Oil Transportation Research Articles

COMPARISON OF TRIETHANOLAMINE (TEA) AND ETHYL VINYL ACETATE (EVA) AS FLOW IMPROVERS OF CRUDE OIL.

This research presents a study on the comparative analysis of the efficiencies of triethanolamine (TEA) and ethylvinylacetate (EVA) as flow improvers for crude oil transport. Varied concentrations (by volume percentage) of 0%, 0.025%, 0.05%, 0.1%, 0.2%, 0.4% and 1% of triethanolamine were introduced into separate but same quantities of crude oil and stirred. The viscosity and pour points were monitored at varied temperatures (30oC, 40oC, 50oC, 60oC, 70oC) to ascertain optimum concentration and temperature of best flow improvement with that of zero concentration serving as control. Similar thing was done with EVA at same conditions. TEA and EVA both drastically dropped viscosity of the crude close to what temperature alone could offer but rose immediately after the minimum concentration of 0.025% with EVA and TEA on further diluent addition. TEA viscosity rose steeply and later tended towards a constant viscosity. This was also the trend with EVA, but it rose gently unlike TEA at increased concentration of the additive. Using room temperature (30oC) for the two additives (TEA and EVA) as reference point at 0.025% concentration of each to the same volume of crude oil, TEA gave a minimum viscosity of 0.1124centistokes and EVA gave 0.1184centistokes. Similar trend was also observed at the apex temperature (70oC) at 0.025% concentration (TEA viscosity = 0.0997centistokes and EVA = 0.1015centistokes). In the end, TEA was observed to be better than EVA although EVA has its own relative advantage especially at higher temperatures and concentrations. Higher temperature from 40oC and above degraded TEA but not EVA, as a result was inhibitory to the reverse rise in viscosity in TEA. Hence, having established TEA and EVA as good drag reducing agents, the additives if used in the proper calculated quantities will act optimally in improving crude oil transport. Outcome of this research will find application in our oil and gas industry where challenges in crude oil transport has been overwhelming as a result of wax formations in the pipelines.

Aggregation behaviour of paraffin molecules with different branched distributions during crude oil gelling: A molecular dynamics study

Revealing the microdynamic mechanism and thermodynamic properties of the gelling process of waxy crude oil at the microscale plays an important role in ensuring the safe production and transport of waxy crude oil. However, few studies have dealt with the influence of paraffin molecular branching position on the gelling process. The focus of this study is to clarify the influence of branching distribution on molecular aggregation through molecular simulation, so as to further improve the mechanistic study of the gelling process of waxy crude oil. A variety of molecular models of crude oil systems containing paraffin molecules with different distributions of branched chains, asphaltenes, and light oils are developed to analyse the molecular aggregation and wax precipitation characteristics during the gelling process.The results show that the paraffin molecular chain morphology gradually from stretching to curling and the molecules gradually from dispersing to aggregating during the temperature drop process. From the van der Waals force analysis, it is concluded that isomeric alkanes with a close branching distribution form the weakest gelling structures. In addition, the phase transition temperature difference between n-alkanes and isoalkanes is large about 9 K, but the phase transition temperature difference between the two isoalkanes with different distributions of branched chains is small only about 3 K. This indicates that for alkanes with the same molecular formula, the length of the main carbon chain is a dominant factor in influencing the aggregation of the molecules and the gelling properties of the crude oil system. Under high temperature conditions, isomeric alkanes have the best mobility and are most sensitive to temperature. The results of the study can provide help for the mechanism of the gelling process of waxy crude oil to ensure the safety of the pipeline transmission process, and provide theoretical guidance for the production of depressants and catalysts.

An interesting phase transition in polyamide 6/nitrile rubber blend induced by temperature and pressure and its effect on tribological performance

AbstractThe preparation of high‐performance rubber‐plastic blending elastomers has always been a research hotspot in the field of petroleum equipment. The two‐phase separation structure of the blend determines the macroscopic properties of the materials. It is of great significance to deeply explore the influence of processing technology on the two‐phase separation structure. In this paper, polyamide 6 (PA6)/nitrile rubber blends were prepared via the melt–compounding method. To meet the requirements of oil production and oil transport equipment, we investigated systematically the mechanical properties of the specimens exposed to different environments. The oil resistance and high‐temperature resistance of the blends were enhanced considerably with the addition of PA6. The temperature and pressure fields induced a novel transition from particle into fibrous phase based on Ostwald's ripening. However, this brand new transformation showed no benefits to the improvement of the frictional performance. Meanwhile, the relationship between aggregate structure and mechanical performance was demonstrated from the aspects of crystallization behavior and phase morphology.

