Petroleum Business Review

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 Iran’s latest risk service contract, known as the Iran Petroleum Contract (IPC), has been introduced to the international upstream market with the aim of attracting foreign investment in the country’s oil and gas sector. Several terms and conditions distinguish the IPC from the previous Iranian upstream oil and gas contract, the buyback contract. The objective of this investigation is to examine the legal implications of signing contracts in Iran, as well as the contractual terms and conditions of a signed contract in the Cheshmeh Khosh field. This study offers valuable insights into the potential hazards of the IPCs from the perspective of the National Iranian Oil Company (NIOC) by providing realistic information about the IPC and utilizing qualitative methods such as library and documentary research. Moreover, it is designed to assist the NIOC in effectively responding to and monitoring these risks, thereby promoting investment in the development of Iran’s oil and gas initiatives and protecting the national interest of Iran.

Abstract One of the innovations that has been formed in the insurance industry in recent years is transfer the risk to the capital markets. Today, this possibility is provided by issuing insurance bonds and Catastrophe bonds, which are a most important type of insurance-linked securities (ILS), can redress inefficiency in the insurance industry.
Today, more and more Catastrophe (CAT) bonds are being issued worldwide, which is welcomed by investors and insurance companies. On the other hand, traditional insurance solutions to cover the risks of Iran's oil and gas industry is not efficient and sufficient and using CAT bonds to transfer risks of this industry to capital markets is a necessary and inevitable issue.
The aim of this research is to identify effective factors for issuing Catastrophe bonds in Iran's oil and gas industry. On this basis and after reviewing the literature through library studies, 33 factors were identified in the form of seven categories, based on the similarities. Then, based on Delphi method, experts were asked to express their opinions through an iterative questionnaire. After take the experts' opinions in every round, the statistics analysis was performed and the Delphi process was stopped in the third round. Based on the results, the number of 32 factors in six categories with the titles Legislation and Amendment of the Rules, Knowledge Management, Process Management, Transparency, Creation and Strengthening of Software Platforms and Cultivation were approved by experts and identified as effective factors for issuance of Cat bonds in Iran's oil and gas industry.

Abstract Delay is an event that increases the completion time of a part of the project, which is one of the main problems in the executive projects of the country and causes an increase in project costs as well as damages. Project delays pose significant risks to the project that are dangerous for the project to continue. These risks are of particular importance in oil and gas projects. The purpose of this study is to identify and rank the risks related with delays in oil and gas projects. The present study is applied in terms of orientation and quantitative in terms of methodology. The statistical population of the study is managers and experts of risk and delay in oil and gas projects in the country. Among these people,15 people were selected as the sample by judgmental sampling method. For data collection, two questionnaires of expertise and prioritization were used, both of which had validity and reliability. In the first step, the risks associated with project delays were extracted by reviewing project risk and delay articles. In the next step, these risks were screened using the Binominal test.11 risks had a significance coefficient higher than 5% and were excluded from the calculations. The remaining 8 risks were prioritized using the Codas distance technique. According to the data of the relative evaluation matrix and the scores of each risk, the risks of sanctions, inflation, and lawsuits and complaints had the highest priority, respectively. Finally, research proposals were developed based on significant risks.

Abstract Companies need to exactly manage their assets to balance performance, risk, and cost. The ability of equipment to provide a certain level of performance is influenced by its design, utilization, deterioration, and life. On the other hand, in order to obtain the desired level of performance and reduce risk, proper planning of maintenance activities during the period must be done. To manage this issue, organizations must develop a suitable method for their assets from the acquisition stage to the disposal to obtain the required processes and, ultimately, to earn the desired profit. In this study, petroleum pipelines have been considered as a case study, and life cycle cost (LCC), risk, and key performance indicators (KPI) have been identified as the criteria for decision making. KPI is itself composed of three sub criteria, including reliability, availability, and maintainability. They are weighted by using the opinions of eight expert and DANP method. The final weights of LCC, risk, and KPI (reliability, availability, and maintainability) are 0.269, 0.301, and 0.429 respectively. Considering different strategies in each phase of the asset life cycle, different scenarios are described for the asset life cycle as follows: 1) RCM-replacement, 2) RCM-overhaul, 3) CBM-replacement, 4) CBM-overhaul, 5) TPM-replacement, and 6) TPM-overhaul. Finally, based on the gained experts’ viewpoint from questionnaire and MOORA technique to rank the scenarios, the desired scenario, namely Buy-TPM-Replacement, is selected. Due to the use of experts’ opinions, these results will vary with the change of people, and due to the lack of relevant data, it is not possible to avoid this issue.

Abstract It seems that paying attention to social responsibility by companies can lead to a better stakeholder’s view toward the company, thereby increasing their loyalty and trust. Having the ability to obtain more financial resources in times of crisis, due to the greater loyalty of investors, will result in reducing the company risk. In contrast, being overconfident about the loyalty of individuals to the company can lead to keeping a short-term debt structure, thereby increasing the risk of obtaining financial resources. Recently, the negative impacts of petrochemical companies on the environment have made social and environmental groups focus more on this industry, and this focus has pushed companies into involving in more social activities. Considering the potential impact of CSR on the company’s risk, this study examines the relationship between corporate social responsibility and value at risk in petrochemical industry using a sample of 27 companies listed on the Tehran Stock Exchange during the 2010-2017 period. Eviews 10 is used for computing and analyzing the data, and the generalized auto regressive conditional heteroskedasticity (GARCH) model is employed to estimate value at risk. The results indicate a negative and statistically significant relationship between corporate social responsibilities and company value at risk.