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As one of the leading oil producers in the world, Nigeria's economy is profoundly influenced by fluctuations in global oil prices, affecting the government capacity to allocate resources on national healthcare system and its ability to ensure healthy lives and promote wellbeing for all, as outlined in Sustainable Development Goal 3 (SDG-3). On this backdrop, this study has undertaken a comprehensive examination of both linear and non-linear relationship between oil price shocks and sustainable development in Nigeria, a country heavily reliant on oil revenue from 1970 to 2022 in Nigeria. Using linear Autoregressive Distributed Lag (ARDL) and nonlinear Autoregressive Distributed Lag (NARDL) models, the findings show that increasing crude oil price shock has a substantially large adverse impact on SDG-3 in the short run while decreasing crude oil price has unobserved effect in both short and longrun when asymmetries were considered. Based on the findings of this study, Nigerian policymakers should expedite efforts to diversify its economy away from oil dependency. This diversification should focus on promoting sectors with growth potentials, creating jobs, and generating stable revenues to support healthcare and sustainable development initiatives. The study highlights other actionable insights and policies to navigate the challenges posed by oil price volatility while advancing the noble aspirations of SDG 3 for the people of Nigeria. [ABSTRACT FROM AUTHOR]

This article investigates the effect of global oil and wheat prices, and local price shocks on the real price of wheat flour in Lebanon. We estimate a structural vector autoregressive model with exogenous variables (SVARX) using Bayesian methods. We then compute the impulse response functions and find that global commodity price shocks play a trivial role. Meanwhile, local gasoline price and wheat flour price‐specific shocks trigger large increases in the Lebanese wheat flour price on impact. Furthermore, since 2020, local gasoline price and wheat flour price‐specific shocks have contributed the most to the historical variation in the Lebanese wheat flour price. [ABSTRACT FROM AUTHOR]

We examine the nexus between financial inclusion and energy poverty. Analysing data for 27 energy-poor countries in the Sub-Saharan Africa region over 2004–2021, we employ sequential (two-stage), panel-corrected standard error (PCSE) and two-step dynamic system GMM (generalized method of moments) regression models, and control for endogeneity, CSD, slope heterogeneity as well as stationarity and cointegration patterns of the variables. Our empirical results show that financial inclusion significantly reduces energy poverty in the selected energy-poor countries. The study also finds a positive significant association between energy access and GDP per capita, while oil price and energy intensity are inversely associated with energy access. The results are robust to different control variables, estimation methods and subsamples. These findings have strong policy implications for energy-poor countries and point to the need for appropriate policies to promote financial inclusion for reducing energy poverty. [ABSTRACT FROM AUTHOR]

This work uses the vector-valued Bernoulli equation to build a nonlinear multi-variable grey Bernoulli model, which is available to describe the nonlinear relationship between the output variables. By using P a d e ´ approximation, the proposed model can be implemented with high time efficiency. Additionally, the Sine Cosine Algorithm is employed to determine the Bernoulli exponent, thereby enhancing prediction accuracy. To evaluate the predictive performance of the proposed model, three case studies using three real-world data sets with different features of predicting per capita household income, fuel prices and crude oil prices are carried out. The results are compared with three existing grey multi-input multi-output models. Experimental results demonstrate that the proposed model excels in handling nonlinear relationships between variables and has strong robustness against noise, consistently delivering lower error values, demonstrating superior predictive performance. • A nonlinear multi-variable grey Bernoulli model is proposed based on the Hadamard product. • Linear parameter estimation is carried out using the least squares method or the least norm method. • P a d e ´ approximation is used to compute the matrix exponential to improve the time efficiency. • The model is optimized using the Sine Cosine Algorithm. • The proposed model shows superior prediction performance compared with three other typical models. [ABSTRACT FROM AUTHOR]

Dissolved air flotation (DAF) is an effective method for separating suspended oil and solid particles from wastewater by utilizing small air bubbles. This study aims to investigate the impact of key factors, such as saturating pressure and water flow rate, on the separation of fine oil droplets from a water stream. The macroscopic flow patterns within the cell were analyzed using particle image velocimetry (PIV), while Digital Image Analysis (DIA) was employed to study microscopic phenomena, including oil droplet rising velocity and oil-bubble contact mechanisms. Our findings propose a safe operating window (specifically, water flow rate and saturation pressure) for the effective separation of oil droplets without any oil escaping into the clean water stream. It was found that the oil droplet rising velocity increases with the saturation pressure up to 200 kPa. However, a further increase in the pressure of the air saturating chamber leads to a decrease in oil droplet rising velocity. Additionally, we identified a peak in rising velocity at an oil droplet size of approximately 200 µm. Below this threshold, the rising velocity increases with droplet size, while for droplet sizes exceeding 200 µm, the rising velocity decreases with size. This behavior can be explained by the conflicting effects of droplet size increment according to the Stokes law for the rising velocity of oil droplets. As the droplet size increases, the average density of the bubbles/droplet aggregate rises, reducing the ∆ρ in the Stokes law and subsequently lowering the aggregate rising rate. However, as per the Stokes law, the oil droplet rising velocity increases proportionally to the square of its size. [ABSTRACT FROM AUTHOR]

Addressing the interconnectedness of oil prices and foreign exchange rates poses a substantial challenge and raises significant questions within economic research. Existing studies reveal a fragmented understanding of the dynamics between these crucial variables, highlighting a need for deeper investigation. This study extends previous research by employing the time-varying parameter VAR extended joint connectedness model and using the baseline approach called the generalized connectedness approach. Our research findings indicate that exchange rates and crude oil prices exhibit pairwise and total connectedness, varying over time. Furthermore, this connectedness experiences substantial increases during severe crisis periods. We uncover that exchange rates and crude oil prices not only share a dynamic, pairwise, and total connectedness but these results are stronger for oil exporting countries. However, these methods yield inconsistent results for various countries. Moreover, there is compelling evidence that fluctuations in exchange rates and oil prices can cause bi-directional and time-dependent shocks. [ABSTRACT FROM AUTHOR]