Stretch-Controlled Branch Shape Microstructures for Switchable Unidirectional Self-Driven Spreading of Oil Droplets.

Unidirectional transport of liquids has attracted the attention of researchers in recent years for its wide application foreground. However, it is still a challenge to control the spreading of liquid, especially for oils with relatively high viscosity. In this paper, a flexible surface textured with branch-shaped microstructures is proposed. These asymmetric microstructures exhibit excellent unidirectional spreading behaviors for various oils. By suitably stretching the flexible surface to different stretch ratios, the spreading length of the oil droplets can be controlled. Moreover, the ongoing forward spreading of oil droplets can be suspended dynamically when the surface is stretched to 40%. Corresponding mechanism analysis demonstrates that surface stretching can narrow and close the microvalves between adjacent branches, which restrain the flow of the precursor film and the primary droplet. The switchable unidirectional spreading behavior enables the surface with such microstructures to be used for oil transportation, oil-water separation, and controllable lubrication.

Fabrication of superamphiphobic micro-reentrant structures by inverted electrochemical deposition

Due to excellent oil resistance and shortened liquid-solid contact time, superamphiphobic surfaces have promising application prospects in oil transportation, and petroleum pollution control. Although superamphiphobic surfaces have been constructed on various substrates, there is still a lack of high-efficient methods for fabricating micro-reentrant structures on engineering metal substrates. This paper proposes a new method combining laser processing and inverted electrochemical deposition techniques to achieve high-efficient and large-scale fabrication of superamphiphobic surfaces on copper substrates. Firstly, micropillar array structures are constructed by laser processing, and the structures exhibit excellent superhydrophobicity after low surface energy modification. Then, inverted electrochemical deposition is performed after polishing the top of the array, and local angle of the gas/liquid interface can be controlled by adjusting the distance between the top of the micropillar and the electrolyte level, thus regulating micro-morphology of the roof structure. The influences of electrochemical deposition parameters on characteristics of the micro-reentrant structures are systematically investigated. Finally, superamphiphobic micro-reentrant structures (roof diameter > 190 μm, micropillar spacing <250 μm) with water and oil contact angles exceeding 150° are prepared after lowering the surface energy of the deposited structures. After anti-fouling, blowing, ultrasonic vibration, and tape adhesion tests, the prepared superamphiphobic micro-reentrant structures maintained good water and oil repellency, showing excellent chemical stability and durability. The research may provide a simple, efficient, and low-cost method for high-efficient constructing superamphiphobic surfaces on engineering metal substrates, enriching the fabrication techniques of micro-reentrant structures and facilitating their practical applications.

Fleet deployment with time-chartered and voyage-chartered tankers for a refined oil shipping company

Fleet deployment with time-chartered and voyage-chartered tankers for a refined oil shipping company

Experimental study on the influence of the riser on the gas-liquid flow in the horizontal pipeline of the offshore pipeline-riser system

The study of gas-liquid interface evolution and pressure fluctuation mechanism in the pipeline-riser system is the key to ensuring the safety of oil and gas transportation. This paper investigates the influence of the riser on the gas-liquid interface in the system with a 1657 m pipeline and risers of 16 m, 22 m, and 29 m. In severe slugging, the differential pressure in the horizontal pipeline exhibits a low-frequency large-amplitude fluctuation consistent with those in the riser. During the gas blowdown of the riser, the pressure fluctuation breaks the force equilibrium of the gas-liquid interface and induces numerous liquid slugs in the horizontal pipeline. A strong correlation is found between the differential pressure in the riser and the slug velocity in the horizontal pipeline by the Spearman Rank coefficient. The correlations between the slug velocity and the gas volume fraction and the void fraction under different riser heights are established, and the errors are 15% and 10%, respectively. The linear relationship between the Strouhal number of liquid slugs and the Lockhart-Martinelli parameter is constructed during the gas blowdown.

