scholarly journals Oil and gas business in changing times

2017 ◽  
Vol 11 (1) ◽  
pp. 9-24
Author(s):  
Sergiu Brasoveanu
Keyword(s):  
Crude Oil ◽  
Value Chain ◽  
Corporate Strategy ◽  
Oil Production ◽  
Oil Price ◽  
The Other ◽  
Crude Oil Price ◽  
Oil Companies ◽  
Cost Cutting ◽  
Other Hand

Abstract The top 5 oil majors (British Petroleum, ExxonMobil, Total, Chevron and Royal Dutch Shell) are analyzed in terms of investments, earnings and financial & operational performance along the entire business value chain, for a period of 5 years. One of the key objectives is to understand how the Upstream and Downstream segments may play different roles in the definition of a winning corporate strategy, considering how they may reveal very different strengths and weaknesses during crude oil price crises. When the crude oil price goes down, the upstream sector is running big cost cutting measures, in order to reduce expenditures and keep acceptable gross margins per barrel of oil equivalent. On the other hand, the downstream segment receives cheaper raw material without a significant decrease in the final price of the oil products. Thus, how can oil companies leverage this flexibility in order to pass successfully through periods of crude oil price slides, and even take advantage of those? The paper aims to analyze the correlation between oil price and oil volume produced on one hand, and investments and earnings, split by business segments, on the other hand. The variation of investment and earnings is hence compared to crude oil price fluctuations for a clearer picture of the business profitability per segment during the peak and bottom periods of the oil market. Upstream and Downstream segments are also benchmarked against each other to understand the role that each of them is playing in the industry. The results are expected to provide some trend lines to understand how much the cost cutting measures are impacting the overall business, as well as to appreciate whether the reduction in the oil production, which in theory should be followed by a rise in prices, is indeed in the best interest of the oil majors. Going further into analysis, the paper is trying to define an optimum production interval, that will maximize profits along the entire value chain (upstream and downstream) of the oil business, defined by both the production volume of crude oil (replacement cost per barrel in accordance with volume), as well as the price per barrel of oil equivalent. The analysis takes into account official sources exclusively, i.e. oil companies’ websites, corporate crude oil production reports, annual financial reports and investors’ analyses.

scholarly journals Logistics Aspect of Offshore Support Vessels on the West Africa Market

2013 ◽  
Vol 25 (6) ◽  
pp. 587-593 ◽  
Author(s):  
Ivica Skoko ◽  
Marinko Jurčević ◽  
Diana Božić
Keyword(s):  
West Africa ◽  
Crude Oil ◽  
Oil Production ◽  
World Market ◽  
Oil Price ◽  
Crude Oil Price ◽  
Oil Companies ◽  
Energy Needs ◽  
Offshore Oil Production ◽  
Offshore Oil

With the rapidly increasing global energy needs, offshore oil production has become an attractive source of energy. Supplying offshore oil production installations is a complex logistics problem that hinges on many factors with significant uncertainties. So, it is critical to provide the necessary supplies and services without interruption. In a typical offshore oil production effort, oil companies charter most or all drilling units as well as offshore supply vessels (OSV). The type and duration of charter contract has direct impact on the project budget as vessels market is closely correlated with the world market crude oil price which can have daily significant fluctuations. As the region of West Africa is one of the world’s busiest offshore exploration and oil production markets employing 12% of the world’s fleet, exploring its issues, was taken to study the relations between daily OSV rates and crude oil price. The research results presented in this paper show correlation between OSV daily rates and crude oil price with broader fluctuations in crude oil price. 

Crude oil price–shale oil production nexus: a predictability analysis

2020 ◽  
Vol 14 (4) ◽  
pp. 729-744 ◽  
Author(s):  
Sam O. Olofin ◽  
Tirimisiyu Folorunsho Oloko ◽  
Kazeem O. Isah ◽  
Ahamuefula Ephraim Ogbonna
Keyword(s):  
Crude Oil ◽  
Predictive Model ◽  
Good Predictor ◽  
Forecast Accuracy ◽  
Oil Production ◽  
Oil Price ◽  
Shale Oil ◽  
Reverse Causality ◽  
Crude Oil Price ◽  
Content Type

