Game Analysis of Oil Trade among Major Countries: Taking China, Russia, India and Saudi Arabia as Examples

A new pattern of oil trade has emerged under the influence of geopolitics and the COVID-19 pandemic. To explore China's oil security in these changed times, this study takes the new pattern of global oil trade as the background and adopts the oil trade models of Russia, India, Saudi Arabia, and China itself. Since Saudi Arabia's oil trade with China and India has been safe and stable for long, this study uses evolutionary game theory to make a quantitative analysis of the energy competition between China and India and the energy cooperation between China and Russia. The research results reveal the following: 1) The continued increase in India's Russian oil imports will pose a threat to China's oil security. When India's oil imports from Russia reach 16.5%, it will change the oil trade structure of the four countries and become a crucial threat to China and 2) Russia's willingness to export has a direct impact on the results. As Russia's willingness to export declines, it will affect the results and pose a threat to China's oil security. This study is of great significance as it provides meaningful insights to ensure China's oil security in the post pandemic era with key changes in the world's oil trade pattern. © 2023 Science Press. All rights reserved.

Competitiveness, Market Structure, and Energy Policies: A Case Study of the World's Largest Crude Palm Oil Exporter

Crude Palm Oil (CPO) is the mainstay of Indonesian agricultural products which is the largest CPO producing country in the world. The high market share of Indonesian CPO exports reflects the high competitiveness of Indonesian CPO in the global market. The purpose of this study is to determine the competitiveness of Indonesian CPO, the concentration of the Indonesian CPO industry, and analyze the factors that are suspected to affect the competitiveness of the CPO industry in Indonesia. The data used in this study are secondary data with a five-digit ISIC (10432) using time series data for 2001-2020 and the analytical techniques used in this study include Revealed Competitive Advantage (RCA), Gini Coefficient, and Error Correction Model (ECM). The results showed that Indonesian CPO has high competitiveness in the international market, the Indonesian CPO industry is not concentrated, in the short term the variables that affect competitiveness are CPO prices, subsidized solar prices policy, and industrial concentrations, while in the long term the influential variables are biodiesel policy, subsidized diesel oil policy and industrial concentration

Sequestration methodology in practice through evaluation of joint demographic distributions of 54,185 patients in the Medical Imaging and Data Resource Center (MIDRC) data commons

The Medical Imaging and Data Resource Center (MIDRC) is a multi-institutional effort to accelerate medical imaging machine intelligence research and create a publicly available data commons as well as a sequestered commons for performance evaluation of algorithms. This work sought to evaluate the currently implemented methodology for apportioning data to the public and sequestered data commons by investigating the resulting distributions of joint demographic characteristics between the public and sequestered commons. 54,185 patients whose de-identified imaging studies and metadata had been submitted to MIDRC were previously separated into public and sequestered commons using a multi-dimensional stratified sampling method, resulting in 41,556 patients (77%) in the public commons and 12,629 patients (23%) in the sequestered commons. To compare the balance obtained in the joint distributions of patient characteristics from use of the developed sequestration method, patients from each commons were separated into bins, representing a unique combination of the demographic variables of COVID-19 status, age, race, and sex assigned at birth. The joint distributions of patients were visualized, and the absolute and percent difference in each bin from an exact 77:23 split of the data were calculated. Results indicated 75.9% of bins obtained differences of less than 15 patients, with a median difference of 3.6 from the total data for both public and sequestered commons. Joint distributions of patient characteristics in both the public and sequestered commons closely matched each other as well as that of the total data, indicating the sequestration by stratified sampling method has operated as intended. © 2023 SPIE.

Hedging potentials of green investments against climate and oil market risks

PurposeThis study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.Design/methodology/approachThe study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan's (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West's model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.FindingsThe study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.Originality/valueThe study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.

The effect of increasing health disaster risk and public spending on economy conditions: a DSGE perspective

PurposeThe main motivation of the present study is to understand the severity of the effect of health shock on Iran's oil economy and analyze the role of government under these conditions.Design/methodology/approachDynamic stochastic general equilibrium (DSGE) models can show the precise interactions between market decision-makers in the context of general equilibrium. Since the duration of the virus outbreak and its effect on the economy is not known, it is more appropriate to use these models.FindingsThe results of the survey of hands-on policies scenarios compared to the state of hands-off policy indicate that the effect of government expending shocks on the economy under pandemic disease conditions has much less feedback on macroeconomic variables.Originality/valueAs a proposed policy, it is recommended that the government play a stabilizing role under pandemic disease conditions.Key messages There is no study regarding health shock and its economic effects in Iran using DSGE models. Also, in foreign studies, the health shock in an oil economy has not been modeled.The general idea in the present study is how the prevalence of a pandemic infectious disease affects the dynamics of macroeconomic variables.In three different scenarios, according to the persistence of health disaster risk and the deterioration rate of health capital due to this shock, the model is simulated.In modeling pandemic diseases, quarantine hours are considered as part of the total time of individuals.According to the research findings, it is recommended that the government, as a policy-maker, play a stabilizing role under pandemic crises conditions.

