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This review provides an overview of some of the issues surrounding the existing implication of renewable energy technologies (RETs) and background rural knowledge to unfold the modern energy harvesting system. Owing the alarming call by nature about environmental pollution and continuous hike in petroleum prices, a better fuel option is still a mission worldwide. [ABSTRACT FROM AUTHOR]

The volatility of oil prices correlates with major international crises, namely the Asian Economic Crisis of 1997, the 2001 Recession, the 2007-2008 Financial Crisis, and most recently, the Covid-19 pandemic (2020-2021). In response to these related incidents, the current study aims to determine the impacted sectors in Malaysia during the Covid-19 pandemic and the Recession of 2001. In this study, the authors focus on data from January 1998 till November 2001 for Recession 2001 and January 2018 till September 2021 for Covid-19. Data are daily sector indices of the Malaysian market comprised of data from the Construction, Consumer, Energy, Finance, Real Estate, Telecommunication, and Utilities sectors. This study employed various statistical analyses, such as autoregressive integrated moving average (ARIMA), Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family model, persistency, half-life, and capital asset pricing model (CAPM) effect. These were used to analyze these corresponding events and their impact on the sectors. As a result, the study will show how global oil price volatility affects different sectors in Malaysia. This research will also assist in determining which model is best used to describe these various events and will subsequently help future-proof the investors from any impending crisis. [ABSTRACT FROM AUTHOR]

Crude oil is a vital natural resource needed worldwide and the most demanded commodity. Fluctuating oil prices can affect a country's economic conditions e.g., economic growth, inflation rate, money supply, exchange rate and interest rates. Consequently, statistical forecasting methods are needed for a more accurate prediction in period t to support decision-making. This study aims to predict crude oil prices during the Covid-19 pandemic and compare the performance of crude oil price forecasting using the Fuzzy Time Series (FTS) Markov Chain method and Autoregressive Integrated Moving Average (ARIMA) method. The data used is daily crude oil prices with West Texas Intermediate (WTI) Standard in US$/barrel from March 3, 2020, to March 31, 2022. Forecasting with the FTS Markov Chain method resulted in a mean absolute percentage error (MAPE) of 2.76%, and root mean square error (RMSE) of 580.3. The best model for ARIMA is ARIMA (0,1,1) which produces MAPE of 3.85% and RMSE 856.7. Due to the MAPE & RMSE values in the FTS Markov Chain method being smaller than the ARIMA method. Hence, forecasting using the FTS Markov Chain has better performance than the ARIMA method in the forecasting of crude oil prices during the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

Rubber industry is one of the backbones and the key player in Malaysia's economy alongside with oil palms, automotive and other industries. In addition, natural rubber has recently become one of Malaysia's most important economic contributors. Natural rubber price fluctuates due to the volatile nature of natural rubber price. Despite this, the price of Standard Malaysia Rubber 20 (SMR20) changes frequently over time. These are some of the reasons why the determination on the factors that influences the price of natural rubber is crucial. This research aims to identify the factors that affecting the price of natural rubber in Malaysia based on rubber tappers perspective. The data for this research was collected from 200 rubber tappers from Padang Terap area via questionnaire. Convenience and snowball non-probability sampling methods were adopted for data collection. Reliability test and exploratory factor analysis (EFA) was used to measure the items on the questionnaire. There are five factors that have been identified to have influenced on the price of natural rubber. The factors are season, demand and supply, crude oil price, career and productivity. [ABSTRACT FROM AUTHOR]

While renewable energy is growing in terms of its production and usage, the oil & gas industry is still the major contributor to world energy production. The rapid decline in oil & gas demand is not foreseeable in the near future unless there is a drastic shift in current policies. Hence, considering its impact on the world, it becomes crucial that the oil & gas sector functions efficiently. However, the execution of oil & gas projects, particularly Large Oil and Gas Projects (LOGPs) have a sluggish track record of execution in terms of time and cost. The execution of LOGPs within the allocated time frame and budget is of paramount importance to keep the investors' faith for receiving budget allocations in future investments and remain a prime target to attract investment expected as per world energy outlook, 2020. Project management tools such as identification of Success Factors/Critical Success Factors (CSFs) help the project management team in the successful implementation of a project. This study aims to find out and enumerate success factors for different phases of project life cycle specific to oil & gas projects. [ABSTRACT FROM AUTHOR]

Crises, by their environment, are inclined to have an undesirable influence on markets and financial activities. The emergence of COVID-19 has widely affected the global demand for crude oil. Prices continued to fall in January and February 2020, as China demand - the world main crude oil trader and Iraq main customer - ended up shutting down. This pressure increased to turn into the biggest price drop in March 2020. At that time, Iraq goes through the two crises of the Corona virus and the collapse of oil prices. Iraq's commitment to OPEC announcement to reduce its oil production was an issue, and Iraq did not only obtain a smaller amount of the crude oil it produces, as the second largest producer in OPEC, but also decided not to pump the same amount of it. This decision has a crucial impact on oil prices in Iraq using daily information of the crises. The results indicate that both COVID-19 and oil prices are inversely proportional. In addition, this crise has exhausted the Iraqi economy. Iraq was not prepared for such circumstances, logistically or morally. When reviewing oil prices before the emergence of COVID-19, it is impossible to reject the oil market recovery hypothesis. In other words, the results agree with the evidence of market performance before the crisis, and the opposite is completely true, as oil prices collapsed after the emergence of the virus at the end of 2019. The question here is whether or not we will be ready or prepared for such circumstances. This paper will summarize what Iraq has gone through concerning the oil markets, aspiring to benefit from this crisis. Although oil prices are recovering somewhat, this does not mean that the Covid-19 shock will be transient and may have long-term belongings. [ABSTRACT FROM AUTHOR]