Khartoum War's echoes in oil and energy sectors: Economic and environmental implications for Sudan and South Sudan

The energy sector is a main driver of African growth, particularly in regions with geopolitical conflicts like Sudan and South Sudan. The oil and gas industry notably influences these regions' economy, politics, humanitarian situation, and social stability. This study seeks to investigate how the Khartoum War affected the energy sector of both Sudan and South Sudan, particularly looking at the disruptions caused by recent conflicts and their impact on oil production, economic stability, and environmental conditions. The study employs a multi-disciplinary approach, utilising different sources such as regional legal agreements, government reports, academic articles, and press releases from international organisations. The key methodology includes qualitative analysis of several documents and quantitative assessment of production data and economic reports. The study's key findings show a significant decline in oil production and transportation due to the shutdown of key oilfields and pipelines, intensifying economic and humanitarian crises. Additionally, the damage to oil infrastructure has presented serious environmental risks, highlighting the delicate balance between resource management and regional stability. In conclusion, the study's findings underscore the intense impact of the Khartoum War on the energy sector of Sudan and South Sudan, and the urgent need for policy recommendations to mitigate these effects and foster sustainable development.

Analysis and optimization design of internal pressure resistance of flexible composite pipe

Flexible composite pipes have the advantages of light weight, corrosion resistance, scale resistance, and low cost compared to carbon steel pipes, and have attracted much attention in the application of onshore oil and gas gathering and transportation systems. Understanding the relationship between the pressure-bearing mechanical properties of composite pipes and their structural characteristics is crucial for guiding their process application. To investigate the mechanical behavior of flexible composite pipes under internal pressure loads, discrete and combined finite element models were established to analyze the stress-strain characteristics of flexible composite pipes. The bursting strength was predicted, and the influence of winding angle and number of reinforcement layers on the pressure-bearing capacity of flexible composite pipes was revealed. The applicability of the two models in the analysis of internal pressure resistance of flexible composite pipes was evaluated using whole pipe strain testing and instantaneous hydrostatic burst experiments. The results showed that the reinforcement layer is the main pressure-bearing layer of flexible composite pipes, and the innermost reinforcement layer bears the highest pressure. The pressure-bearing capacity of flexible composite pipes significantly increases when the winding angle is greater than 53°, and the increase in pressure-bearing capacity slows down when the number of reinforcement layers exceeds 3. Under the combination model, the strain and bursting strength of flexible composite pipes were closer to the experimental results. The study clearly defines the stress-strain characteristics of flexible composite pipes under internal pressure load and the impact of process parameters, providing a basis for the optimization design of single well oil transmission pipelines in Xinjiang oilfield.

Economic analysis of transportation of crude oil of Upper Assam Basin through pipeline

Economic analysis of transportation of crude oil of Upper Assam Basin through pipeline

Unveiling Turbulent Flow Dynamics in Blind-Tee Pipelines: Enhancing Fluid Mixing in Subsea Pipeline Systems

Blind tees, as important junctions, are widely used in offshore oil and gas transportation systems to improve mixing flow conditions and measurement accuracies in curved pipes. Despite the significance of blind tees, their unsteady flow characteristics and mixing mechanisms in turbulent flow regimes are not clearly established. Therefore, in this study, Unsteady Reynolds-Averaged Navier–Stokes (URANS) simulations, coupled with Explicit Algebraic Reynolds Stress Model (EARSM), are employed to explore the complex turbulent flow characteristics within blind-tee pipes. Firstly, the statistical flow features are investigated based on the time-averaged results, and the swirl dissipation analysis reveals an intense dissipative process occurring within blind tees, surpassing conventional elbows in swirling intensity. Then, the instantaneous flow characteristics are investigated through time and frequency domain analysis, uncovering the oscillatory patterns and elucidating the mechanisms behind unsteady secondary flow motions. In a 2D-length blind tee, a nondimensional dominant frequency of oscillation (Stbt = 0.0361) is identified, highlighting the significant correlation between dominant frequencies inside and downstream of the plugged section, which emphasizes the critical role of the plugged structure in these unsteady motions. Finally, a power spectra analysis is conducted to explore the influence of blind-tee structures, indicating that the blind-tee length of lbt = 2D enhances the flow-mixing conditions by amplifying the oscillation intensities of secondary flow motions.