Purpose The purpose of this study is to investigate the predictability of crude oil price and shale oil production, in a bid to examine the possibility of bi-directional causality. Design/methodology/approach The study adopts a recently developed predictability model by Westerlund and Narayan (2015), which accounts for persistence, endogeneity and heteroscedasticity. It also accounts for structural breaks in the predictive models. Findings The empirical results show that only a unidirectional causal relationship from crude oil price to shale oil production exists. This happens as crude oil price appears to be a good predictor of shale oil production; however, shale oil production does not serve as a good predictor for crude oil price. Accounting for structural break was found to improve the predictability and forecast accuracy of the predictive model. Our result is robust to choice of crude oil price benchmarks (West Texas Intermediate, Brent, Dubai Fateh and Refiners’ Acquisition Cost) and their denominations (real or nominal). Research limitations/implications The result implies that crude oil price must be considered when predicting shale oil production. Meanwhile, the non-significance of shale of production in crude oil price predictive model provides information to potential analyst, researchers and countries predicting crude oil price that failure to account for the effect of shale oil production would not have significant impact on the forecast accuracy of their models. Originality/value The study contributes originally to the literature on crude oil price–shale oil production in four major ways. First, it applies a recently developed predictability method by Westerlund and Narayan (2015), which is more suitable for dealing with persistence, conditional heteroscedasticity and endogeneity in the predictors. Second, it investigates existence of reverse causality between crude oil price and shale oil production. Third, it examines the variation in the response and effect of four major crude oil price benchmarks. Fourth, it considers crude oil price in both real and nominal terms.

Petrobras Brazil outlook improves but challenges loom

2018 ◽  
Keyword(s):  
Crude Oil ◽  
Government Policy ◽  
Oil Price ◽  
Crude Oil Price ◽  
Upward Trend ◽  
Short Term ◽  
Content Type ◽  
Oil Companies ◽  
Future Success

Subject The outlook for Petrobras. Significance The collapse of the crude oil price in 2014, a huge corruption scandal and government policy have combined to damage Petrobras. While most major international oil companies have turned a corner and their profitability is on an upward trend, uncertainties continue to plague the company. Impacts Future success will depend in part on Petrobras tackling its debt mountain effectively. Petrobras will face a struggle to regain credibility in the markets despite improving results. Plans to require congressional approval of privatisations, and diverging campaign promises on Petrobras, will increase short-term doubts.

scholarly journals Forecasting Volatility of Crude oil Prices using Box-Jenkins's Autoregressive Moving Average: Evidence from Indian Chemical Industry

2019 ◽  
Vol 8 (3) ◽  
pp. 229-234
Keyword(s):  
Crude Oil ◽  
Moving Average ◽  
Oil Prices ◽  
Information Criteria ◽  
Oil Price ◽  
Spot Price ◽  
Autoregressive Moving Average ◽  
Crude Oil Price ◽  
Oil Companies ◽  
Crude Oil Prices

The current paper deals with to forecast volatility in crude oil prices in Indian economy. In the current study volatility is measured through change in monthly crude oil prices per barrel. The monthly data of crude oil price have taken from January 1995 to May, 2017. The different unit root tests are applied to test check change in crude oil price series is stationary or non stationary. Box-Jenkins's Autoregressive Moving Average of Box-Jenkins methodology has been used for developing a forecasting model. Minimum Akaike Information Criteria (AIC) has been opted to arrive at fit good ARMA model. According to this criteria (4, 3)(0,0) was observed as one of the best model to predict the volatility in future crude oil prices. Forecasted volatility in prices may be utilized for calculating future spot price and hedging future risk. Moreover, forecasted prices volatility of crude oil will also beneficial to oil companies, policy makers for formulating different economic policies and taking some crucial economic decision.

scholarly journals Oil threshold value between oil price and production

2019 ◽  
Vol 66 (4) ◽  
pp. 487-505 ◽  
Author(s):  
Tzu-Yi Yang ◽  
Ha Thanh ◽  
Chia-Wei Yen
Keyword(s):  
Crude Oil ◽  
Price Volatility ◽  
Oil Prices ◽  
Oil Production ◽  
Threshold Value ◽  
Oil Price ◽  
Smooth Transition ◽  
Crude Oil Price ◽  
Oil Price Volatility ◽  
Crude Oil Production

This study proposes a panel smooth transition regression (PSTR) model to investigate the nonlinear relationship between crude oil prices and crude oil production in 122 countries, both OPEC and non-OPEC, from March 1994 to October 2015. The statistical test for the existence of a threshold effect indicates that the relationship between oil prices and oil production is nonlinear, with different changes over time among the oil price and transition variables. Additionally, a threshold value exists. Furthermore, crude oil price volatility exhibits asymmetric responses to production volatility by fluctuating above or below the threshold value. Finally, when crude oil price volatility with a lag of two periods exceeds the threshold value, crude oil production changes have a positive impact on crude oil price volatility. In contrast, when crude oil price volatility with a lag of two periods is less than the threshold value, crude oil production changes have a negative impact on price volatility.

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