In this paper super capacitor technology is under study for electric car. This paper suggests some remedies to solve problems of fuel based transportation such as pollution, Green house gas effect, increase in oil prices and oil dependency etc. It also provides another option in Electric car by replacing batteries of Electric car by super capacitor bank to achieve fast charging, reduce size and weight of battery module. Possible to achieve goal of vehicle to grid by using this model as it can supply small amount of power back to home when it is parked at home [ABSTRACT FROM AUTHOR]

The Indonesian Crude Oil Price (ICP) is determined by the Government of Indonesia. This price is used to calculate the profit sharing of the production sharing contracts in Indonesia. The price policy and methodology refer to the Minister of Energy and Mineral Resources Regulation Number 23 of 2012. ICP is formed by benchmarking and indexation of international crude oil prices and derivative products. In this process, the government considers the production continuity, quality of crude and infrastructure. Gross Product Worth (GPW) is weighted average value of the refined product components minus a refinery fuel and the loss of a barrel of the crude. It is calculated by multiplying the price of each product by its percentage share in the yield of the total barrel of crude. Through a comparison between ICP and GPW of 11 types of crude oil in Indonesia, for the period January 2019 to December 2020, it was found that some crude oil located in eastern Indonesia has a characteristic that the ICP is under the GPW consistently, Its values vary from minus 3.72 USD/Bbl to minus 11.96 USD/Bbl. While the crude oil located in western Indonesia has a characteristic that the different value of ICP to GPW vary from minus 3.76 USD/Bbl to plus 9.80 USD/Bbl. The Factors that affect the variation in values between ICP and GPW include: location, volume and impurities. [ABSTRACT FROM AUTHOR]

Indonesia is projected to still have abundant potential oil and gas reserves in deep-offshore areas, which require advanced technology and large capital investments to start production. The high cost of production, coupled with the continued volatility of crude prices, and the deferment of cost recovery as an impact of declining revenues from field development projects are inevitable problems on oil and gas management. This study will evaluate the impact of current fiscal on deep-offshore project development and estimates the limit of gas price, reserves and expense, with the aim of obtaining an optimal scheme that will encourage new deep-offshore field development. The approach used in this study is based on deterministic discounted cash flow modelling, and takes into account the uncertainty condition using a Monte Carlo simulation process. The study found that a field and development cost of 20$/bbl suggests new deep-offshore developments will not be economically attractive without cost efficiency improvements and fiscal incentives. It also suggests that sharing facilities with other nearest working area is expected be able to reduce the development and operating costs. [ABSTRACT FROM AUTHOR]

Newer efficient energy fermentation technologies are gaining a lot of attention as a result of increase in petroleum prices. Fermentation chemicals are much required in modern market. The recovery of carboxylic acid is a difficult task. The majority of fermentation technology uses carboxylic acids. As a result, present recovery technologies required to be modified. As most chemical recovery processes are driven by equilibrium, increases in reaction rates will occur due to removal of product as soon as it is produced. This leads to increase in reaction rates, increase in feed conversions, and reduction in reaction exactness. These constraints can overcome by using reactive extraction. Reactive extraction found to be a capable novel option for recovering the fermentation chemicals. This review paper discusses the reactive extraction of carboxylic acids. Under the category of reactive separation reactive extraction with high selectivity and capacity in recovery of chemical species from dilute solution is one of the methods. [ABSTRACT FROM AUTHOR]

Natural fibers, like as bamboo, are easily destroyed by microbes (Biodegradability) and may become an alternative fiber in the future because to their very low supply. Bamboo grows all year and is not impacted by the seasons. Bamboo fiber is a solution to environmental issues, and synthetic fibers business prospects are likely to dwindle as oil prices rise. Bamboo fibre has hydrophilic qualities in its composition, allowing it to absorb more water. The mechanical and physical properties of the resultant composites suffer as a result. This study's goal is to understand the types and process of each bamboo fibre treatment method,to be able to choose the best treatment method that brings the best tensile strength and to explain why the chosen treatment method yields high tensile strength. The bamboo fibre is extracted using a variety of methods, including mechanical extraction, chemical extraction, and combination (Chemical + Mechanical) extraction. In comparison to other fibre treatments, alkaline treated bamboo fibre with compressed moulding technique(CMT) as the mechanical separation produces a greater tensile strength value(1000 MPa). [ABSTRACT FROM AUTHOR]