The need for renewable energy is regarded as a major component in the move towards achieving sustainable development. Using a large sample of 177 countries over the period 1990 to 2020, this research explores the impact of the most significant drivers of renewable energy. Findings from this work contribute to the literature by identifying the most significant drivers of renewable energy deployment and their different responses in developed and developing economies. Empirical results suggest that GDP, oil price, access to electricity, and CO2 and methane emissions are significant determinants of renewables both as a share in energy consumption and as a share in electricity production. Additionally, trade is found to be a significant driver for the share of renewables in total energy consumption but not for the share of renewables in the electricity production model. Finally, our findings indicate that the factors influencing the development of renewables vary significantly between developed and developing countries, necessitating distinct approaches for each group of countries. These results can play a significant role from a policy perspective in designing and implementing specific policies to increase renewable energy deployment. [ABSTRACT FROM AUTHOR]

The interaction between new energy vehicle (NEV) stock prices and the crude oil market is crucial for resource allocation and risk management. This study employs Multifractal detrended cross-correlation analysis (MF-DCCA) to investigate the multifractal characteristics of the cross-correlation between Tesla stock price (TSLA) and crude oil price (Brent), as well as between TSLA and other NEV stocks (excluding TSLA). The experimental results reveal long-term persistence and multiple fractal characteristics in the cross-correlations. Additionally, multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) demonstrates the asymmetry of the cross-correlation during upward or downward trends between TSLA and Brent, as well as between TSLA and other NEV stocks (excluding TSLA). Furthermore, utilizing the transfer entropy (TE) method, we assess the strength and direction of information flows between TSLA and Brent, and between TSLA and other NEV stocks (excluding TSLA). Interestingly, we observe bidirectional information transmission between TSLA and other NEV stocks, while only unidirectional information transmission from NIO to TSLA is evident. These findings provide valuable insights for resource allocation, supply chain management and sustainable development strategies for decision-makers in the NEV market. [ABSTRACT FROM AUTHOR]

Energy is vital to international trade, social security, and financial markets. Crude oil, as a non-renewable resource, is affected by complex factors. To better capture this influence, we introduce stochastic differential equations (SDEs) to depict crude oil prices. This paper establishes time-dependent linear and space-dependent nonlinear SDEs respectively. Time-dependent linear SDEs are established by recovering the drift and diffusion terms based on point estimation and sliding window. Space-dependent nonlinear SDEs are established by sparse Bayesian learning. Empirical results show that time-dependent linear SDE can better describe the actual fluctuations of historical crude oil prices, and can predict more accurately compared with constant coefficient linear SDE, namely geometric Brownian motion. The space-dependent nonlinear SDE can achieve the effect of time-dependent linear SDEs on historical data, while the former is more accurate in predicting. In addition, the former gained an in-depth understanding of the intrinsic dynamics. In summary, the models proposed in this study provide powerful tools for better understanding and predicting crude oil prices, which make a positive impact on the stability of the global economy and energy markets. [ABSTRACT FROM AUTHOR]

This paper examines the divergent trajectories of automotive investment and employment in Detroit, Michigan and Windsor, Ontario. Located on opposite shores of the Detroit River, in the United States and Canada respectively, Detroit and Windsor are the founding cities of the North American auto industry. Long dominated by the Big Three, their factories have produced vehicles for the same continental market since 1965. Each has weathered parallel challenges since then, including spikes in the price of oil, the Big Three's loss of market share, the transition to lean production, and the near-collapses of Chrysler and GM. Yet Detroit began deindustrializing decades earlier and lost much more employment than Windsor. To determine why, we compared their automotive sectors from 1900 to the 2010s. Since the Depression, each city has repeatedly confronted the prospect of deindustrialization, but three factors have made Windsor more resilient: (1) federal and provincial interventions on its behalf, (2) Windsor's greater competitiveness with respect to factor costs, quality, and innovation, and (3) Windsor's annexation of outlying territory to capture new factories. These differences show how national, subnational, and regional/local policies have mediated corporate decision-making to produce a variegated North American Rust Belt, with Canada outperforming the United States. [ABSTRACT FROM AUTHOR]

The study investigated the potential non‐linear impacts of fluctuations in oil prices on domestic prices in Nigeria. Utilising the non‐linear autoregressive distributed lag (NARDL) model, the study revealed the presence of asymmetry in the behaviour of domestic prices. Both forms of oil price shocks were observed to have a negative influence on domestic prices in the short term, with only positive oil price shocks demonstrating statistical significance. However, in the long run, a distinct pattern emerged where a decrease in oil prices significantly affected domestic prices. Additionally, analysis of VAR impulse response showed a consistently negative reaction of domestic prices to oil price shocks, falling below the steady‐state equilibrium. The study concluded that changes in oil prices, in conjunction with other macroeconomic variables, affected the prices of domestic goods in Nigeria, whether in the short or long term. This underscored the complexity of Nigeria's economic landscape. Consequently, it is advisable to prudently invest excess revenue generated from rising oil prices to mitigate the adverse impacts of negative oil shocks on the economy. [ABSTRACT FROM AUTHOR]

This paper argues that energy efficiency is a potent shield against oil price uncertainty in an increasingly interconnected world fraught with geopolitical tensions. By reducing dependence on oil, enhancing economic resilience, and improving energy security, energy efficiency measures offer multifaceted benefits for both national economies and global stability. Specifically, a wavelet coherence analysis is conducted to study the response of global energy efficiency to geopolitical oil price uncertainty. Quantile-on-quantile and quantile regressions are additionally employed to separate the impacts of various geopolitical oil price risk quantiles on the quantiles of energy efficiency. These methods are utilized in the examination of global time-series data covering the timeframe 2004:Q1–2020:Q4. The wavelet coherence outcomes indicate a positive correlation between geopolitical oil price uncertainty and energy efficiency, particularly during the energy crisis of the 2000s and the COVID-19 pandemic. The results also reveal that geopolitical oil price uncertainty leads to energy efficiency, indicating that an upsurge in geopolitical oil price uncertainty causes energy efficiency to increase. Moreover, the results from quantile-on-quantile and quantile regressions affirm the predominantly positive effects of geopolitical oil price uncertainty on global energy efficiency. Our conclusion therefore is that through strategic investments, innovative policies, and international collaborations relating to energy efficiency, nations can fortify themselves against the destabilizing effects of geopolitical conflicts on energy markets. This would ensure a more sustainable and secure energy future for all. [ABSTRACT FROM AUTHOR]

