governmental companies—faces numerous obstacles, including the lack of effective guarantee mechanisms, absence of credible collaterals, limited access to sovereign guarantees, and the skepticism of financial institutions. This paper, adopting a descriptive-analytical approach and grounded in the study of existing legal and institutional frameworks, explores the legal capacities for designing and utilizing alternative instruments to traditional guarantees in the financing process of high-risk projects. Within this framework, and based on the “Production and Infrastructure Financing Act”, the executive bylaw on the establishment of non-governmental guarantee funds, and other upstream legal documents, the establishment of an institution titled the "Oil Guarantee Fund" is proposed as an innovative solution. This fund is designed to mitigate default risk, facilitate project credit assessment, and replace bank or property-based guarantees for companies active in the oil and gas value chain. Its legal structure is envisioned based on the model of non-governmental institutions and private joint-stock companies. The proposed model has been formulated through a legal analysis of the relevant documents and informed by the outcomes of expert panels comprising specialists in energy law, finance, and public policy. Findings of the study indicate that the establishment of such a fund, capable of issuing valid guarantees based on contractual commitments, provides a practical tool to strengthen institutional trust and facilitate investment in upstream oil and gas projects. The article also presents a conceptual and institutional framework for the fund and offers recommendations for its policy-level and legal implementation.

Abstract This study investigates the impact of global crude oil price fluctuations on the volatility of the Iranian Rial–U.S. Dollar exchange rate over the period November 2011 to August 2025. Using daily data and employing GARCH-family models—including GARCH(1,1), EGARCH(1,1), and GJR-GARCH(1,1,1) under heavy-tailed distributions—we examine whether oil price shocks influence the mean and conditional variance of exchange rate returns. The results indicate that higher oil prices significantly appreciate the Rial, reflecting Iran’s dependence on oil revenues and foreign exchange inflows. Volatility dynamics reveal strong persistence, with shocks exhibiting long memory. Asymmetric effects are also evident: negative oil price shocks increase exchange rate volatility more than positive shocks, highlighting the destabilizing role of downturns in global oil markets. Diagnostic tests confirm the adequacy of the estimated models, with EGARCH and GJR specifications providing the best fit. The findings underscore three key policy implications. First, Iran’s exchange rate remains highly sensitive to oil revenues, reinforcing the need for structural diversification. Second, the persistence of volatility complicates short-term stabilization, demanding long-term reserve and fiscal policies. Third, the asymmetric impact of oil downturns calls for proactive risk management to mitigate volatility in times of declining oil prices. Overall, the study provides new evidence on the oil–exchange rate nexus in an oil-exporting economy, offering lessons for macroeconomic management under external shocks. Robustness checks — including Bai–Perron breakpoint tests and alternative model specifications with event dummies — confirm the main findings.

Abstract Iran's gas industry plays a strategic role in supplying and distributing natural gas energy to society. The project-based, operational, and service-oriented nature of this industry, combined with its large workforce, underscores the necessity to address the risks confronting its human resource management system. This study was conducted to identify and analyse these human resource management risks. This study employed a mixed-methods approach. In the qualitative phase, the researcher's lived experience was utilized to identify and categorize 35 human resource management risk factors in Iran's gas industry. For the quantitative phase, a risk management framework was applied to evaluate each identified factor based on two key dimensions: risk probability and risk impact. The assessment results were subsequently visualized through a heat map. The study results demonstrated that none of the indicators fell within the low-risk zone, with 15 indicators classified as medium-risk and 20 as high-risk, while two critical indicators - imposition of salary and benefit restrictions with a risk rating of 9 and dependence on political affiliations for filling key positions with a risk rating of 8 - were identified as the most substantial challenges facing the human resource management system in Iran's gas industry.