This study investigated the effect of storage time and temperature on the quality of Sacha Inchi (Plukenetia volubilis L.) oil during processing. Storage time and temperature were considered two important factors that affected the oil quality. The oil quality was noticeably decreased by extended storage time and heating treatment via the observation of peroxide value, acid value, iodine value, and saponification value. Physicochemical properties of oil were determined including boiling point (207.33±2.520C), crystallization temperature (-200C), and decomposition temperature (340-350 0C). The quality of oil was declined after 7 months of storage; the peroxide value of fresh Sacha Inchi oil increased from 0.63±0.03 Meq/kg to 1.07±0.06 Meq/kg. Heating process at the temperature of 205 oC for 90 min remarkably affected the peroxide and acid value of oil but these values were still within the allowable limit at the studied. This suggested that Sacha Inchi oil could possibly be processed at higher temperature and extended heating time. Besides, the alterations of peroxide value and acid value were still within the allowable limit when Sacha Inchi was subjected to the 3rd repeated deep-frying cycle of potato slices (5 min for each cycle). This suggested the feasibility of Sacha Inchi to be a suitable alternative to normal cooking oil. [ABSTRACT FROM AUTHOR]

Crude oil is one of the most traded commodities in the world and its prices have a significant impact on the global economy. Although many forecasting models have been developed for predicting oil prices, it remains one of the most challenging forecasting tasks due to the high volatility of oil prices. This study proposes a combination of Maximal Overlap Discrete Wavelet Transform (MODWT) with Gaussian Process Regression (GPR) for monthly crude oil price forecasting. For this purpose, monthly West Texas Intermediate (WTI) and Brent crude oil prices are used to evaluate the performance of proposed model. Feature selection in time series forecasting is important to improve learning accuracy and reduce computational time by eliminating redundant and irrelevant input. In order to identify significant input time lag for the models, Neighborhood Component Feature Selection (NCFS) is first used to rank the input lag based on their importance. MODWT is used to decompose the time series data to details (high frequency) and approximation (low frequency) components. The proposed model, MODWT-GPR model is developed by using the decomposed time series components obtained from MODWT. Two types of MODWT-GPR models with three different wavelet families (daubechies, symlets and coiflets) are studied and compared to get the best forecasting performance. Standard MODWT-GPR model only uses the decomposed wavelet components, while Hybrid MODWT-GPR includes the original input lag series in additional to the decomposed wavelet component. The proposed models are compared with other benchmark models including Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and the conventional GPR model. The forecasting performance of the tested method are measured by using root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The result shows that the integration of MODWT improves the performance of the conventional GPR model and Hybrid MODWT-GPR outperforms all other forecasting models used in this study. Future study suggests the application of different kernels to study their impact on crude oil price forecasting. [ABSTRACT FROM AUTHOR]

Forecast future crude oil stock price trends are essential for the purpose to assist the government, economists, and investors. However, the non-trading days will affect the accuracy of forecasting. Thus, multiple imputations were applied in this study toward the non-trading days in the stock price. To verify the accuracy of multiple imputations, this study attempt to compare the forecast accuracy of both artificial neural network (ANN) and simple exponential smoothing (SES) in forecasting the future crude oil stock price with imputation and without imputation process. Based on the results, ANN with imputation consist of fifteen lags as input neurons and ANN without imputation consist of five lags input neurons. In overall, ANN outperformed SES and all forecast models with imputation outperformed the models that without imputation. Therefore, the best approach is ANN with imputation after Min-Max normalization. Thus, it can be concluded that imputation can improve the forecast accuracy and the non-trading days should not be neglected. [ABSTRACT FROM AUTHOR]

Recently, the fluctuations of oil prices and unstable product demands resulting in disruption at procurement, production, and inventory stages have led to increased awareness among managers and decision-makers to include uncertainty in the refinery planning. Among the most prominent approach in handling optimization under uncertainty is stochastic programming. However, it is critical and challenging to construct a representation of random variables that describe the uncertainty behaviour. Thus, this study proposes the model and forecasting of oil prices and petroleum products demand under uncertainty to incorporate Hurst parameter values and structural break approach as input parameters to the stochastic programming. In modelling oil price, the information on whether the structural break exists is crucial due to the long memory property that might be camouflaged by the existence of the structural break. The Hurst parameter, connected to the fractional differencing parameter, was used to characterize the long memory process. The time series will be modelled and forecasted based on the Hurst value, and stochastic differential equations will be explored to analyze the uncertainty of oil prices. Meanwhile, the Holt-Winter method is adopted to describe the uncertainties of petroleum product demand. The result indicates that Geometric Brownian Motion (GBM) and mean-reverting Ornstein-Uhlenbeck (OU) are accurate forecast models to forecast future oil prices, and Holt-Winter seasonal method is an accurate model to forecast future petroleum products demand due to mean absolute percentage error (MAPE) value is less than 10. Thus, we conclude that the coherent probabilistic scenario can then be constructed with this stochastic model framework to formulate a deterministic equivalent of stochastic programming. [ABSTRACT FROM AUTHOR]