In 2020, the world experienced several significant events, including the coronavirus (COVID-19) pandemic and the collapse of international crude oil prices. The rapid spread of this pandemic has dramatic impacts on financial markets all over the world, thereby increasing market risk aversion in an unprecedented way since the subprime financial crisis. The decline in stock markets implied volatilities of equity and oil prices, thereby heightening turmoil in global financial markets despite comprehensive and substantial financial reforms. To this end, we investigated the likely effects of this pandemic on the Saudi stock market while controlling for oil prices based on daily data for a period from 1/1/2020 to 19/9/2022. To ascertain the existence of a long-run equilibrium relationship between the variables, we applied autoregressive distributed lag (ARDL) modeling and the error correction model, with this ultimately revealing the existence of strong cointegration in the long run. The ARDL bounds test was found to be robust by combined cointegration tests, thus providing further evidence of a strong relationship in the long run. Granger causality tests also yielded evidence of causality between the variables in both directions. The total COVID-19 confirmed cases and oil prices also caused movements in stock returns in the short run. Our findings have some prominent implications for asset managers and policymakers to improve stock market efficiency and boost global economic activity. Saudi authorities can consequently remove the regulatory and legal obstacles to develop their stock market and better improve the risk management, which will allow to make quick decisions in response to any oil price volatilities. Policymakers should also adopt proactive strategies that can comfort stock investors' anxieties over the increasing oil price volatilities. Finally, the findings should be treated with some cautions because of the limited sample size and the tests' statistical inference. Nevertheless, they do open opportunities for further studies to look in more detail at how the COVID-19 pandemic affected, over the short and long run, monetary and fiscal policy coordination, financial stability, and various other macroeconomic indicators in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Unprecedented increases in European natural gas prices observed between late 2021 and mid 2022 raise a question about the sources of these events. In this article we investigate this topic using a time-varying parameters structural vector autoregressive model for crude oil, US and European natural gas prices. This flexible framework allows us to measure how disturbances specific to the analyzed markets propagate within the system and how this propagation mechanism evolves in time. Our findings are fourfold. First, we show that oil prices are hardly affected by shocks specific to natural gas markets, whether in the US or Europe. Second, we demonstrate that oil shocks have limited impact on US natural gas prices, which points to the decoupling of both markets. Third, we evidence that over longer horizons natural gas prices in Europe are still mostly determined by oil shocks, with idiosyncratic disturbances leading to short-lived decoupling of both commodity prices. Fourth, we illustrate that along the gradual shift from oil price indexation to gas-on-gas competition, the contribution of idiosyncratic shocks to European natural gas prices has increased. Nonetheless, we discuss why the notion that EU natural gas and crude oil prices have decoupled might be premature. [ABSTRACT FROM AUTHOR]

This study utilized both single-regime GARCH and double-regime GARCH models to investigate oil price volatility, Spanish macroeconomic factors, and stock prices during major crises such as geopolitical conflicts, the global financial crisis (GFC), and COVID-19, covering the period from Q2-1995 to Q4-2023. Additionally, the impact of crude oil price volatility on these factors was examined. The empirical results confirmed the presence of the leverage effect and identified multiple volatility switches associated with remarkable events like the GFC, the European debt crisis, the COVID-19 pandemic, and the Russian war. ARDL model analysis revealed a statistically significant positive relationship between oil prices and both unemployment and inflation rates in the long term, while other factors showed a negative correlation. [ABSTRACT FROM AUTHOR]

Although the recent debate in energy economics on the importance of oil price indexation versus shale gases suggest that big data can be used in predictive analysis in energy economics, little is known particularly in the context of shale gas and oil price interlinkages. Grounding our investigations in such directions we investigate in this paper the relationship between gas and crude oil markets and the impact US shale gas by employing time-varying causality method by Shi et al. (J Time Ser Anal 39(6):966–987, 2018; J Financ Econom 18(1):158–180, 2020) and cross-quantilogram correlation approach by Han et al. (J Econom 193(1):251–270, 2016). In particular, as a representative of the crude oil market, we use OPEC oil; WTI; Crude oil Oman; Crude oil Dubai while for the gas market, we use natural gas prices of UK NBP (National Balancing Point), NYMEX HH (Henry Hub) and US shale gas prices. Data period is from 11th January 2013 to 8th September 2020. We find significant negative spillovers from crude oil markets to natural gas markets particularly during moderate market conditions. The results suggest crucial implications in energy economics literature, to diversify assets to hedge against risks. We further find strong causality association between oil markets, natural gas markets and further oil markets and shale gas markets. Our findings describe that aftermath of the shale-gas boom the predictability nexus between oil and natural gas increased. Once we condition for shale gas the significant negative spill overs from oil markets to natural gas markets increases in the long-run. We suggest important policy prescriptions which have interconnected market repercussions. [ABSTRACT FROM AUTHOR]

This study examines the dynamic relationship between oil prices and exchange rates, concentrating on the effects of various exchange rate regimes on this relationship. Previous research on the relationship between oil prices and exchange rates has been extensive; however, the effects of different exchange rate regimes have not been properly investigated. For instance, we utilize econometric techniques like Vector Autoregression (VAR) analysis, Augmented Dickey-Fuller (ADF), and PhillipsPerron (PP) unit root tests on Turkey that are highly reliant on the price of Brent crude oil. The findings indicate that exchange rate regimes have a significant impact on the long-term correlations between oil prices and exchange rates, as well as the volatility of these correlations. The analysis highlights how important it is for emerging nations' fiscal and monetary policymakers to consider these dynamics. Policymakers will benefit from a greater knowledge of these links as a result of this work, which will assist lessen the economic instability caused by fluctuations in oil prices. Additionally, the results imply that, in comparison to fixed regimes, flexible exchange rate regimes may provide greater resilience against shocks to the price of oil. This knowledge is especially helpful for developing nations looking to create more resilient economic strategies. [ABSTRACT FROM AUTHOR]