Abstract The Arash (Al-Durra) gas field, located in the northern Persian Gulf, is a shared natural resource claimed by Iran, Kuwait, and Saudi Arabia. Ongoing maritime boundary disputes have made the development of this field a geopolitical and legal challenge. Game theory is used in this research to model the strategic interactions between the three states under various cooperation and competition scenarios. The results indicate that trilateral cooperation would be the greatest economic and security benefits for all parties; however, political tensions and legal barriers, particularly Iran’s non-membership in the United Nations Convention on the Law of the Sea (UNCLOS), hinder such outcomes in the short term. Iran experiences the greatest losses under competitive strategies, while Saudi Arabia and Kuwait benefit more from bilateral agreements. The study also explores how Iran’s legal position could be strengthened through accession to UNCLOS and the adoption of a flexible strategy that combines active diplomacy with cautious resource exploitation. This approach could improve Iran’s bargaining power and reduce its isolation in the dispute. The research offers a comprehensive analysis of the legal, geopolitical, and economic dimensions of the Arash field conflict and provides actionable policy recommendations to reduce tensions and promote equitable, long-term resource sharing in the region.

Abstract This study conducts a comprehensive examination of the interlinkages among four key financial markets—crude oil, gold, currency, and equities—over the July 23, 2013, to March 12, 2025. This study employs the Contemporaneous and Lagged R2 Decomposed connectedness approach recently introduced by Balli et al. (2023), which allows us to decompose the connectedness among variables into lagged and contemporaneous components. As the previous approaches only show overall or contemporary results, this novel approach fills the gap in the literature. The findings reveal that most spillovers occur contemporaneously, with the U.S. dollar playing a central role in the propagation of contemporaneous shocks. In contrast, gold emerges as a significant transmitter of long-term shocks, underscoring its relevance for strategic risk management. Moreover, crude oil is the main receiver of shocks in the average and lagged connectedness in the network. Dynamic analyses indicate heightened market sensitivity during periods of geopolitical tension, particularly under intensified sanctions and currency volatility in Iran. By uncovering the evolving structure of cross-market dependencies, this research offers valuable insights for portfolio allocation, systemic risk assessment, and the formulation of responsive economic policies in times of financial stress.

Abstract The resource-based model (centered on the extraction and sale of crude oil) has been a significant contributor to the phenomenon of the "natural resource curse," undermining sustainable economic growth. Consequently, this study advocates for a paradigm shift in Iran’s oil industry, moving from the current model of crude oil extraction and export toward a technology-driven model. The technology-centric approach is proposed as a solution to mitigate this challenge and facilitate long-term development. In this context, critical questions arise: How prepared is a nation’s oil industry across technical, human, structural, and other dimensions to adopt a technology-driven approach? This research focuses on the human capability components within Iran’s oil industry for implementing such a model. To this end, 36 components across four key domains—organizational talent management, leadership, human resources, and organizational capabilities—were analyzed using the Importance-Performance Analysis (IPA) method. The findings reveal that leadership-related components predominantly fall within Quadrant I of the IPA matrix, indicating high importance but weak performance, necessitating urgent strategic interventions. Conversely, most human resource components reside in Quadrant IV, reflecting the existing workforce’s high readiness for adopting a technology-driven approach in Iran’s oil industry. Components related to organizational capabilities and talent management are dispersed across multiple quadrants, underscoring the need for tailored policies and context-specific measures. Further results highlight that transitioning to a technology-driven model could yield significant competitive advantages and profitability for Iran’s oil industry. However, this transformation demands a comprehensive evaluation of existing capabilities and the design of targeted strategies to address identified gaps.

