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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 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]

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]

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]

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]

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]

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]

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 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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

We explore the relationship between the returns of 45 dry bulk shipping company stock prices and the main 15 commodities that bulk carriers transport. Using a principal component analysis to reduce the dimensionality of the commodities dataset and a panel methodology, we find that a change in the commodity price principal component would result in a 0.6% change in the returns of the shipping stock prices. Minerals appear to have a stronger impact, as a 1% change in the minerals principal component results in a 1.1% change in the returns. This is mainly due to the fact that minerals account for larger trade volumes in the dry bulk market and they employ mostly bigger vessels, while the price of Brent oil is also an important factor affecting shipping stock prices. [ABSTRACT FROM AUTHOR]

This paper combines the Generalized Autoregressive Conditional Heteroskedasticity-Extreme Value Theory-Value at Risk (GARCH-EVT-VaR) method in conjunction with the Time-Varying Parameter Diebold-Yilmaz (TVP-VAR-DY) model to investigate the contagion of extreme risks between fossil and green energy markets in China. Specifically, the study concentrates on coal, crude oil, and natural gas markets as representative sectors for fossil energy, while green bonds, investments, green power, and associated new energy markets are chosen as representatives for the green energy sector. Our analysis reveals that extreme events can rapidly propagate risks between fossil and green energy markets, particularly during significant shifts in the external environment. Notably, green energy markets exhibit greater susceptibility to severe risks compared to their fossil energy counterparts, indicative of their instability and immaturity. Moreover, the analysis highlights the green bond market's heightened sensitivity to extreme risks, with green investments playing a pivotal role in propagating such risks throughout the system. These insights underscore the intricate dynamics of risk contagion between fossil and green energy markets, emphasizing the need for comprehensive risk management strategies in both sectors. [ABSTRACT FROM AUTHOR]

The recent energy crisis has renewed interest in forecasting crude oil prices. This paper focuses on identifying the main drivers determining the evolution of crude oil prices and proposes a statistical learning forecasting algorithm based on regression analysis that can be used to generate future oil price scenarios. A combination of a generalized additive model with a linear transfer function with ARIMA noise is used to capture the existence of combinations of non-linear and linear relationships between selected input variables and the crude oil price. The results demonstrate that the physical market balance or fundamental is the most important metric in explaining the evolution of oil prices. The effect of the trading activity and volatility variables are significant under abnormal market conditions. We show that forecast accuracy under the proposed model supersedes benchmark specifications, including the futures prices and analysts' forecasts. Four oil price scenarios are considered for expository purposes. [ABSTRACT FROM AUTHOR]

This article explores how declining oil revenue might shape the amount of international conflict initiated by major oil producers (petrostates). We analyze four potential mechanisms through which variation in oil prices could affect petrostate conflict initiation: emboldenment, battling over a smaller market, signaling strength, and diversionary conflict. The empirical findings suggest that higher oil prices are associated with lower rates of petrostate conflict initiation. From one standard deviation below the mean oil price to one standard deviation above it, the predicted number of militarized interstate disputes declines twofold, from.025 [95% CI:.016–.034] per petrostate per year to.012 [.007–.016]. Moreover, the evidence suggests that petrostates are more likely to target other petrostates when oil prices are low. This suggests that the energy transition may not be a boon for international peace among petrostates, and for a time, it may even prove to be the opposite. [ABSTRACT FROM AUTHOR]

Precisely forecasting the price of crude oil is challenging due to its fundamental properties of nonlinearity, volatility, and stochasticity. This paper introduces a novel hybrid model, namely, the KV-MFSCBA-G model, within the decomposition–integration paradigm. It combines the mixed-frequency convolutional neural network–bidirectional long short-term memory network-attention mechanism (MFCBA) and generalized autoregressive conditional heteroskedasticity (GARCH) models. The MFCBA and GARCH models are employed to respectively forecast the low-frequency and high-frequency components decomposed through variational mode decomposition optimized by Kullback–Leibler divergence (KL-VMD). The classification of these components is performed using the fuzzy entropy (FE) algorithm. Therefore, this model can fully exploit the advantages of deep learning networks in fitting nonlinearities and traditional econometric models in capturing volatilities. Furthermore, the intelligent optimization algorithm and the low-frequency economic variable are introduced to improve forecasting performance. Specifically, the sparrow search algorithm (SSA) is employed to determine the optimal parameter combination of the MFCBA model, which is incorporated with monthly global economic conditions (GECON) data. The empirical findings of West Texas Intermediate (WTI) and Brent crude oil indicate that the proposed approach outperforms other models in evaluation indicators and statistical tests and has good robustness. This model can assist investors and market regulators in making decisions. [ABSTRACT FROM AUTHOR]