Over the years, oil prices and financial stock markets have always had a complex relationship. This paper analyzes the interactions and co-movements between the oil market (WTI crude oil) and two major stock markets in Europe and the US (the Euro Stoxx 50 and the SP500) for the period from 1990 to 2023. For that, I use both the time-varying and the Markov copula models. The latter one represents an extension of the former one, where the constant term of the dynamic dependence parameter is driven by a hidden two-state first-order Markov chain. It is also called the dynamic regime-switching (RS) copula model. To estimate the model, I use the inference function for margins (IFM) method together with Kim's filter for the Markov switching process. The marginals of the returns are modeled by the GARCH and GAS models. Empirical results show that the RS copula model seems adequate to measure and evaluate the time-varying and non-linear dependence structure. Two persistent regimes of high and low dependency have been detected. There was a jump in the co-movements of both pairs during high regimes associated with instability and crises. In addition, the extreme dependence between crude oil and US/European stock markets is time-varying but also asymmetric, as indicated by the SJC copula. The correlation in the lower tail is higher than that in the upper. Hence, oil and stock returns are more closely joined and tend to co-move more closely together in bullish periods than in bearish periods. Finally, the dependence between WTI crude oil and the SP500 stock index seems to be more affected by exogenous shocks and instability than the oil and European stock markets. [ABSTRACT FROM AUTHOR]

We assess the impact of changes in oil prices on building permit applications in the top oil-producing counties, using monthly data between 2004 and 2021. In the long-run, a positive shock in oil prices increases the number of home permit applications in Lea and McKenzie Counties. Long-run point estimates also reveal that a 10 percent increase in oil prices reduces building plans by 2 and 3.4 percent in Kern and Oklahoma Counties, respectively. In Midland and McKenzie Counties, only long-run changes in oil prices impact home investment decisions while short-run changes have no impact. The inverse relationship between oil prices and permit applications hints that investors may dampen construction plans in lieu of higher costs of raw materials during periods of higher energy prices. Threshold Autoregressive model findings demonstrate that changes in permit applications occur during periods of high oil prices. Our findings imply that the expansionary monetary or fiscal policies that would be required to revive the housing market would need to be regime and region specific. Thus, coordination between regional lending units and investors is important and can boost recoveries from economic downturns. [ABSTRACT FROM AUTHOR]

Uncertain time series models constitute a pivotal tool for analyzing phenomena evolving over time. However, most of the prevailing research centers on parameter models, which exhibit limitations in addressing intricate temporal dynamics. To address this gap, this paper introduces a non-parametric uncertain time series model. Primarily, we propose the definition of the non-parametric uncertain time series models. Subsequently, tailored to the non-parametric uncertain additive autoregressive model, we propose a non-parametric estimation method based on linear polynomial splines. Following this, the effectiveness of these estimations is verified through residual analysis and uncertain hypothesis tests. Finally, we apply the introduced non-parametric estimation approach to the Brent crude oil spot price. [ABSTRACT FROM AUTHOR]

The uncertainty caused by high volatile crude oil prices and the higher level of deregulations worldwide has significant effects on the economic growth of a country. The financial markets of many developing countries experienced a severe downturn during the oil price shocks in March-April 2020. Traditional predictive approaches, which assume linearity and stationarity of time series in the long run, fail to accurately capture short-term fluctuations. This paper presents an efficient algorithm based on ARMA denoising and taking advantage of the wavelet transformation. By decomposing the time series and extracting the intricate underlying structure, wavelet denoising minimizes distortions and enhances forecasting accuracy. The results demonstrate a substantial improvement in performance compared to conventional forecasting techniques. [ABSTRACT FROM AUTHOR]

Given the demand for oregano oil in the food, pharmaceutical, and cosmetic industries, in this work for the first time an attempt was made to investigate innovative methods for extracting essential oil from oregano in order to reduce energy consumption and ensure high-quality product. Three different methods of distillation, conventional hydrodistillation (CH) and hydrodistillation with ultrasound application (UH) and with ultrasound pretreatment (UPH) were examined using a frequency of 20 kHz and an intensity ranging from 65 to 120 W. For each method, various parameters (amplitude level, pulse duration/pulse interval ratio, and treatment time) were examined for their effect on oil yield. The optimum distillation method and operating conditions were determined. The obtained oils were analyzed by gas chromatography–mass spectrometry (GC–MS) and characterized for their total phenolic content and antioxidant activity. In all treatments, the oil was collected at various time intervals and two mathematical approaches were selected for the kinetic modelling, namely, the first order kinetic model and the Peleg's model. Ultrasounds led to an increase in oil yield of 8% for UPH and 17% for UH, as compared to the conventional method, shorter distillation time, and slightly higher energy consumption that can be ignored taking into account the high price of the oil. The composition of oils distilled by ultrasounds was not differed from that of oil produced with the classic method. The use of ultrasounds increased the total phenolic content of the oils, whereas their antioxidant activity did not differ from that of the conventional product. [ABSTRACT FROM AUTHOR]

Due to the extremely low permeability of shale formations, the combination of horizontal well and volume fracturing has been proposed as an effective technique to improve the production of Dagang continental shale oil reservoirs. Based on the flow material balance method (FMB) and straight-line analysis (SLA) method, the stimulated reservoir volume (SRV) and drainage volume are determined to identify the flow regimes of the seepage mechanism of shale oil reservoirs. To resolve the challenges of multi-scaled flow regimes and bottom hole pressure (BHP) variation before and after pumping in shale oil wells, a multi-linear analytical flow model was established to predict the future production and the final expected ultimate recoverable oil (EURo) after fitting the historical production dynamics. Based on the results, it can be concluded that the flow regime of a shale oil well in production can be divided into two stages consisting of linear flow within SRV and composite flow from the un-stimulated area to SRV. The effects of fracturing operation parameters, such as fracturing fluid volume and sand/liquid ratio, on shale oil productivity, are analyzed, and insightful suggestions are drawn for the future development of this pay zone. [ABSTRACT FROM AUTHOR]

The stability analysis of horizontal wells is essential for a successful underground coal gasification (UCG) operation. In this paper, a new 3D coupled thermo-mechanical numerical modeling is proposed for analyzing the stability of UCG horizontal wells. In this model, the effect of front abutment stresses, syngas pressure, syngas temperature and thermal stresses is considered to predict the mud weight window and drilling mud pressure during UCG process. The results show that the roof caving in UCG panel has a greatest impact on the stability of horizontal well. Moreover, when the time of coal gasification is increased, the well convergence increases and for more stability it is necessary to increase the drilling mud pressure. This research was carried out on the M2 coal seam in Mazino coal deposit (Iran). The results showed that the mud weight window for horizontal well drilling is between 0 and 33 MPa. The appropriate stress for the maximum stability of the horizontal well, taking all the thermal and mechanical parameters into account, is 28 MPa. The suggested numerical method is a comprehensive and consistent way for analyzing the stability of horizontal wells in UCG sites. [ABSTRACT FROM AUTHOR]