Abstract This study investigates the multifaceted challenges of implementing digital transformation within Iranian oil and gas companies, focusing on organizational barriers and managerial solutions. Despite the global momentum toward digitalization, Iran’s oil and gas sector faces unique obstacles, including resistance to change, skill gaps, legacy infrastructure, and insufficient alignment between technology providers and large enterprises. Utilizing a mixed-methods approach, we conducted a survey of 210 managers and IT professionals across upstream and downstream organizations, complemented by in-depth interviews with key stakeholders. Exploratory factor analysis (EFA) and structural equation modeling (SEM) were employed to identify and validate critical barriers and their interrelations. Findings reveal that organizational inertia, lack of digital competencies, and inadequate investment in digital infrastructure are the most significant impediments, while leadership commitment and targeted training programs emerge as effective managerial remedies. The study contributes actionable insights for policymakers and executives by outlining a roadmap for overcoming digital transformation hurdles and achieving sustainable competitive advantage. The results underscore the necessity of a holistic strategy integrating technological, human, and process dimensions to facilitate successful digital transformation in Iran’s oil and gas industry.

Abstract This study uses spatial econometric and dynamic analyses to examine the temporal and spatial effects on three performance indicators of petrochemical companies active in the Tehran Stock Exchange: price performance, retained earnings, and total performance. The target population comprises all petrochemical companies listed on the Tehran Stock Exchange that have been active since the beginning of 2013 to the end of 2024. The findings suggest that, while information asymmetry positively influences companies' retained earnings, it simultaneously has a negative impact on price and total performance. Additionally, an examination of the H-index revealed that the market structure of this industry is monopolistic. However, monopolistic behavior is observed in the distribution of retained earnings, which can be attributed to the centralized structure governing the management of the Iranian petrochemical industry. Findings concerning financial structure suggest that elevated financial leverage and financing costs negatively impact returns, while investment in physical assets has the most favorable impact. Furthermore, identifying significant spatial effects corroborates the idea that proximity and spillover effects between companies are substantial. This study provides substantial empirical evidence that enhancing information transparency, optimizing financial structures, and reforming corporate governance mechanisms could increase market returns and improve stock returns in the petrochemical industry.

Abstract The United States, recognized as the leading global producer and consumer of oil, significantly influences the dynamics of the international oil market. Therefore, changes in governments and their policies in the energy sector have a significant impact on the oil market, especially for oil-exporting countries like Iran. Hence, it is imperative to conduct an analytical assessment of the implications arising from the transition of political power in the United States on the global oil market dynamics. This study examines the implications of Trump's energy policies on the global petroleum market, focusing on Iran. The research employs a qualitative, descriptive-analytical method using desk research to explore how these policies impact Iran's oil exports, market share, and geopolitical standing. Under the Trump administration, the U.S. pursued an "energy dominance" agenda characterized by increased fossil fuel production, deregulation, and a confrontational stance towards OPEC. This neo- mercantilist approach aimed to bolster U.S. energy security and economic leverage. Trump’s Key policies include expanding fossil fuel production, lifting ecological restrictions, and promoting unilateralism in the oil and gas trade. This will likely lead to a decrease in oil prices in global markets, which will, in turn, result in reduced oil revenues for Iran and put pressure on its share. Additionally, Trump's policy of regional confrontation with Iran could also impact these outcomes.

Abstract Climate change is a global issue, driven largely by greenhouse gas emission, with carbon dioxide (CO2) being the biggest contributor. Iran, one of the top 10 emitters globally, faces unique challenges in reducing its CO2 emission due to economic sanctions, data gaps, and limited experience with climate policy. To help guide decision-makers, this study uses the Simplified DICE model—DICE model is a widely accepted tool for analyzing climate and economic interactions—to evaluate different strategies for emission reduction. These strategies mainly include carbon pricing, investment in renewables as mitigation of emission growth, and improving energy efficiency. The results show that such policies can positively impact GDP, temperature stabilization, and emission levels. This research provides the first numerical framework tailored to Iran’s specific context, offering practical insights for policymakers. Key policy implications include the necessity to overcome sanctions in aspects of Investment and technology absorption, improved data collection to refine future analyses, and adopting cost-effective measures that balance economic growth with environmental sustainability.