Empirical analysis is conducted to examine the nexus of energy consumption, energy intensity and carbon dioxide (CO2) emissions using the global panel dataset of 1990 to 2014. The main objectives are to compare the nexus between oil-importing versus oil-exporting countries, to examine the nexus between short versus long-run counterparts, and to reveal the asymmetric effects of oil price changes in the nexus examined. The main contribution of this study is to analyze the asymmetric effects of oil price changes using a nonlinear autoregressive distributed lags (NARDL) model. A few variables are included, which are energy consumption, energy intensity, total and sectoral CO2 emissions, and world crude oil price, in which the oil price acts as a control variable. The results show that CO2 emission affects energy consumption positively for both groups of countries, with a higher impact in oil-importing countries. Besides, a rise in CO2 emissions shrinks the energy intensity of oil-exporting countries but raises the energy intensity of oil-importing countries. The oil price has asymmetric effects on energy consumption, with larger effect from oil price increases. Oil price has a limited influence on energy intensity, while the higher oil price causes higher emissions. The oil-dependency factor matters, with oil-importing countries experiencing larger impacts from oil price changes. It is suggested that policy decision/ planning should co-exist with the environmental concern, to sustain the environmental quality and economic growth. [ABSTRACT FROM AUTHOR]

Purpose: This study examines how investors’ sentiment impacted the profit spreads of three major energy companies: BP PLC, Chevron, and Exxon Mobil, from 2014 to 2024. Given the recent spike in volatility in the oil industry caused by COVID-19 and the Russia-Ukraine crisis, it is necessary to examine how investor emotions impact profit spreads in addition to the more traditional causes. Methodology: We investigate the relationship between a weekly investor sentiment index and daily profit spreads using a MIDAS regression approach. Additionally, the results are compared using standard linear regressions. Weekly data for January 3, 2014, to May 6, 2024, and daily data for January 9, 2014, to May 9, 2024, are used in the study. Results: We expect the MIDAS regressions to show a nuanced link between profit spreads and investor mood. A nuanced influence would be suggested by the mixed positive and negative signs across different lags, even if some lagged sentiment variables would have statistically significant coefficients. This could be different from what regular linear regressions find. Chevron The analysis of Chevron's daily stock returns using MIDAS regressions suggests that investor sentiment might not have a clear-cut impact. While a strong negative mean reversion effect exists (where yesterday's return influences todays in the opposite direction), the sentiment index's coefficients in the MIDAS regressions were not statistically significant. This indicates other factors likely play a larger role in influencing Chevron's daily returns. This could be because the oil and gas industry focus on long-term projects and may prioritize stable cash flow, making daily stock prices less responsive to short-term investor sentiment. However, limitations exist in this analysis, and a larger dataset or further analysis might be needed for a more definitive conclusion. Exxon Mobil Examining MIDAS regressions for Exxon Mobil revealed an unclear link between investor sentiment and daily stock returns. Unlike a standard regression, some lags of the sentiment index showed statistically significant relationships in MIDAS, but the positive and negative signs suggest a complex influence. This contrasts somewhat with the inconclusive results for Chevron, but could be due to the oil and gas industry's focus on long-term factors and Exxon Mobil's potential prioritization of stable cash flow, limiting the daily price impact of investor sentiment. While limitations exist, these results suggest investor sentiment might not significantly affect Exxon Mobil's daily stock price, potentially influencing its profit spread in a way that differs from other companies. BP PLC Analyzing MIDAS regressions for Exxon Mobil (DEXXON) and BP (DBP) revealed an unclear influence of investor sentiment on their daily stock returns. While there were some statistically significant coefficients for lagged sentiment terms in the MIDAS regressions, the mixed positive and negative signs across different lags suggest a complex relationship, not a clear positive or negative impact. This is similar to the findings for Chevron and strengthens the notion that investor sentiment might not be a major driver for daily stock prices in the oil and gas industry. This could be due to the industry's focus on long-term factors like global oil prices and the potential prioritization of stable cash flow by these companies, limiting the daily price impact of short-term sentiment swings. It's important to remember that limitations exist, and further analysis or a larger dataset might be necessary for a more definitive answer. However, these results suggest investor sentiment might not significantly affect the daily stock price of these oil and gas companies, potentially influencing their profit spreads in a way that differs from companies in other sectors. Research limitations: This study acknowledges limitations inherent to the MIDAS framework. The model might not capture all factors influencing daily profit spreads. Additionally, the chosen period might not fully capture long-term trends. Originality: This study adds to the body of knowledge by looking into the impact of investors‘sentiment on profit spreads in the energy industry, which has recently experienced increasing volatility as a result of global events. It uses the MIDAS approach to model the dynamic link between high-frequency investor sentiment and low-frequency profit spreads. It also compares the findings of MIDAS regressions to typical linear regressions to gain a more complete insight. [ABSTRACT FROM AUTHOR]

The article examines the fractal similarity of the structure and functioning of the Cosmos and the Earth, starting with the influence of stellar migrants in the form of plasmoids on northern Hyperborea, the spiral migration of the population across the expanses of Eurasia and the return of passionaries to the North Pole. Then, according to K.E. Tsiolkovsky, "humanity, having turned into radiant energy, will set off to explore new cosmic spaces." Influence of the Cosmos. The authors consider examples of the impact of solar activity on socio-natural energy processes, including in the form of periodic natural anomalies, cyclical fluctuations and crises in the economy, the dynamics of fluctuations in oil prices in the world energy market, as well as periodicity, economic and military events in the economy of Russia and Eurasia. The authors consider the reverse influence of the Earth on the cosmic noosphere in the form of energy-informational expansion, which determines not only the physical exploration of the near space, but also the concentration of new ideas and virtual representations in the near-earth space. This expansion, according to the authors, opens up opportunities for the further development of cosmoplanetary mankind. The article cites as an example 10 priorities and opportunities for such development. [ABSTRACT FROM AUTHOR]