The present work investigates the volumetric and viscometric properties of an aqueous solution of 1,2-dimethylethylenediamine (DEEDA) over an entire concentration range and an absorber operating temperature range of 313.15K-333.15K at atmospheric pressure. The investigated volumetric properties included the density, excess molar volume, partial molar volume, and the investigated viscometric properties included the viscosity, viscosity deviation, free energy for activation of viscous flow, excess free energy for activation of viscous flow, and excess entropy for activation of viscous flow. The results indicated that there are strong intermolecular interactions and suitable molecular packing in the binary DEEDAewater mixture. Hence, the mixture was found to deviate from a real mixture according to the calculated excess properties. The DEEDA solvent's preliminary volumetric and viscometric properties revealed convincing potential as a novel amine for carbon capture. Additionally, the Redlich-Kister-based correlations showed favorable correlative performance for excess molar volume, viscosity deviation, and excess entropy for activation of viscous flow. [ABSTRACT FROM AUTHOR]

Sandstone reservoirs often contain clay particles that can cause damage and reduce permeability during low-salinity water flooding. In this study, the effect of surfactants on fine migration in clay-rich sandstones and its impact on oil recovery was investigated. First, the impact of surfactants on interparticle forces in fine-matrix, fine-fine, and oil-matrix systems was modeled. The results showed that both CTAB (cetyltrimethyl ammonium bromide) and QS (quillaja saponin) cause EDL compaction, weakening the repulsive forces. However, SDS (sodium dodecyl sulfate) and TX (triton X-100) do not affect the EDL. Next, the effect of surfactants on IFT reduction and wettability alteration was experimentally investigated. All surfactants reduced IFT due to the surface excessive concentration mechanism. The wettability alteration experiment illustrated that although QS and CTAB compact EDL around oil and matrix particles leading to attraction force augmentation, they both alter wettability through adsorption on matrix and carboxylic groups present in crude oil, respectively. Surfactant aqueous solutions were then injected into various clay-rich sandstone sanpacks, which resulted in increased oil recovery. However, the mechanisms leading to enhanced oil recovery variedby surfactant type. CTAB increased recovery by 10% through IFT reduction and wettability alteration, while SDS and TX increased recovery by 12% and 9%, respectively, through wettability alteration and extreme fine migration. In contrast, partial fine migration in the QS flooding experiment reached a recovery increase of 18%. Permeability trends through experiments were also recorded. During CTAB injection, permeability did not reduce, while QS aqueous solution reduced rock permeability to 5 mD. SDS and TX reduced the magnitude of permeability to 2 mD. In conclusion, this study demonstrates that surfactants can effectively improve oil recovery in clay-rich sandstones by altering the interparticle forces, reducing IFT, and changing wettability. The results suggest that the type of surfactant used should be carefully selected to achieve the desired recovery increase without affecting the permeability of the reservoir. [ABSTRACT FROM AUTHOR]

Cambrian in Sichuan basin developed thick black shale, varies carbonate and clastic rock, which deposited in different sedimentary environment. Sichuan basin in the upper Yangtze platform contained a record of environment during the Cambrian. Detail facies analyses of Cambrian enable us to discuss the sedimentary environment and palaeogeographic setting. Sedimentation commenced in the Early Cambrian with the deposition of shelf facies (Qiongzhusi Formation and Canglangpu Formation). At this stage, thick shale and clastic rock deposited in Sichuan basin. At the end of the Early Cambrian, a carbonate platform developed in upper Yangtze platform, and Sichuan basin was located in restricted platform (Longwangmiao Formation). In the Middle Cambrian, tidal flat and restricted platform developed in Sichuan basin (Douposi Formation), because of continuous regression. During the Late Cambrian, Sichuan basin was located in carbonate platform again (Xixiangchi Formation). There are three types of sedimentary system in the Cambrian of Sichuan basin: clastic sedimentary system, clastics-carbonate mixed sedimentary system and carbonate sedimentary system. Vertically, the basin shows the evolutionary character of clastic-carbonate sedimentary systems. The three sedimentary systems correspond to three "transgression-regression" cycles of the Cambrian. The transgression in the initial period of the Early Cambrian led to the formation of clastic sedimentary system in the Qiongzhusi Formation of Lower Cambrian. The transgression in the later period of the Early Cambrian led to the formation of clasticcarbonate mixed sedimentary system in the Middle-Lower Cambrian. The transgression in the initial period of the Late Cambrian led to the formation of carbonate sedimentary system in the Xixiangchi Formation of Upper Cambrian. With the end of Late Sinian continental rifting ended, Sichuan basin entered a stable evolutionary stage of the craton basin, while the paleo-land developed in the north and southwest. In Qiongzhusi-Canglangpu period, the basin developed onshore-shelf sedimentary facies from west to east; In Longwangmiao-Xixiangchi period, the basin developed tidal flat-platform-slope sedimentary facies from west to east. [ABSTRACT FROM AUTHOR]

Graphene is a single atom thick crystal composed of carbon atoms. It is the lightest, thinnest, strongest material that conducts heat and electricity well heretofore. In terms of application, by introducing oxygen-containing groups, graphene can be well dispersed in solvents, can be chemically modified and functionalized, or connected with other electroactive substances through covalent bond or non-covalent bond to form composite materials, which is conducive to further processing and promotion. The application of graphene in oilfield chemistry started late, but developed rapidly. Graphene has played an active role in drilling fluid, cementing fluid, fracturing fluid, displacement fluid and other oilfield working fluids. It can enhance the temperature and salt resistance of working fluid and improve the effect of working fluid. In this paper, several directions of graphene applications in oilfield chemistry, such as modified graphene, graphene copolymers and graphene nanoparticles, are reviewed in detail from the synthesis methods, action mechanisms and effects of graphene and its derivatives, and the frontier cases at this stage are given. On the basis of the existing research, suggestions for the development direction of graphene materials in oilfield chemistry are given for a variety of graphene materials, aiming to provide guidance for the application of graphene in oilfield chemistry. [ABSTRACT FROM AUTHOR]