Evaluation of infection probability in a multiroom office space using computational fluid dynamics coupled with Wells-Riley model

The current COVID-19 pandemic has highlighted the importance of health safety assessment in various indoor scenarios. Computational fluid dynamics (CFD) combined with a modified Wells-Riley equation provides a powerful tool to analyse local infection probability in an indoor space. Compared to a single infection probability characterising the space in the traditional Wells-Riley model, the coupled approach provides a distribution of infection probability within the space. Furthermore, this approach avoids assuming a well-mixed state, usually related to Wells-Riley equation. This study compares displacement and mixing ventilation strategies with four different ventilation rates to assess the local quanta concentrations modelled using passive scalar transport approach. The simulation results are processed to also account for the effect of wearing masks and vaccinations. The result show that a well-designed displacement ventilation system can significantly reduce infection probability compared to mixing ventilation system at similar airflow rate. Additionally, the results emphasised the importance of wearing mask and getting vaccinated as a means of reducing infection probability. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Johan Sverdrup: the Final Lap of a True North Sea Giant

The second phase of Johan Sverdrup came on stream in December 2022. This paper focuses on the execution of Johan Sverdrup phase 2 and describes the assessments and investments for improved oil recovery (IOR) from one of the largest oil fields in Norway. The Johan Sverdrup field development has been called Equinor's ‘digital flagship', and this paper includes the proof of concept for the digital initiatives after more than three years of operation. Despite the Covid-19 pandemic Johan Sverdrup phase 2 has been able to deliver on schedule, under budget, and with an excellent safety record. The paper includes experiences from the concept development and engineering phase to the global contracting strategy, through the construction on multiple building sites in Norway and globally, and until the end of the completion phase offshore Norway. Johan Sverdrup is the third largest oil field on the Norwegian Continental Shelf (NCS), and with recoverable reserves estimated at 2.7 billion barrels of oil equivalents, has the resources to be a North Sea Giant. Start-up of the Johan Sverdrup phase 2 extends and accelerates oil and gas production from the NCS for another five decades. This paper aims to highlight what it took to make Johan Sverdrup a true North Sea Giant, fit for the 21st century: a safe and successful execution of a mega-project, with next-generation facilities adapted to a more digital way of working, with an ambition to profitably recover more than 70% of the resources, while limiting carbon emissions from production to a minimum. In many ways the Johan Sverdrup development has set a new standard for project execution in Equinor. The impact of different variables made during the execution of the project, such as the Covid-19 pandemic, market effects, procurement strategies, value improvement initiatives, execution performance and reservoir characteristics is addressed, as well as describing assessments and investments for improved oil recovery (IOR). Data acquisition, Permanent Reservoir Monitoring (PRM), fibre-optic monitoring of wells, innovative technologies, and digitalization, as well as new ways of working are included. Equinor ´s digital strategy was established in 2017, and Johan Sverdrup was highlighted as a digital flagship at that time and a frontrunner in applying digital solutions to improve safety and efficiency from the development to the operational phase. What has been implemented so far together with experiences will be shared. © 2023, Offshore Technology Conference.

Stock Price Forecasting of IBEX35 Companies in the Petroleum, Electricity, and Gas Industries

In recent years, time series forecasting has become an essential tool for stock market analysts to make informed decisions regarding stock prices. The present research makes use of various exponential smoothing forecasting methods. These include exponential smoothing with multiplicative errors and additive trend (MAN), exponential smoothing with multiplicative errors (MNN), and simple exponential smoothing with additive errors (ANN) for the forecasting of the stock prices of six different companies in the petroleum, electricity, and gas industries that are listed in the IBEX35 index. The database employed for this research contained the IBEX35 index values and stock closing prices from 3 January 2000 to 30 December 2022. The models trained with this data were employed in order to forecast the index value and the closing prices of the stocks under study from 2 January 2023 to 24 March 2023. The results obtained confirmed that although none of the proposed models outperformed the rest for all the companies, it is possible to calculate forecasting models able to predict a 95% confidence interval about real stock closing values and where the index will be in the following three months.