The objective of this article is to forecast India's crude oil output patterns in the future. Specifically, this article examines whether data on crude oil output in India may be modified to ARIMA models for the purpose of estimate and forecasting. This article makes use of monthly data on Indian crude oil output. The Box Jenkins autoregressive integrated moving average (ARIMA) forecasting method was used to anticipate future patterns in the Indian crude oil market. The ARIMA model clearly indicates that the average monthly percentage rise in crude oil output will be.01 percent between December 2019 and November 2020, corresponding to a 0.36 percent increase in crude oil prices over the same time. The results of the study would be helpful for the investors of the commodity market to make their investment strategies keeping in mind the predicted future fluctuations. Further, it will also assist the Indian government to make necessary policies to absorb the volatility and to control prices of crude oil. [ABSTRACT FROM AUTHOR]

This paper investigates the profitability of technical analysis in a portfolio of integrated oil and gas companies. Using data of 21 individual companies for the period 01/07/2011 to 30/06/2021, we examine the Percent Bollinger (%b) technical trading rule against the benchmark buy-and-hold (B&H) policy. Our results show that the %b generates positive returns, lower drawdowns and smaller ulcer index as compared to the B&H. Risk-return trade-off analysis confirms the superiority of the technical strategy, where it produces greater ulcer performance index, Sharpe and Sortino ratios. These metrics confirm that returns from the technical rule are not characterized by higher risks. Our findings suggest that stock prices of these oil and gas companies neither fully nor rapidly capture historical price patterns, allowing traders to exploit and earn abnormal returns. The results are inconsistent with weak form market efficiency. [ABSTRACT FROM AUTHOR]

From 1991 to 2020, this study investigates the asymmetric effects of crude oil prices, exchange rates, and inflation on Bangladesh's performance in remittances. The non-linear autoregressive distributed lag (NARDL) model was utilized to determine the non-linear effects of our research variables on the performance of remittances. Higher oil prices have a significant and beneficial impact on the performance of remittances in the long run, but a significant and negative impact in the near run, according to the NARDL model's empirical findings in this study. Lower oil prices, on the other hand, have a negligible short-term and long-term influence on the performance of remittances. The adjustment asymmetry in the dynamic multiplier graphs demonstrates that the performance of remittances responds more strongly to a negative change in oil prices than to a positive change. Inflation and exchange rate reductions, on the other hand, have a significant impact on the performance of remittances both in the long and short run. According to the Wald test, there are asymmetries among variables. For Bangladeshi politicians and investors, the implications of this study are critical. [ABSTRACT FROM AUTHOR]

Financial markets and financial instruments and derivatives have experienced significant changes recently. Although this transition, the gold and crude oil are still leading the market and determine the main market conditions, so their importance could not be neglected. Looking back in history, there are milestone events that have drastically changed the economic, social and political circumstances, which have immediately affected the financial markets. In the recent study we calibrate jump-diffusion process to historical prices of gold (XAU) and crude brent oil futures (LCOc1), and derive piecewise approximations of the trend, volatility and jump intensity and distribution parameters. In the framework of jump-diffusion, we interpret the results as well as describe the possible future states of their prices and their impact on the global economy and quantify the respective outcomes probabilities. Based on the analysis, essential remarks for the economic environment are made in the conclusion of the paper. [ABSTRACT FROM AUTHOR]

With considerable uncertainty in energy markets, international cooperation between members of the Organization of Petroleum Exporting Countries and Russia regulates the industry. It was revealed that the sanctions imposed on Russian companies, as well as the decline in oil prices in the short term, did not have a significant impact on the stability of production of the Russian oil and gas sector. The conclusion that the absence of such influence is due to the significant volumes of raw materials and the presence of profits of Russian oil companies even when oil prices are decreasing, is substantiated. It is shown that in the context of declining resources, it is necessary to modernize the conditions of mining, to ensure coordination of efforts to conduct joint basic research work. Key benchmarks for the development of the oil and gas industry of the Russian Federation in the world market were identified: further supplies of Russian hydrocarbons in the context of economic interests of foreign countries; joint cooperation in developing equipment and technologies for deep offshore oil production and minimizing sanctions; further supplies of Russian hydrocarbons in the context of economic interests of foreign countries; cooperation with oil producing countries and OPEC countries to regulate the functioning of the industry. [ABSTRACT FROM AUTHOR]

At the time of primary production, a large amount of oil reserves are left in the reservoir. The purpose of this research is to determine the results obtained from the CO2 injection and water injection methods.Therefore, CO2 injection is one of the Enhanced Oil Recovery (EOR) methods used for the remaining oil reserves in the reservoir. Water injection is used to maintain the energy reservoir to ensure that oil is pushed from the reservoir into the production well. In this study CO2 and Water Flooding were analyzed using a literature review from previous studies and the results of the simulation of these 2 methods.. The method used in this research is the observation of the mechanism and the results obtained with the two methods. The results showed that the oil production at the beginning of gas injection increased significantly and was almost the same as water injection of 5,000bbl/day. The decline in oil production using CO2 gas injection was faster compared to water, due to its low small viscosity and gas density. In addition, the injection of CO2 gas led to the recovery of oil from a larger one with a difference in acquisition of 1-2%, which would be greater when the injection volume is increased. It was concluded that water flooding may be injected at a depth of less than 1000ft with an average permeability of 10mD and oil saturation of less than 5%. Meanwhile, CO2 injection may be injected at a depth of over 2500ft. Therefore, both types of injection were suitable for sandstone or carbonate rocks. From the results of this study it can be concluded that the difference between the two methods is the type of miscibility where CO2 injection is miscible, while water injection is not mixed. These two things have two different mechanisms. [ABSTRACT FROM AUTHOR]