Present drilling fluids for deep water wells have severe degenerative effect on the environment with high operational and disposal costs. Thus, making them less desirable in recent times. Ester synthetic drilling fluid provides a novel environmentally friendly alternative but conventional ester-based drilling fluids exhibit high viscosities in deep-water wells causing excessive equivalent circulating density (ECD) and increased risk of lost circulation owing to narrow mud density window. This study experimentally investigates the critical fluid properties and aerobic biodegradability potentials of two newly developed deep-water synthetic ester drilling fluids namely: iso-propyl caprylate (COIPE) and iso-propyl linolenate (LOIPE) synthetic fluids and their comparison with synthetic-paraffin (SP-SBF) and isomerized-olefin (IOSBF) synthetic hydrocarbon fluids. The esters of iso-propyl caprylate and iso-propyl linolenate were produced from the isolation of ester mixtures that were obtained from the homogeneous catalytic transesterification of coconut and linseed plant oil biomass respectively. The COIPE was isolated from the coconut oil iso-propyl ester mixture by low-pressure fractional distillation technique. While fractional distillation and crystallization were used to isolate the LOIPE ester from the linseed oil iso-propyl ester mixture. Meanwhile, the aerobic biodegradation investigation was conducted by a modified oxygen consumption respirometry technique. The GC-MS analysis of the COIPE and LOIPE showed that the former contains essentially of lower saturated carbon compounds (C8). Whereas the latter contains higher molecular weight and unsaturated carbon compounds (C18+). The COIPE and LOIPE kinematic viscosity values are in good agreement with that of the reference synthetic hydrocarbon fluid samples (SP-SBF and IO-SBF). Although, the COIPE synthetic ester has lower viscosity value owing to the presence of shorter chain and saturated carbon atoms (C8 esters). Similarly, the linolenic oil iso-propyl ester has excellent cold flow characteristics for deep-water well drilling owing to lower values of cloud and pour points as a result of higher concentration of poly-unsaturated linolenic esters. The iso-propyl caprylate and the iso-propyl linolenate ester synthetic fluids are readily biodegradable in the sea water inoculum under aerobic condition. However, the iso-propyl caprylate is inherently biodegradable because its degradation level and that of the reference chemical sample were already above 60% during the 10-day window period. The SP-SBF and the IO-SBF synthetic fluids have lower aerobic biodegradation values because they contain little quantity of poly aromatic hydrocarbons as evident in their GC-MS profiles. Finally, esters and unsaturated synthetic-based fluid are more rapidly biodegradable than paraffinic synthetic fluids and the rate of biodegradation of organic compounds decreases as molecular weight increases. [ABSTRACT FROM AUTHOR]

Shale gas reservoirs are unconventional tight gas reservoirs, in which horizontal wells and hydraulic fracturing are required to achieve commercial development. The fracture networks created by hydraulic fracturing can increase the drainage area extensively to enhance shale gas recovery. However, large volumes of fracturing fluid that is difficult to flow back to the surface and remained in the shale formation, will inevitably lead to damages of the shale formations and limit the effectiveness of stimulation. Supercritical water (SCW) treatment after hydraulic fracturing is a new method to enhance shale gas recovery by using appropriate heat treatment methods to the specific formation to convert the retained fracturing fluid into a supercritical state (at temperatures in excess of 373.946°C and pressures in excess of 22.064 MPa). An experiment was conducted to simulate the reaction between shale and SCW, and the capacity of SCW treatment to enhance the permeability of the shale was evaluated by measuring the response of the shale porosity and permeability on SCW treatment. The experimental results show that the shale porosity and permeability increase by 213.43% and 2198.37%, respectively. The pore structure alteration and permeability enhancement of the shale matrix were determined by analyzing the changes in pore structure and mineral composition after SCW treatment. The mechanisms that affect pore structure and mineral composition include oxidative catalysis decomposition of organic matters and reducing minerals, acid-catalyzed decomposition of carbonate minerals and feldspar minerals, hydrothermal catalysis induced fracture extension and cementation weakening induced fracture extension. SCW treatment converts harm into a benefit by reducing the intrusion of harmful substances into the shale formation, which will broaden the scope and scale of shale formation stimulation. [ABSTRACT FROM AUTHOR]

The paper presents the results of studies on the transformation of the organic matter of siliceous-clayey carbonate rocks of the SemilukskoeMendymsky horizon of the Romashkino oil field in a hydrothermal fluid for an hour (with a water-to-rock ratio of 33) at 340°C and 380°C and pressures of 17 and 20 MPa. As a result of hydrothermal treatment, at 340°C and 17 MPa, based on nitrogen porosimetry and electron microscopy data, transformations of rock-forming minerals in the rock are observed. They lead to an increase in the volume and average diameter of mesopores in it and the formation of micropores, as well, which improve its filtration properties. At the same time, the amount of kerogen in the composition of the organic matter decreases and the yield of the petroleum hydrocarbon extract increases, in which, according to the SARA analysis, the content of asphaltenes increases and the content of resins, aromatic and saturated hydrocarbons decreases. In the composition of aroatic hydrocarbons, the proportion of alkyltrimethylbenzenes and dibenzothiophenes increases, phenanthrene homologues appear, and in the composition of saturated hydrocarbons, the amount of iso-structure alkanes decreases relative to the content of linear alkanes. Raising the temperature and pressure of the hydrothermal fluid to 380°C and 20 MPa increases the degree of kerogen conversion from 12.4% to 23.6%. At the same time, changes occurring in the component composition of petroleum hydrocarbon extracts remains similar to the experiments carried out at 340°C and 17 MPa; the content of naphthalenes decreases, the content of dibenzothiophenes increases and C11-C17, C19-C22 alkyltrimethylbenzenes appear. According to IR spectroscopy, with increasing temperature and pressure of the hydrothermal fluid the intensity of the absorption bands of the aromatic ring, aliphatic fragments, and oxygen-containing groups increases in resins; the structural-group composition of asphaltenes changes little: aromaticity and the content of condensed structures slightly increase. The revealed distinctive features in the composition of organic matter after hydrothermal impact on siliceous-clayey carbonate rocks confirm the concept of staged destruction of kerogen, when large structural heteroatomic blocks (asphaltenes) are split off at the initial stages. Changes occurring in the composition of petroleum hydrocarbon extracts indicate their involvement in the process of hydrothermal transformation of organic matter of siliceous-clayey carmbonate rocks with the predominant reactions of dehydrogenation of naphthenic compounds and oxidative polycondensation of aromatic structures. The data of electron microscopy and nitrogen porosimetry of rocks after hydrothermal exposure at 380°C and 20 MPa indicate a deterioration in their reservoir properties. The most optimal thermobaric conditions of the hydrothermal fluid for the generation of petroleum hydrocarbons from kerogen of siliceous-clayey carbonate deposits of the SemilukskoeMendymsky horizon of the Romashkino field, which improve their reservoir properties, are 340°C and 17 MPa; with implication of hard-to-recover heavy hydrocarbon resources and wellestablished catalytic methods of in-situ conversion. [ABSTRACT FROM AUTHOR]