Disentangling Short-Run COVID-19 Price Impact Pathways in the US Corn Market

Despite this focus on pandemic-related supply chain disruptions, fewer empirical studies have sought to isolate short-term price impacts in food and nonfood agricultural commodity markets.1 Understanding the drivers of short-term commodity price impacts is critical to understanding future susceptibility to major market shocks and to informing policies related to shock mitigation. Declines in ethanol production reached an estimated 2 billion gallons lost from March to November 2020, leading to a corresponding decline of 700 million bushels of corn usage and a loss of billions of dollars of ethanol producer surplus (Renewable Fuels Association, 2020b;Schmitz, Moss, and Schmitz, 2020). Increases in corn-based ethanol production that started in 2005 have linked agricultural commodity prices and energy markets as US ethanol production increased rapidly from 3.9 billion gallons in 2005 to 13.3 billion by 2010 and 15.8 billion by 2019 (Chakravorty, Hubert, and Nøstbakken, 2009;Wright, 2011;Roberts and Schlenker, 2013;Asgari, Saghaian, and Reed, 2020;US Department of Agriculture, 2021). Given that over 90% of US ethanol is used in mixtures of E10 gasoline and the US market reached a 10% "blend wall" in 2016, any reduction in gasoline use will cause proportional decreases in ethanol use (US Energy Information Administrationa, 2020;US Department of Agriculture, 2021).

Key Success Factors of 3D OBN Survey in a Congested Oil Field in the Caspian Sea

In this paper, we present and demonstrate that the implementation of an efficient Project Management Strategy has effectively contributed in a safe and successful completion of a very complex 3D OBN Seismic Survey in congested Oil fields. Thus, delivering high quality data on schedule and within the predetermined budget at the full satisfaction of all involved parties and stakeholders. Strong commitment to HSSE Standards and working as an integrated One-Team with full collaboration and continuous communication between all the Team members are among the main Success Factors of the 3D seismic survey which was carried out during the critical period of COVID-19. Moreover, the deployment of experienced personnel, advanced and reliable Technologies with adequate equipment have also extended the efficiency of this OBN 3D seismic survey. Preliminary results of 3D seismic data processing, interpretation and reservoir characterization are also briefly presented and discussed as a clear enhancement of data quality was already observed compared to the legacy 3D OBC data set. A fast track small 3D cube was successfully processed as an utmost and urgent priority for appraisal well selection, design and drilling. Copyright © 2023, Society of Petroleum Engineers.

The Pandemic Waves' Impact on the Crude Oil Price and the Rise of Consumer Price Index: Case Study for Six European Countries

This study examines the response of the Consumer Price Index (CPI) in local currency to the COVID-19 pandemic using monthly data (March 2020–February 2022), comparatively for six European countries. We have introduced a model of multivariate adaptive regression that considers the quasi-periodic effects of pandemic waves in combination with the global effect of the economic shock to model the variation in the price of crude oil at international levels and to compare the induced effect of the pandemic restriction as well and the oil price variation on each country's CPI. The model was tested for the case of six emergent countries and developed European countries. The findings show that: (i) pandemic restrictions are driving a sharp rise in the CPI, and consequently inflation, in most European countries except Greece and Spain, and (ii) the emergent economies are more affected by the oil price and pandemic restriction than the developed ones.

Consequences of the Russia-Ukraine war: evidence from DAX, ATX, and FTSEMIB

PurposeThe Russian invasion of Ukraine generated unprecedented panic in the European financial system. As expected, the European Union (EU) felt most of the negative effects of the war due to geographical proximity to Ukraine and energy dependence on Russia. This study aims to investigate the influence of Brent crude oil (BCO), Dutch Title Transfer Facility Natural Gas, and CBOE Volatility Index (VIX) on Deutscher Aktien Index (DAX), Austrian Traded Index (ATX) and Milano Indice di Borsa (FTSEMIB). The German, Austrian and Italian equity indexes were chosen due to the heavy dependence of these countries on Russian gas and oil.Design/methodology/approachThe data cover the period from November 24, 2021, to June 24, 2022, including five months of the Russia–Ukraine war. To generate the intended results, vector autoregressive, structural vector autoregressive, vector error correction model, Johansen test and Granger causality test were used.FindingsThe results highlight that natural gas and the VIX carried negative effects on DAX, ATX and FTSEMIB. The BCO was expected to have influenced three selected equity indexes, while the results suggest that it was priced only in ATX.Originality/valueThis research provides modest evidence for the policymakers on the systemic risk that Russian gas has for the EU equity markets. From a managerial perspective, changes in oil and gas prices are a permanently integral part of portfolio risk analysis.