A large amount of impurities in the oil when it is produced makes the price of the oil decrease. Therefore, it is necessary to demulsify the stable emulsion which is not separated from the oil, so that the impurity level becomes low. For this reason, it is required to add a demulsifier to increase water separation from oil, so that the oil price becomes higher. Demulsifier highly influenced by temperature, salt content, demulsifier mixture, and time. In this study the result yields to highest water separation is d NaCl 60%+PEG 1000 (20%), with heating system temperature at 70oC for 1440 minutes. The water separation from oil is as much as 96%. [ABSTRACT FROM AUTHOR]

CO2 flooding is one of the enhanced oil recovery methods (EOR) that has shown great potential for oil recovery enhancement. It is a proven method in worldwide CO2 EOR projects with significant enhancement in additional oil recovery. However, due to the content of medium-to-light oils, many mature oilfields in Indonesia propound the potential for incremental oil production through EOR techniques, including CO2 flooding, which has not been implemented. In addition, a significant amount of Indonesian potential reserves creates an opportunity to apply CO2 flooding to increase the national oil production. This research aims to analyze and assess the prospect of CO2 flooding and its potential application to Indonesian mature oilfields. In this work, we review the possibility and challenges of CO2 flooding to be implemented in Indonesian mature fields by collecting and analyzing data from publications including field reports and case studies, government reports, and journals. The result showed that the experimental research of CO2 flooding in other countries proved that the EOR technique is promising and needs to be applied. Furthermore, the EOR application through CO2 flooding depends on the availability of CO2 sources and the coordination of the whole process, starting from the development to separation. In Indonesia, CO2 sources are found in North Sumatra 10 TCF (83% CO2), South Sumatra Basin, East Java (2.53 TCF IGIP with 85-165 MMCFD CO2), and Natuna Basins (160 TCF Overpressure CO2 with 60-80% CO2). Many CO2 EOR candidates are fields located near the CO2 source such as Central Sumatra fields, South Sumatra fields, and the West Java Basin. Therefore, based on its availability, oil categories, and potential reserves, many Indonesian mature and declining oil fields become the promising target for CO2 EOR application. [ABSTRACT FROM AUTHOR]

By far, over the last couple of months, the day-to-day business activity of crude supply and demand in Indonesia has been in the position of barely touching the bottom line, moving disproportionally with the government's long- run strategic plan in providing sufficient energy supply for the consumers. The statistics have revealed the current energy supply realization is different than that of the last year. In brief, the performance of oil and gas export-import has been deeply disturbed since the global pandemic of Covid-19 broke out. This particular paper aims at portraying, from a macro perspective, the intricate nature of the oil and gas phenomenon, having many complexly interrelating variables. The methodology opted in this particular study is the multivariate linear regression to draw the complete picture of the relationship between the global pandemic and its profound impact on the oil and gas trade balance. The value of the originality of this study is to reveal the effect of a global pandemic to the Indonesia Economy at large and also to make suggestions to the policymakers, or other stakeholders in an effort to support the initiative of developing a strategic plan for the long-term sustainability of petroleum energy in Indonesia. [ABSTRACT FROM AUTHOR]

Oil & gas production is intensive cost activity due to the high cutting-edge technologies and energy requirements. In addition to the global continuous increase in power demands and due to the correlation of oil prices with global events which makes the price vulnerable to rapid fluctuation; most oil and gas companies tend to increase the production for the same oil field above the initial forecasting limit to increase the total profit in terms of monetary value during the oil wells' life. Nevertheless, the oil overproduction has negative impacts on the company main assets such as wells equipment damage, high wells depletion rate, high power consumption, high wastewater, low product quality and adverse environmental impact; which will make the operation and maintenance cost to be much higher than the production increasing revenues. As the Lean management system concepts and tools are well known in the oil and gas industry and already in use in several operations improvement projects. So, in this research, a new model is suggested to be readily used by any oil and gas company to solve the problem by using Lean concepts and tools such as Value stream mapping "VSM", Value Analysis, Method Study and Analytic Hierarchy Process "AHP" to eliminate wastes and concentrate the main values of the operations that lead ultimately to an acceptable increase in profits while not causing the mentioned overproduction problems. [ABSTRACT FROM AUTHOR]

This paper investigated the technical and economic feasibility of on-board boil-off gas reliquefaction system on a liquefied natural gas tanker ship which has 154,852 m3 cargo tank capacity operated in Tangguh Field Indonesia by comparing three systems available in the market for mini liquefied natural gas liquefaction, i.e. single nitrogen system, ethylene and propylene refrigerant system, and Joule Thomson cycle. All three systems were evaluated through chemical process modelling software and through sensitivity analysis by varying the boil-off gas and liquefied natural gas price comparing the net present value and internal rate of return. The sensitivity analysis result shows that the Joule Thomson cycle is more economic compared than the other two systems within the range of marine gas oil price must not higher than US$640/ton on liquefied natural gas price US$10/mmbtu or liquefied natural gas price must not less than US$7/mmbtu on marine gas oil price US$400/ton. [ABSTRACT FROM AUTHOR]