Soil corrosion and hydrogen embrittlement are the main factors of hydrogen pipeline failure. The gas escapes, diffuses and accumulates in the soil and enters the atmosphere when leak occurs. The mechanism of gas diffusion in buried pipelines is very complicated. Mastering the evolution law of hydrogen leakage diffusion is conducive to quickly locating the leakage point and reducing the loss. The leakage model of the underground hydrogen pipeline is established in this paper. The effect of leakage hole, soil type, pipeline pressure, pipeline diameter on hydrogen leakage diffusion were investigated. The results show that when the hydrogen pipeline leaks, the hydrogen concentration increases with the increase of leakage time, showing a symmetrical distribution trend. With the pipeline pressure increase, hydrogen leakage speed is accelerated, and longitudinal diffusion gradually becomes the dominant direction. As the leakage diameter increases, hydrogen leakage per unit of time increases sharply. Hydrogen diffuses more easily in sandy soil, and its diffusion speed, concentration, and range are higher than that in clay soil. The research content provides a reference and basis for the detection and evaluation of buried hydrogen pipeline leakage. [ABSTRACT FROM AUTHOR]

The development of low-permeability oil and gas resources presents a significant challenge to traditional development methods. To address the problem of "no injection and no production" in low -permeability reservoirs, a novel fracture-injection-production integration technology named fracturing-flooding has been proposed by oilfield sites. This technology combines the advantages of conventional fracturing, water flooding, and chemical flooding, resulting in improved reservoir physical properties, increased injection, replenished energy, and increased oil displacement efficiency. The technology is especially suitable for low-permeability reservoirs that suffer from lack of energy, and strong heterogeneity. Fracturing-flooding technology has shown significant results and broad development prospects in some oilfields in China. This paper analyzes the development status of fracturing-flooding technology from its development history, technical mechanism, technical characteristics, process flow, types of fracturing and oil displacement fluids, and field applications. Physical and numerical simulations of fracturing- flooding technology are also summarized. The results suggest that fracturing-flooding technology is more effective than conventional fracturing, water flooding, and chemical flooding in stimulating lowpermeability tight reservoirs and improving oil recovery. Moreover, it has a high input-output ratio and can be utilized for future reservoir stimulation and transformation. [ABSTRACT FROM AUTHOR]

Fluid production from unconsolidated reservoirs often leads in sand production, which poses a number of issues. Sand deposition in flowlines can result in significant pressure dips, pipe and facility damage, and obstructions that decrease productivity. More research is needed to understand the movement and deposition of sand in oil--water--sand (O--W--S) fluxes. This article focuses on O--W--S flows in a 6-meter-long horizontal pipe with an inner diameter of 0.0381 m. The study looks at the flow behavior of high viscosity oil-water (O--W), wateresand (W--S), and oil--water--sand (O--W--S) flows. Experiments were carried out at 250 psig pressure in a laboratory flow test facility using various heavy synthetic oils (viscosities ranging from 3500 cP to 7500 cP at 25°C) and tap water. The sand concentration varied from 1% to 10%, with an average sand particle diameter of 145 mm and material density of 2630 kg/m³. Water cuts ranged from 0.0 to 1.0. The experimental results revealed a minor change in pressure gradient between (O--W) and (O--W--S) flows. However, increasing the sand concentration in (O--W--S) flow resulted in higher pressure losses. The reduction factor of pressure gradient indicated that the highest decrease in pressure drop occurred at higher superficial oil velocities. Furthermore, a direct relationship was observed between the reduction factor and the decrease in water cut. The results also showed that the minimum required transportation velocity for sand slurry decreased with increasing superficial oil velocity, while the minimum transportation condition increased with higher sand concentration. The comparison between the expected pressure gradient from Bannwart and McKibben et al. and the actual experimental data demonstrated significant accuracy for the oil viscosities and superficial oil velocities used in the study. [ABSTRACT FROM AUTHOR]

Increasing world request for energy has made oil extraction from reservoirs more desirable. Many novel EOR methods have been proposed and utilized for this purpose. Using nanocomposites in chemical flooding is one of these novel methods. In this study, we investigated the impact of six injection solutions on the recovery of light and heavy oil with the presence of two different brines as formation water using a homogenous glass micromodel. All of the injection solutions were based on a 40,000 ppm NaCl synthetic seawater (SSW), one of which was additive free and the others were prepared by dispersing nanocomposite silica-based polyacrylamide (NCSP), nanocomposite alumina-based polyacrylamide (NCAP), the combination of both nanocomposites silica and alumina based on polyacrylamide (NCSAP), surfactant (CTAB) and polyacrylamide (PAM) with a concentration of 1000 ppm as additives. The Stability of nanocomposites was tested against the salinity of the brine and temperature using salinity and DSC tests which were successful. Alongside stability tests, IFT, contact angle and oil recovery measurements were made. Visual results revealed that in addition to the effect of silica and alumina nanocomposite in reducing interfacial tension and wettability alteration, control of mobility ratio caused a major improvement in sweeping efficiency and oil recovery. According to the sweeping behavior of injected fluids, it was found that the main effect of surfactant was wettability alteration, for polyacrylamide was mobility control and for nanocomposites was the reduction of interfacial tension between oil and injected fluid, which was completely analyzed and checked out. Also, NCSAP with 95.83% and 70.33% and CTAB with 84.35% and 91% have the highest light oil recoveries at 250,000 ppm and 180,000 ppm salinity, respectively which is related to the superposition effect of interactions between nanocomposites, solution and oil. Based on our results it can be concluded that the most effective mechanism in oil recovery was IFT reduction which was done by CTAB reduction also by using a polymer-based nanocomposite such as NCSAP and adding the mobility control factor, the oil recovery can be further enhanced. In the case of heavy oil recovery, it can be concluded that the mobility control played a much more effective role when the PAM performed almost similarly to the CTAB and other nanocomposites with a recovery factor of around 17%. In this study, we tried to investigate the effect of different injection solutions and their related mechanisms on oil recovery. [ABSTRACT FROM AUTHOR]