Update on Risk Criteria for Crude Oil Tanker Fleet

In recent years, the maritime trade of crude oil has suffered notable perturbations caused by the unbalanced relationship between supply and demand. The COVID-19 pandemic caused a drop in oil consumption in 2019, followed by a reduction in production in 2020. The seaborne transport of oil accounts for approximately 50–60% of all crude oil in world production. The crude oil market is a crucial regulator of the global economy and instabilities in this market have noticeable effects on collective risks. The immediate risks that the society see are the changes in the cost of living, which are followed by political uncertainties. Less visible are the risks that these uncertainties have on shipping companies and the level of management stability they have to maintain in order to keep seagoing safe. This paper presents an update on the overall state of risk management for the crude oil tanker fleet, evidenced by EMSA and other international marine organisations. The previous paper, entitled Safety Assessment of Crude Oil Tankers, which applied the methodology of the Formal Safety Assessment (FSA), was published in 2018 and covered the historical data related to the fleet size, accident reports, amount of oil spilled on sea and the economic value of the crude oil transport business. The particular focus of this paper is on the evolution of the risk acceptance criteria over the years and the difference in the predictions from 2018 to the present day. The effects of the pandemic on crude oil shipping are discussed through the changes in the risks. Three of them are analysed: PLL (potential loss of lives), PLC (potential loss of containment) and PLP (potential loss of property). The representation of the risk applies the F-N curves among the risk acceptance criteria lines observed for different tanker sizes. Among the three risks, the paper exposes the vulnerability of the loss of containment risk, where the strong economic impact of the oil trade outweighs the environmental concerns. In relation to the PLC, the paper proposes the approach of relating the oil spill acceptability with the spill quantity and ship revenue instead of to the cost of cleaning or the cost of environment recovery.

Weaponizing Wheat: Russia's Next Weapon in Pandemic and Climate Eras

[...]the article closes with policy recommendations to prevent the weaponization of wheat. [...]Russia has recently violated Swedish airspace,8 simulated attacks on Norway,9 jammed GPS systems during NATO exercises,10 and tested new missile systems.11 Russia's quest for melting Arctic fossil fuels is part of an overall plan to leverage the advantages they gain from climate change, a plan that is marked by increased aggression and strategic manipulation of climate-vulnerable regions. [...]as importing countries transition away from fossil fuels, demand for Russian oil and gas will decrease, reducing the overall [End Page 63] revenue for the Russian economy. Countries that fell under the Soviet sphere of influence during the Cold War are less diversified in their energy mixes than those in Western Europe and are highly dependent on Russia.19 For example, in 2015, the stateowned oil and gas company Gazprom increased prices for the Baltic states, Bulgaria, and Poland.20 EU antitrust regulators found that Gazprom was manipulating gas prices in Bulgaria and Poland to force them to participate in additional pipeline projects.21 Such manipulative tactics could indicate future avenues for hybrid warfare, through which Russia combines military strength with economic, resource, technological, or political aggression.22 Russia's use of energy as a form of hybrid warfare can also be seen clearly in Ukraine.

Efficient numerical simulations based on an explicit group approach for the time fractional advection–diffusion reaction equation

The time-fractional advection–diffusion reaction equation (TFADRE) is a fundamental mathematical model because of its key role in describing various processes such as oil reservoir simulations, COVID-19 transmission, mass and energy transport, and global weather production. One of the prominent issues with time fractional differential equations is the design of efficient and stable computational schemes for fast and accurate numerical simulations. We construct in this paper, a simple and yet efficient modified fractional explicit group method (MFEGM) for solving the two-dimensional TFADRE with suitable initial and boundary conditions. The proposed method is established using a difference scheme based on L1 discretization in temporal direction and central difference approximations with double spacing in spatial direction. For comparison purposes, the Crank–Nicolson finite difference method (CNFDM) is proposed. The stability and convergence of the presented methods are theoretically proved and numerically affirmed. We illustrate the computational efficiency of the MFEGM by comparing it to the CNFDM for four numerical examples including fractional diffusion and fractional advection–diffusion models. The numerical results show that the MFEGM is capable of reducing iteration count and CPU timing effectively compared to the CNFDM, making it well-suited to time fractional diffusion equations. © 2023, The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional.