This paper investigates economic forces affecting Japanese stock returns paying particular attentions to economic/structural interpretations of structural shocks behind oil price and exchange rate movements, extending the frameworks of Kilian (2009) and Ready (2018) by including exchange rate variable in their models. The performance of the extended Ready's model is much better than the extended Kilian's model. However, we find economic interpretation of the Ready's empirical framework difficult, because stock returns respond positively to oil price increase due to oil supply shocks and the signs of the impact of exchange rate shocks change in sub samples. Statistical interpretations of two models are rather straightforward: in both models, the residuals of oil price uctuations that cannot be explained by other explanatory variables or structural shocks have positive impacts on Japanese stock returns. They are called oil-market-specific price shocks in Kilian's model and called oil supply shocks in Ready's model, because of their different identification strategies. [ABSTRACT FROM AUTHOR]

This paper surveys normative and positive reasons why oil and gas exporting countries chose to enter into downstream industries. Several explanations are surveyed from a normative and a positive aspect and then tested against observations, including: price differentiation (export taxes) from industrial organizations (about vertical integration and property rights), and arguments based on fostering development, on a comparative advantage, on hedging and a few others (e.g., opportunities due to climate mitigation). Few normative justifications meet the test of explaining what is going on. Local refining can serve as a partial hedge against the vagaries of oil price. Refining for domestic and regional markets can be economical and even local subsidies can be justified to some extent. However, all of those justifications seem to be mismanaged politically by granting the national oil companies a monopoly and by very large subsidies on refined products. Instead, current downstream activities serve rather political and managerial than economic objectives. [ABSTRACT FROM AUTHOR]

We show that European retail gasoline prices respond slower to changes in the dollar exchange rate than to changes in the international spot price of wholesale gasoline, which is quoted in dollars. This differential passthrough is not specific to the Euro, and is observed both for Euro-member states and also for those using national currencies. We examine the possibility that this pattern is driven by differences in either the variability and or persistence of exchange rates changes relative to those of the dollar price of gasoline, but find minimal supporting evidence for either. Refinery supply contracts treat changes in the dollar price and the exchange rate symmetrically, and are thus also an unlikely explanation. Other possibilities, such pricing to the market or pricing based on the country of origin are precluded by the nature of the product. There is evidence, however, that exchange rate fluctuations are more strongly correlated with country-specific economic conditions, which reduces the ability of firms to pass-through price increases and lessens their incentive to pass-through price decreases. Moreover, consumers likely draw a more direct link between the crude oil and retail gasoline prices, affecting their price expectations and search intensity, and optimal passthrough. [ABSTRACT FROM AUTHOR]

Gold investment began to be popular among groups, especially millennial generation. This is because the price of gold tends to rise continuously despite uncertain global economy. The objective of this study is to obtain the forecasting model that accommodate the effect of US-China trade war. The model used is a multivariate model that can accommodate contribution of other variables, which is the vector autoregressive with exogenous input (VARX). These variables consist of commodity prices (gold price, oil price) and political issue (US-China Trade War). The results of the study stated that the best fitted model is VARX(2,0)-I(1,0) in the form of reduced model with MAPE less than 12 percent. Moreover, there was no significant contribution of US-China trade war on gold and oil prices. [ABSTRACT FROM AUTHOR]

Trade tension or trade war between the U.S. and China has had a significant impact on many sectors in the world. The business sector is one of them. Trade tension began on March 22nd 2018, after U.S. President imposed a $50 billion import duty on Chinese goods entering the United States. In return, the Chinese central government also imposed import duty on more than 128 U.S. products. The import duty policy led to some decreases in productions and sales in China. As a result, the level of consumption and the demand for crude oil in China have declined. The fall in crude oil demand from the largest oil consumer, coupled with excess oil supply are estimated to produce volatility at the Brent crude oil price. Therefore, this study aims to model the monthly average of Brent crude oil price with the influence of trade war. The method used in this study is the Autoregressive Integrated Moving Average with Exogenous Variable (ARIMAX), where the exogenous variable is a dummy variable from the trade war between the U.S. and China. The results show that trade war has a significant effect on the monthly average of Brent crude oil price and the best model is ARIMAX(1,1,0), with a MAPE value of 13.6733 percent. [ABSTRACT FROM AUTHOR]

The oil and gas sector has witnessed in the recent period significant attention towards sustainable methods to enhance the oil recovery, A vivid example of this trend is Microbial Improved Oil Recovery. MIOR over conventional EOR has offered a major advantage, such as low consumption of energy and without succumbing to the prices of gas and oil. In this study, the major work was to isolate and identify the microorganisms to harness the process for producing biosurfactants. The isolated strain of bacteria microorganisms, Pseudomonas (SPP) strains were capable to secrete extra- cellular biosurfactants at 37 °C in aerobic conditions which have grown in medium supplemented with a carbon source. It was observed that the biosurfactants lowered the surface tension of water from 62 to 26 mN/m. In conclusion, the desirability of this work shows that the isolated microorganisms can be regarded as a promising medium for the development of improved oil recovery methods. [ABSTRACT FROM AUTHOR]