This paper proposes new wild bootstrap GLS-detrended unit root tests in the exponential smooth transition autoregressive framework, which could handle both nonlinear movement and time-varying volatility for financial time series. We derive the asymptotic distributions of the proposed tests and explore the finite sample properties. Simulation results show that the size and power performance of the proposed tests are better than the conventional tests. An application on crude oil and copper prices further underlines our test's priority, and our proposed tests do not reject the unit root null of crude oil and copper prices. [ABSTRACT FROM AUTHOR]

Purpose: This study evaluates the impact of the water management policies of energy companies on their volatility interactions with energy commodities. Design/methodology: We tested for volatility transmissions between 66 energy funds and fossil-fuel commodities. After identifying possible integrations, we investigated whether water management policies, after controlling for other fund characteristics, impact the probability of integration. Results: Our findings indicate strong volatility transmission from oil prices to energy funds. However, a reverse of this information flow was not observed. From the perspective of natural gas, we found strong bi-directional integration with energy funds. When we analyzed the influence of fund characteristics on the previously established integrations, water management policies do not impact the probability of the integration of oil. However, these policies are shown to have a significant influence on integration with the natural gas market. Originality/value: While there are multiple studies that show the integration between energy companies and corresponding commodities, according to our knowledge, this is the first study that evaluates the significance of water management policies with respect to volatility integration. This study highlights the importance of water-related policies with respect to the susceptibility of energy firms to volatility contagion from the natural gas market. [ABSTRACT FROM AUTHOR]

This study analyzed the heterogeneity and nonlinear effects of financial development, governance, real exchange rate and oil price on tourism in OIC countries. We used annual panel data of 50 Islamic countries from 1996 to 2021 and apply panel quantile regression as well as fixed and random effect technique. The empirical results illustrated that across quantiles, financial development contributed to the tourism performance in all models under review. We also observed that the impact of governance indicators on tourism demand were positive and statistically significant. The estimated asymmetric model affirmed the positive effect with the weak significant power of oil price on tourism at across quantiles (except 10th), while exchange rate was negatively associated with tourism demand. Furthermore, the results of slope equality test indicated that, in many models, the relationship between tourism demand and explanatory variables was clearly heterogeneous. Finally, the asymmetric effects at different quantiles for more coefficients based on the quantile plot were confirmed. [ABSTRACT FROM AUTHOR]

This paper examines the effects of remittances on output for Lebanon, a case with a unique setting: remittances to Lebanon are primarily from workers located in oil-producing Gulf States and thus influenced by oil prices. This setting enables us to estimate a structural VAR model using the price of oil as an instrument. We estimate the model with and without the instrument and compare the impulse response of remittances. Our key results are as follows: without the instrument, we find that a one-standard deviation shock in remittances increases industrial production by about 0.10% to 0.20%, a small and weakly estimated effect. In the instrumental variable setting, the magnitude increases by a factor of at least 5.8: the increase in output ranges from 0.72% to 1.11%. Our results imply that remittance effects on output computed using standard VARs are likely underestimated. Moreover, they suggest that the adoption of policies that facilitate remittance flows should be encouraged as they likely stimulate economic growth by more than previously detected. [ABSTRACT FROM AUTHOR]

During the twentieth and twenty-first centuries, the oil industry has been pivotal in influencing all countries' geopolitical, economic, and human development strategies. Until recently, the debate was about peak oil and what would happen after oil finished. However, due to technological advances and hydraulic fracturing, shale oil formations have become economically viable due to the United States' desire to achieve energy security to make a qualitative shift in the oil industry and the geopolitics of oil. Therefore, this paper deals with an economic model that illustrates the impact of oil price fluctuations to the shale oil and gas companies by analyzing the main determinants of continuity of shale oil and gas companies in production if global oil prices decline or rise. In addition, the study will investigate the effects of OPEC+ policy and Covid-19 on the future of shale oil industry. The study will discuss some future scenarios for global energy trends and predict what the shale industry will look like in the future. The study concluded the shale industry faces an internal destructive process (within the industry itself) and external (Renewable energy, OPEC and Covid-19). The stability of oil prices is a critical factor that promotes the shale industry's recovery. However, shale industry is expected to continue with low productivity growth rates and continuing government support for it. [ABSTRACT FROM AUTHOR]