Tailoring asymmetric wettability of Janus nanofiber membranes for directional oil transport and oil capture from oil/water mixtures and oil-in-water emulsions

The separation of oil from oil-in-water emulsions is crucial for the recycling of valuable resources. Janus membranes, characterized by their asymmetric configuration, have shown promise in capturing oil from these emulsions due to their ability to efficiently catch micro-size oil droplets with competitive flux rates, minimal energy costs, and fouling-free operations. This study explored the impact of asymmetric wettability on the oil capture capabilities of Janus nanofiber membranes (JNMs). The wettability of the JNMs’ skin layer was modified from oleophilic, with an oil contact angle (OCA) of ∼0°, to oleophobic, with an OCA of ∼142.7°. This adjustment significantly influenced the oil capture process. The oleophobic skin layer acted as a barrier, reducing oil permeation flux from the feed side. However, this same repellent effect facilitated the directional transport of oil once it breached the skin layer. Interestingly, this led to divergent outcomes in the JNMs’ ability to capture oil from oil/water mixture versus oil-in-water emulsion, a distinction not reported in previous studies. These findings are expected to contribute to the enhancement of Janus membranes, optimizing them for more efficient oil recovery from both oil/water mixture and oil-in-water emulsion.

Regional Assessment of Groundwater Contamination Risk from Crude Oil Spillages in the Niger Delta: A Novel Application of the Source-Pathway-Receptor Model

AbstractOnshore oil spills are known for their disastrous environmental impacts and potential to cause lasting damage to underlying groundwater. The Niger Delta is particularly vulnerable to widespread spillages linked to extensive oil exploration, transportation, and theft-related incidents. This research employed a geospatial approach in formulating risk equations, based on the source-pathway-receptor (S-P-R) model using multiple openly available data sets, to assess groundwater contamination risk in the Niger Delta Region (NDR), Nigeria. To develop the overall risk equation, the study combined fourteen thematic data layers including the volume of oil spilled, type of spill, slope, elevation, proximity to spill site, pipeline, oil wells and streams, drainage density, mean annual precipitation and population density. These layers were integrated into source potency, pathway transmissivity, and receptor susceptibility. The NDR was systematically categorized into low, moderate, and high groundwater risk zones. The delineation revealed that high-risk zones predominantly span the central areas, extending from southeast to northwest, effectively encircled by regions of low to medium risk located in both the northern and southern extents of the delta. The efficacy of the risk model was corroborated by existing knowledge. Moderate to high-risk zones were found to be in about 16% of the NDR, revealing previously unknown areas of risk. This spatial configuration underscores a significant gradient in contamination risk across the NDR, with the central corridor emerging as a critical focus for groundwater protection and remediation efforts. In line with UN Sustainable Development Goal (SDG) #6, this study recommends targeted strategies to ensure clean water provision in these identified high-risk areas. By leveraging the S-P-R model within this complex and sensitive ecological area, this research both advances environmental risk assessment and sets a precedent for future large-scale environmental risk assessments utilizing open-source data.

Maximum pitting corrosion depth prediction of buried pipeline based on theory-guided machine learning

Buried pipelines are crucial for the transportation of oil and natural gas resources. However, pipeline failure accidents have frequently occurred due to corrosion. Therefore, an accurate corrosion depth prediction model is necessary for the reliable supply of energy. In this paper, a theory-guided machine learning (ML) model is developed for maximum pitting corrosion depth prediction, the engineering theory and domain knowledge are integrated into feature space to improve the model interpretability. Firstly, several new feature variables are constructed based on the interactions between independent variables. Then, feature importance of all feature variables is obtained using random forest (RF). A hybrid multi-objective grey wolf optimization (HMOGWO) is proposed to optimize the hyper-parameters of RF model, considering feature number, prediction accuracy, and stability simultaneously. Finally, a comprehensive pitting corrosion dataset is utilized for performance evaluation. The results indicate that the proposed theory-guided model can achieve high prediction accuracy and stability, the optimal feature subset can be determined using multi-objective optimization method simultaneously, which solves the problems of model interpretability and feature selection for traditional ML models with the single-objective optimizer. This study is of great significance to the transportation safety of buried pipelines.

Localization for Dual Partial Discharge Sources in Transformer Oil Using Pressure-Balanced Fiber-Optic Ultrasonic Sensor Array.