The mining industries face significant uncertainties resulting in technical and financial risks. Ore reserve is the most critical technical risk. On the financial side, the price fluctuations shape financial risk. Since the commodity prices are hard to predict accurately, a risk assessment process is commonly performed. The Monte-Carlo simulation is a common approach to assess risks in the mineral industries, and requires reproduction of the correlation between the uncertain variables. When these correlations are non-linear, the problem becomes more complicated and require special attention. One way to incorporate non-linear relations into risk analysis is to utilize from copulas. Thus, this research objective is to model the financial risk based on its dependence pattern. As a result, it is found that the gold prices that are correlated with the oil prices follow Clayton copula model with the parameter (θ) of 4.11. [ABSTRACT FROM AUTHOR]

Although the development method is strengthened in the process of oilfield exploitation in the later stage of high water cut, the actual efficiency is low. The analysis of both technical and economic benefits is not conducive to the sustainable development of oilfield enterprises. Especially in the context of the continuous decline of international oil prices, the mining cost of oilfields has been continuously improved, which has greatly hindered the realization of the economic benefits of oilfield enterprises. In order to realize its economic benefits, oilfield enterprises will reduce their cost and realize their core position in the market competition. Therefore, in the research, we should comprehensively explore the technical methods of secondary oil recovery, closely focus on the improvement of economic benefits, continuously realize the innovation and optimization of technology, and realize the sustainable development of oilfield enterprises. [ABSTRACT FROM AUTHOR]

The peak of energy demand, oil prices, and impending climate change are critically driving the adoption of solar photovoltaic (PV) as a sustainable, renewable and less impact energy alternative. The installation of PV systems for optimum yield is primarily dictated by its geographic location (latitude and available solar insolation), and installation design (tilt angle, orientation, and altitude) to maximize solar exposure. Once these parameters have been addressed appropriately, there are other externalities that contribute to the system performance (efficiency and output). Dust is a major factor that significantly influences the performance of the PV systems. Although substantial time and money have been invested in PV systems to increase efficiency, a far less time and money have been invested to address dust deposition on such systems. This paper provides an overview of soiling problems; primarily those associated with dust or sand and combined dust-moisture conditions that are associated with many of the most solar-rich geographic locations in the United States. It reviews and evaluates key contributions to the understanding, performance effects, and mitigation of these problems. More specifically, the paper reviews the impact of dust deposition on the performance of solar PV and identifies challenges to further research in this area. It highlights the status of research over seven decades of effort. Based on the research studies, the research outcome presents recommendations to guide in identifying the appropriate cleaning/maintenance cycle for PV systems. This is aligned with the prevalent climatic and environmental conditions in the United States' climatic zones based on ASHRAE classification. [ABSTRACT FROM AUTHOR]

Many studies have shown the impact of the changes of oil price on the global economy. The main objective of this study is to examine the impact of oil price changes and other non – oil factors on monetary policy behaviour and decision empirically. Generally, this study investigates the monetary policy reaction of oil importing versus oil exporting countries in response to the threshold effect of oil price changes and inflation. An advanced panel threshold regression is employed to study the money policy reaction function for the quarterly period from 1999 to 2016. For oil exporting countries, our results revealed that the existence of double – threshold effect of the oil price changes and inflation on monetary policy reaction. Also, results capture that the threshold effects of inflation and changes of oil price in determining the monetary policy reaction in both groups of countries. In both cases, higher inflation triggers to expansionary policy in which oil exporting exhibits a higher threshold inflation rate (4.63% and 16.37%) compared to oil importing countries (1.11% and 4.97%). On the other hand, oil price changes imposed a higher threshold impact on monetary policy among oil exporting countries compared to the oil importing countries. The results imply both oil and non-oil inflation are the main policy concern in oil exporting countries. However, non-oil (consumer price) inflation is the only concern of policy reaction in oil importing countries. [ABSTRACT FROM AUTHOR]

This paper proposes a fractional filter and Auto Regressive Fractional Unit Root Integral Moving Average (ARFURIMA) model on daily Malaysian Tapis Crude Oil Price (MTCOP) for the period 4th June 2007 to 29th June 2018. The goodness of fits and dependence tests of each model are discussed. Results indicate that ARFURIMA model is superior to the Auto Regressive Integral Moving Average (ARIMA) and Auto Regressive Fractional Integral Moving Average (ARFIMA) models in modelling and forecasting the Tapis Crude Oil Price. [ABSTRACT FROM AUTHOR]

In this paper, it was purposed to analyze the chaotic pattern of inflation-unemployment relation for the period from January, 1960 to April, 2019 in Turkey. For modelling this relation, oil prices were considered as an exogenous variable in examination of chaotic causal relation between inflation and unemployment. This model was applied in two stages: Firstly, the chaotic structure of the variables were determined by using Lyapunov Exponents and Henon Map and secondly by Hristu-Varsakelis and Kyrtsou(2010) [1] and Bai(2018) [2] Chaotic Causality Tests, the chaotic causal relations among the variables were decided. Because, these estimations are crucial especially for analyzing complex economic system of countries. [ABSTRACT FROM AUTHOR]