Abstract Iran, as an oil-dependent economy, has faced strict energy sanctions from the Western bloc, prompting the country to adopt policies aimed at enhancing energy economic resilience. Given the similarities in economic structure, this paper explores the concept of energy economic resilience in Russia under sanctions. Following Russia's special military operations in Ukraine, successive Western sanctions were imposed on Russia, primarily targeting its energy sector and global exports. This study aims to identify the key components affected by these sanctions by examining Russia’s energy security within a structured framework. The findings indicate that sanctions have had a negative impact on Russia's energy security and inflicted economic damage. However, Russia has demonstrated resilience in its energy sector by implementing strategic policies, such as diversifying oil and gas export destinations and strengthening energy transportation infrastructure through investment and new projects. Despite these successes, Russia remains highly dependent on fossil fuel extraction and exports, with limited progress in increasing the share of renewable energy, which remains a major weakness.

Abstract This study explores the intricacies and challenges of financing the oil and gas industry in Nigeria, a sector that has significantly shaped the nation's economy since the discovery of oil in Oloibiri in 1956. Despite Nigeria's substantial oil and gas reserves and the implementation of the Petroleum Industry Act (PIA) in 2021, which aimed to overhaul the legal framework and attract investor interest, the sector still faces a significant financing gap. The study examines the challenges that have hampered the sector's growth, including inadequate infrastructure, frequent sabotage, inadequate funding and the reluctance of foreign banks to invest due to perceived risks. It also evaluates the available financing options, differentiating those applicable to local, international oil companies, and the national oil company. The research highlights the importance of selecting the best financing options for oil and gas business while exploring various financing strategies available to players in the oil and gas industry.

Abstract This article examines the relationship between crude oil trade, economic growth, and the real exchange rate in Iran from 1979 to 2023, utilizing the Autoregressive Distributed Lag (ARDL) approach. The findings indicate that crude oil exports have a negative and statistically significant influence on the real exchange rate. Conversely, crude oil imports have a positive and significant effect on the real exchange rate. Additionally, the budget deficit from the previous period has positively impacted the real exchange rate. Gross Domestic Product (GDP) has also demonstrated a significant positive effect on the real exchange rate. In contrast, the monetary base has shown a significant negative effect on the real exchange rate. Long-term analyses reveal that oil export variables negatively affect the real exchange rate, while crude oil imports contribute positively. Over the long term, GDP maintains a significant positive effect on the real exchange rate, whereas the budget deficit and monetary base variables do not significantly influence the real exchange rate. Short-term dynamics suggest that the real exchange rate from the previous period positively and significantly affects the current real exchange rate. Moreover, the budget deficit variable in the current period negatively and significantly impacts the real exchange rate. The monetary base also has a significant negative effect on the real exchange rate; Central Bank assets have been utilized as a proxy for the monetary base. Key Words: Oil exports, oil imports, real exchange rate, ARDL approach.

Abstract The choice of financial regime in oil-rich countries depends on proven reserves, exploration and production costs, geological characteristics, political risks, and oil market conditions. In this article, contractual components of three contracts IPC, BUYBACK, and PSC are introduced using Visual Basic programming language, and a model structure for a 42-season period scenar-io with oil prices is created. Also, modeling based on the parameters of the Shadegan oil field is another innovation of this work. The aim of this research is to investigate the effective indica-tors in the oil and gas industry contracts based on oil price scenarios. The results of this study show that many of the constraints of the reservoir owner country have been modified in the direction of protecting oil fields and effectively controlling contractor's fees in modified mutual agreement and production sharing contracts, and the financial system of the new oil contracts is more efficient in case of an oil price increase and in the final years of production compared to production sharing and buyback contracts. In this study, comparing indicators such as internal rate of return, payback period, profitability index, and the share of both parties in the contract based on real and simulated data showed that entering into new oil contracts in Iran, especially IPC in the Shadegan oil field, can protect the oil field, prevent uncontrolled oil extraction, and control contractor's revenues, leading to lower costs and higher revenues compared to buyback and production sharing contracts for the host country (Iran).