The power transformer is one of the most crucial pieces of high-voltage equipment in the power system, and its stable operation is crucial to the reliability of power transmission. Partial discharge (PD) is a key factor leading to the degradation and failure of the insulation performance of power transformers. Therefore, online monitoring of partial discharge can not only obtain real-time information on the operating status of the equipment but also effectively predict the remaining service life of the transformer. Meanwhile, accurate localization of partial discharge sources can assist maintenance personnel in developing more precise and efficient maintenance plans, ensuring the stable operation of the power system. Dual partial discharge sources in transformer oil represent a more complex fault type, and piezoelectric transducers installed outside the transformer oil tank often fail to accurately capture such discharge waveforms. Additionally, the sensitivity of the built-in F-P sensors can decrease when installed deep within the oil tank due to the influence of oil pressure on its sensing diaphragm, resulting in an inability to accurately detect dual partial discharge sources in transformer oil. To address the impact of oil pressure on sensor sensitivity and achieve the detection of dual partial discharge sources under high-voltage conditions in transformers, this paper proposes an optical fiber ultrasonic sensor with a pressure-balancing structure. This sensor can adapt to changes in oil pressure environments inside transformers, has strong electromagnetic interference resistance, and can be installed deep within the oil tank to detect dual partial discharge sources. In this study, a dual PD detection system based on this sensor array is developed, employing a cross-positioning algorithm to achieve detection and localization of dual partial discharge sources in transformer oil. When applied to a 35 kV single-phase transformer for dual partial discharge source detection in different regions, the sensor array exhibits good sensitivity under high oil pressure conditions, enabling the detection and localization of dual partial discharge sources in oil and winding interturn without obstruction. For fault regions with obstructions, such as within the oil channel of the transformer winding, the sensor exhibits the capability to detect the discharge waveform stemming from dual partial discharge sources. Overall, the sensor demonstrates good sensitivity and directional clarity, providing effective detection of dual PD sources generated inside transformers.

Data collection framework for enhanced carbon intensity indicator (CII) in the oil tankers

AbstractThe International Maritime Organization (IMO) aims to reduce greenhouse gas (GHG) emissions by 40% by 2030 compared with 2008. The carbon intensity indicator (CII) calculates the annual reduction factor required to continuously improve a ship's operational carbon intensity at a specific rating level. Verification and documentation of the achieved annual operational CII against the prescribed target are necessary to establish the operational carbon intensity rating. This study focuses on the intricate process of data collection for CII within the oil shipping industry, targeting engineering departments and shipboard management teams. Against the backdrop of the industry's substantial carbon dioxide emissions, the IMO has mandated the calculation of CII values for ships exceeding 5000 gross tons to promote sustainability and reduce environmental impact. We have collected emission data of 20 oil tankers over a period of 2 years using our ship maintenance and operating system (SMOS) and analyzed the data to compare the CII ratings. Our results indicate that a staggering ~63% of the vessels had the lowest CII rating of category E. It is therefore crucial to properly collect, organize, and evaluate data for CII calculation and take necessary measures to improve rating. This paper provides a deeper insight into the evolving CII calculation methodology, emphasizing the incorporation of correction factors and exclusions, and delineates the essential data collection practices needed to facilitate accurate CII calculations.

CO2-switchable multi-headgroup surfactant for oil-in-dispersion emulsions with a reusable aqueous phase

Surfactants are widely utilized in various industries, but their amphiphilic nature poses an obstacle to the complete recycling of them from water or oil phases. It is a challenge to design a surfactant that has both good emulsification performance and aqueous-phase recyclable properties. In this paper, we report a novel aqueous-phase recyclable surfactant with multi-headgroups (C3H7-NH (C10COONa)2, di-UAPAba). Di-UAPAba can stabilize oil-in-water emulsions alone at pH ≥ 9 (≥0.3 mM), exhibiting excellent emulsification ability. After adding a trace amount of silica nanoparticles, CO2 switchable oil-in-dispersion emulsions were formed by di-UAPAba at extremely low concentrations (0.01 mM). Reversible demulsification/emulsification was achieved upon CO2/N2 trigger. Moreover, di-UAPAba can be converted into zwitterionic di-UAPAza by bubbling CO2, which entirely enters the aqueous phase with no surfactant residual in the oil phase. Consequently, the emulsions were reformed after di-UAPAba was completely recovered from the aqueous phase. The interfacial behavior of the surfactant and its aqueous recyclable mechanism was analyzed by molecular dynamics simulation. This study introduces a new type of aqueous-recyclable surfactants that can be beneficial in temporary emulsions for oil-soluble products where demulsification is necessary, such as in crude oil production, oil transportation, and multi-phase catalysis.