MMSports'22: 5th International ACM Workshop on Multimedia Content Analysis in Sports

The fifth ACM International Workshop on Multimedia Content Analysis in Sports (ACM MMSports'22) is part of the ACM International Conference on Multimedia 2022 (ACM Multimedia 2022). After two years of pure virtual MMSports workshops due to COVID-19, MMSports'22 is held on-site again. The goal of this workshop is to bring together researchers and practitioners from academia and industry to address challenges and report progress in mining, analyzing, understanding, and visualizing multimedia/multimodal data in sports, sports broadcasts, sports games and sports medicine. The combination of sports and modern technology offers a novel and intriguing field of research with promising approaches for visual broadcast augmentation and understanding, for statistical analysis and evaluation, and for sensor fusion during workouts as well as competitions. There is a lack of research communities focusing on the fusion of multiple modalities. We are helping to close this research gap with this workshop series on multimedia content analysis in sports. Related Workshop Proceedings are available in the ACM DL at: https://dl.acm.org/doi/proceedings/10.1145/3552437. © 2022 Owner/Author.

BTX production by breaking down lignin: Current status and future prospects

Nowadays, lignin is a byproduct of the agricultural and cellulose pulp mill. Lignin is a sustainable, renewable raw material alternative to petroleum‐based chemicals, mainly for the benzene–toluene–xylene (BTX) production of commodities and the sequential secondary, tertiary and manufactured products in the petrochemical industry. It can be mass produced and is used for renewable energy biorefinery or high‐value‐added products. This review aims to outline the important lignin depolymerization technologies and the feasibility of imposing these transforming technologies on a large scale. Finally, this review examines the market prospects for BTX, revealing its R&D progress. However, the harmful effects of BTX and unfavorable conditions resulting from the COVID‐19 pandemic comprise roadblocks to its growth. However, the increasing use of biobased BTX is expected to open new market opportunities. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd. [ FROM AUTHOR] Copyright of Biofuels, Bioproducts & Biorefining is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Gold, crude oil, bitcoin and Indian stock market: recent confirmation from nonlinear ARDL analysis

PurposeThis paper investigates the causality among gold prices, crude oil prices, bitcoin and stock prices by using daily data from January 2014 to December 2021. The study also examines the data during the COVID-19 outbreak from January 2020 to December 2021.Design/methodology/approachTo estimate the long- and short-run causality, this study considers the nonlinear autoregressive distributed lag (NARDL) cointegration test.FindingsThe analysis found the existence of an asymmetric long-run cointegration among selected assets. Findings indicate that positive changes in bitcoin do not affect stock market in the long term. Changes in crude oil prices have a significant impact on stock prices. Moreover, it is observed that variations in the stock prices trigger a negative impact on gold prices. During the COVID-19 period, the study notices the presence of an asymmetric long-term cointegration between selected assets except bitcoin. Besides, findings revealed that negative price adjustments in gold lead to significant positive shocks in stock market.Originality/valueThese results provide critical information for policy performers and researchers to develop new strategies. Policy regulators can also consider the potential effects of the COVID-19 outbreak while developing strategies for investment decisions.

Extended Well Testing Campaign in Extreme H2S Environment in SIMOP

In a modern era of unprecedented events, such as the COVID-19 pandemic, energy matters now more than ever. What was previously impossible is now a challenge that should be met with measured risk and a mitigation plan. In early 2020, a service company pursued a solution to provide a compact surface well test (SWT) package for an extended well test (EWT) on an offshore production platform in the Zafaraana field with extremely high concentrations of H2S. The solution involved proper treatment and safe delivery of well effluent within acceptable H2S limits to a floating production storage and offloading (FPSO) facility. The EWT was to be installed for a long period to allow production from the reservoir, treatment of the effluent using H2S scavenger, and delivery to the FPSO facility by means of electric transfer pumps. This was the only way to produce because the FPSO facility could not accommodate the high H2S concentrations from the reservoir. A further challenge was that it was a simultaneous operation (SIMOPs) wherein the rig was engaged in drilling and completion activities of other wells on the same offshore platform;operational conflicts were identified during the HAZOP/HAZID meeting to help mitigate potential issues. Copyright © 2023, Society of Petroleum Engineers.