Asphaltene precipitation can result in several production, operational, and transportation problems during oil recovery. If asphaltene precipitates and deposits, it can reduce reservoir permeability, damage wellbore equipment, and plug the pipelines. It is therefore extremely important to evaluate the conditions at which asphaltene precipitation occurs; this is referred to as the asphaltene onset pressure. Asphaltene onset pressure has been measured using many different experimental techniques. There have also been many attempts along the years to predict asphaltene onset pressure using mathematical correlations and models. This research provides an up-to-date comprehensive review of the methods by which asphaltene onset pressure can be measured using laboratory experiments and mathematical models. The research explains the main mechanisms of all the laboratory experiments to measure asphaltene onset pressure under static conditions and how to conduct them and highlights the advantages and limitations of each method. The research also provides a summary of the commonly used mathematical models to quantify asphaltene onset pressure directly and indirectly. [ABSTRACT FROM AUTHOR]

Surface chokes are widely utilized equipment installed on wellheads to control hydrocarbon flow rates. Several correlations have been suggested to model the multiphase flow of oil and gas via surface chokes. However, substantial errors have been reported in empirical fitting models and correlations to estimate hydrocarbon flow because of the reservoir's heterogeneity, anisotropism, variance in reservoir fluid characteristics at diverse subsurface depths, which introduces complexity in production data. Therefore, the estimation of daily oil and gas production rates is still challenging for the petroleum industry. Recently, hybrid data-driven techniques have been reported to be effective for estimation problems in various aspects of the petroleum domain. This paper investigates hybrid ensemble data-driven approaches to forecast multiphase flow rates through the surface choke (viz. stacked generalization and voting architectures), followed by an assessment of the impact of input production control variables. Otherwise, machine learning models are also trained and tested individually on the production data of hydrocarbon wells located in North Sea. Feature engineering has been properly applied to select the most suitable contributing control variables for daily production rate forecasting. This study provides a chronological explanation of the data analytics required for the interpretation of production data. The test results reveal the estimation performance of the stacked generalization architecture has outperformed other significant paradigms considered for production forecasting. [ABSTRACT FROM AUTHOR]

This paper examines the returns and volatility of two distinct types of crude oil: Brent and West Texas Intermediate (WTI). The time series data, collected from the international market, spans from February 1, 2014, to February 1, 2024. It includes 2,537 observations for WTI and 2,542 observations for Brent. The study employs the E-Views software to analyze the secondary data and to investigate the impacts of ARCH and GARCH models at a significant level. The mean reversion of WTI is 0.993582, and Brent crude mean reversion is 0.956194. The results show that WTI has a slower mean reversion than Brent because it is closer to 1. Further half-life model analysis showed that WTI reverted to its mean position after 99 days and Brent after 16 days. This study concludes that WTI is more volatile than Brent crude oil. [ABSTRACT FROM AUTHOR]

We conduct a comparison of three portfolio investment strategies in the US stock market following the implementation of Regulation Fair Disclosure in October 2000. The strategies analyzed are analyst‐recommended, recommendation changes, and momentum portfolios. Across various time periods, company sizes, and industry sectors, the momentum portfolio consistently outperforms the other strategies. Portfolios based on analyst recommendations exhibit poor performance in industries such as consumer staples and materials, which are strongly correlated with oil prices. These industries are susceptible to external demand and supply‐side price shocks that are not adequately captured by analyst recommendations. The findings highlight firstly, the efficacy of the momentum strategy and the limitations of relying solely on analysts' recommendations, particularly in oil‐dependent sectors; and secondly, the varying dynamics and performance of different investment strategies for investors seeking to optimize their investment decisions across different sectors and market conditions. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the possible explanatory effect of geopolitical risks on the oil price changes from February 1986 to December 2019 by employing the nonlinear bivariate Granger causality test and frequency domain Granger causality test based on the geopolitical risk index. The results suggest that there exists a nonlinear causality from geopolitical risks to crude oil prices. Moreover, geopolitical risks have a short-term impact on oil prices, less than 12 months. Actual geopolitical events have a smaller and less lasting impact on oil prices than pure geopolitical risks. [ABSTRACT FROM AUTHOR]

Summary: Predicting carbon and oil prices is recently gaining relevance in the climate change literature. This is due to the fact that conventional energy market analysis and the design of mechanisms for climate change mitigation constitute key variables for artificial carbon markets. Yet, modelling non‐linear effects in time series remains a major challenge for carbon and oil price forecasting. Hence, hybrid models seem to be appealing alternatives for this purpose. This study evaluates the performance of 12 hybrid models, which weigh results from random forest, support vector machine, autoregressive integrated moving average and the non‐linear autoregressive neural network models. The weights are determined by (i) assuming equal weights, (ii) using a neural network to optimise individual weights and (iii) employing deep learning techniques. The findings of our work confirm the salient characteristics of modelling the non‐linear effects of time series and the potential of hybrid models based on neural networks and deep learning in predicting carbon and oil price returns. Furthermore, the best results are obtained from hybrid models that combine machine learning and traditional econometric techniques as inputs, which capture the linear and non‐linear effects of time series. [ABSTRACT FROM AUTHOR]

Exploring the nexus between oil prices and remittances is critical to both remitting and recipient countries. Employing non-linear panel autoregressive distributed lag (NARDL) approach, we examine the relationship for 32 sub-Sahara African countries over the period 1986-2019. The results reveal that: (1) changes in oil prices and remittance inflows are asymmetrically associated only in the short run for the entire sample; (2) when the sample is divided into middle and low-income subgroups, asymmetric effect is confirmed for former subgroup only in the long run, while it is confirmed for latter subgroup only in the short run, (3) in the long run, positive movement in oil prices reduces remittances for the sample and in the middle income subgroup, whereas it increases remittances in the low-income subgroup, (4) Negative oil price movement reduces remittances for the entire sample and the two subgroups; (5) in the short run, a reduction in oil prices increases remittance inflows only for the entire sample and for the low-income subgroup. These results suggest that policymakers in SSA should implement policies that will reduce oil price risks on remittance inflows especially in the long run. [ABSTRACT FROM AUTHOR]