The Mechanism of Air Blocking in the Impeller of Multiphase Pump

The exploitation and transportation of deep-sea and remote oil and gas fields have risen to become important components of national energy strategies. The gas–liquid separation and gas blocking caused by the large density difference between the gas and liquid phases are the primary influencing factors for the safe and reliable operation of gas–liquid mixed transportation pump systems. This paper takes the independently designed single-stage helical axial-flow mixed transportation pump compression unit as the research object. Through numerical simulation, the internal flow of the mixed transportation pump is numerically calculated to study the aggregation and conglomeration of small gas clusters in the flow passage hub caused by gas–liquid phase separation, influenced by the shear flow of phase separation, forming axial vortices at the outlet where gas clusters gather in the flow passage. The work performed by the impeller on the gas clusters is insufficient to overcome the adverse pressure gradient formed at the outlet of the flow passage due to the gathering of the liquid phase in adjacent flow passages, resulting in the phenomenon of gas blocking, with vortex gas clusters lingering near the hub wall of the flow passage.

Superamphiphobic coating prepared via a two-step spray method: An effective coating for reducing VOCs emission from crude oil tank

In the petrochemical industry, crude oil adhesion in storage tanks leads to volatilization of volatile organic compounds (VOCs), causing environmental harm and economic losses. Superamphiphobic coatings show promise in addressing this issue, but current options face challenges like complexity, limited durability, and poor corrosion resistance. This work introduces a durable and corrosion-resistant superamphiphobic coating on Q235 carbon steel using the "paint + adhesives" two-step spray method. The first layer comprises polytetrafluoroethylene (PTFE) and epoxy resin (E-44), while the second layer consists of fluorine modified silica nanoparticles (F-SiO2). The numerous and homogeneously dispersed fluorine on the coating imparts excellent liquid-repelling properties for both water and crude oil, with a water contact angle of 164.1 ± 2.4° and a sliding angle of 1.1 ± 0.1°, as well as a crude oil contact angle of 172.1 ± 0.9° and a sliding angle of 2.5 ± 0.5°. Systematic stability tests confirm the coating's mechanical and chemical stability, suggesting its potential in practical applications. Importantly, a crude oil tank with our superamphiphobic coating can reduce non-methane hydrocarbon (NMHC) volatilization by 77.4 % ± 7.8 % compared to an uncoated tank. This research provides a superamphiphobic coating to reduce crude oil loss and VOC volatilization in petrochemical enterprises, showing significant contribution to environmental sustainability.

Insights into water-lubricated transport of heavy and extra-heavy oils: Application of CFD, RSM, and metaheuristic optimized machine learning models

With diminishing light crude oil reserves, the focus shifts to heavy and extra-heavy crude oil, posing challenges with high viscosity impeding flow. Water-lubricated technology addresses this issue in oil transmission lines. This study introduces a novel method integrating response surface methodology (RSM), computational fluid dynamics (CFD), and optimized machine learning (ML) models to analyze pipeline pressure gradients (PG) in oil–water two-phase flows downstream of T-junctions. The present study uses the D-optimal technique for simulation design to optimize CFD computational demands efficiently. This study breaks new ground by proposing a framework that leverages support vector machines (SVMs). The proposed framework incorporates metaheuristic optimization algorithms (genetic algorithm (GA) and particle swarm optimization (PSO)) to achieve superior PG prediction accuracy. The optimized ML models outperformed RSM models for predicting PG. Results indicated that oil-to-water viscosity ratio and oil inlet velocity significantly affect PG, followed by water inlet velocity and surface tension between phases. In contrast, the oil-to-water density ratio, oil entry angle at the T-junction, and wall contact angle have minimal impact. Furthermore, statistical metrics and visual comparison tools identified the PSO-optimized SVM model based on linear kernel function as the most effective (MAPE = 13.2 % and R = 0.9949). The hybrid methodology presented in this research holds significant promise for optimizing heavy oil transfer efficiency in applications involving water-lubricated technologies.