Abstract The current research was conducted with the aim of providing a conceptual framework for the development of relations with suppliers in Abadan Oil Refining Company. The research method is qualitative and based on the data theory of the foundation. To collect data, semi-structured interview was used and data analysis was done by Strauss and Corbin method and paradigm model. The statistical population was experts and managers with experience in Abadan Oil Refining Company, from which a sample of 21 people was selected after reaching theoretical saturation. Sampling has been done theoretically and using targeted (judgmental) techniques. The results of the analysis of the data obtained from the interviews, during the process of open, central and selective coding, led to the creation of models of the development model of the relationship with the suppliers of consumer products in the Abadan Oil Refining Company based on the data theory of the foundation, which ultimately provided a model for the development model. Communication with suppliers was identified. The findings of this research indicate that for the success of the development model of the relationship with the suppliers of consumer products, company managers can pay attention to the identified categories and subcategories and if they match the conditions of the company, from this category. use In addition, this research shows the need to pay attention to the development patterns of relationships with suppliers.

Abstract The purpose of this study is to design a strategic restructuring model for strategic restructuring in the oil industry with attention and emphasis on eco-industrial development. This current research is developmental in terms of its purpose; In terms of approach, it has been done qualitatively and based on metacomposition. Based on this, the statistical community of the research includes a collection of articles that have been published from 2020 to 2023 on the topic of strategic restructuring and organizational modernization, and the authors have searched among prominent domestic and foreign scientific databases to find 57 articles out of 336. They selected articles and after analyzing their content, categories and concepts were extracted and their prioritization was done using Shannon's entropy method. Based on the research findings, 40 concepts were identified in the form of 10 categories and were separated into three categories intra-organizational, extra-organizational, and environmental factors. The categories of Organizational transformation, the establishment of new management styles, organizational knowledge, customer relationship management, broker organization, integration of industry and environment, adaptability, and predictability, job training needs assessment, quick and smart thinking, and human resource evaluation had the highest coefficient of importance, respectively. Therefore, due to its entrepreneurial nature, strategic restructuring will affect the realization of environmental protection as much as possible and will increase the responsibility of the oil industry towards the environment.

Abstract The price of Crude Oil is Exposed to Various Factors That Cause Random, Sudden and Chaotic Price Fluctuations. Accurate Forecasting of Oil Prices Has a Central Impact on The Macro Economy. The aim of This Study is to Predict the Fluctuations of OPEC Crude Oil in The  long-term Using Chaos Theory and GMDH-GA Algorithm. First, the Daily Oil Price Time Series is Decomposed by Wavelet Transformation. Then, Chaos is Tested Using Embedding Dimension, Lyapunov Power and GA tests. Finally, Time Series Noises are Reduced by Reconstructing the Wavelet Phase Space. Three Nonlinear Models, GMDH-GA model, GMDH-GA Wavelet Model, and GMDH-GA Extended Model, Were Used to Forecast Time Series. Although the Results Showed that All three Models are Favorable in Terms of Root Mean Square Error (RMSE) and Correlation Coefficient, But the Developed GMDH-GA  Neural Network Model with low RMSE and High Correlation Coefficient is the Most Effective in Predicting the Daily Price of OPEC Crude Oil. has it.

Abstract The oil and gas industry, as one of the most complex industries with unique characteristics, plays a vital role in the world's energy supply. In order to be present in this field, gain and maintain a competitive advantage, the actors of this industry are condemned to create, develop or acquire innovative technologies. With the change in the approach of companies active in the oil and gas industry compared to the past, intellectual achievements have been considered as a valuable asset and their support has become inevitable. Companies active in the field of oil and gas are well aware of the fact that obtaining maximum profits requires managing and supporting intellectual achievements and defining an intellectual property strategy aligned with the company's business goals. Therefore, each company defines its intellectual property strategy according to its role in the energy supply chain and operates based on it. Investigating the cost and profit of intellectual assets are two important criteria in determining the appropriate strategy of an oil company.