Submarine Oil Research Articles

Long-range temperature sensing based on forward Brillouin scattering in highly nonlinear fiber

We propose and experimentally implement a long-range forward Brillouin scattering (FBS) temperature sensor, in which a 25-m highly nonlinear fiber (HNLF) is included in a Sagnac ring and is employed as the main sensing unit, and a 40-km standard single-mode fiber (SMF) is used as the transmission channel to connect the main sensing unit to the data processing center. The approach for quickly acquiring an optimal R0, m mode spectrum is presented. After taking into account the signal-to-noise ratio, sensitivity, and Lorentzian spectral shape, the R0, 17 mode was selected to perform temperature sensing. The frequency shift of the long-range and local FBS sensing demonstrates a linear correlation with the temperature change from 30 ℃ to 60 ℃, with respective frequency shift-temperature coefficients of 73.1 kHz/℃ and 73.4 kHz/℃. Impact of the length of the SMF as the main sensing unit and the SMF as the transmission channel on the FBS gain spectrum has also been discussed, respectively. The proposed long-range FBS scheme is expected to find applications in the investigation of submarine oil and gas pipelines, as well as temperature gradients in underwater and mountainous environments.

Application of Improved Support Vector Machine in Predicting Failure Pressure of Oil and Gas Pipelines with Internal Corrosion Defects

In this study, the failure pressure of submarine oil and gas pipelines was predicted by using five commonly used machine learning models and derivative models. Firstly, an efficient local time-intensive finite element algorithm is constructed and used to generate a machine learning database. Secondly, in order to improve the accuracy of machine learning algorithm, the frontier optimization algorithm is improved to form a new predictive regression model IAEO-SVM model. To compare the accuracy of commonly used machine learning models and IAEO-SVM models, a comprehensive evaluation standard consisting of k-fold cross-validation and three statistical indicators was used. Finally, the influence of seawater depth and geometric factors of corrosion defects on the blasting pressure of submarine oil and gas pipelines was comprehensively analyzed through the high-dimensional surface built by the IAEO-SVM model. The IAEO-SVM model shows superior stability and accuracy compared to the comparison model, as demonstrated by its MSE’ of 0.0482, R2’ of 0.9982, MAE’ of 0.1295, and SD of 0.2198. The high-dimensional surface obtained through inversion shows a linear relationship between seawater depth and failure pressure. Meanwhile, the width of corrosion defects has a significant impact on failure pressure, accounting for up to 23% and thus cannot be overlooked.

Model analysis of flow-induced vibration (LIV) in submarine oil and gas pipeline

Abstract In order to realistically simulate the flow-induced vibration of submarine oil and gas pipelines, this paper assembles a gas-liquid two-phase flow vibration device, develops a detailed and comprehensive experimental procedure, and sets the flow aperture, flow pressure, flow depth, flow direction, and gas-liquid phase apparent flow rate and other variables. According to the different types of pipelines, the multiphase flow-induced vibration of submarine oil and gas pipelines can be categorized into straight pipe vibration and elbow pipe vibration, and combined with the theoretical knowledge of fluid dynamics and the equations of motion to construct a multiphase flow-induced vibration model of submarine oil and gas pipelines and discuss the vibration mechanism of submarine oil and gas pipelines in two-phase liquid flow. Combined with the corresponding experimental parameters, the vibration phenomenon induced by gas-liquid two-phase flow in submarine oil and gas pipelines is experimentally analyzed. It is analyzed that the first-order intrinsic frequency of the submarine oil and gas pipeline is kept at 23.2 Hz when the value of the Reynolds number of the in-pipe flow ranges from 2.53 × 104 to 1.08 × 107. The first-order intrinsic frequency of the submarine oil and gas pipeline monotonically decreases with the increase of the Reynolds number of the in-pipe flow. In addition, when Ul=0.4m/s, the average standard deviation of the data is only 1.114m/s² with the rise of Ug, indicating that the vibration intensity of the fluid on the subsea oil and gas pipeline increases gradually with the increase of the apparent flow velocity of the liquid phase. By analyzing the multiphase flow problem of oil and gas pipelines, this study is of great significance in improving the efficiency of oil and gas transportation.

Studying Corrosion Failure Prediction Models and Methods for Submarine Oil and Gas Transport Pipelines

To predict the corrosion failure of carbon steel oil and gas pipelines more accurately, a new corrosion failure prediction model for submarine oil and gas transport pipelines was constructed. A corrosion failure prediction management system was also developed based on the constructed model. To construct the model, corrosion experiments were carried out to analyze the influences of temperature, partial pressure of CO2, pH value, and flow rate acting on the corrosion rate. Based on the analysis results and the corrosion experiment data, a new corrosion failure prediction model containing the time and flow rate for oil and gas pipelines was constructed. The model is based on the existing corrosion prediction model and has a determination coefficient, R2, of 0.9573, which indicates good prediction accuracy. A machine learning prediction model was also used to predict, and the prediction results are compared with that of the proposed model, which further verifies the accuracy and feasibility of the proposed model. A corrosion failure prediction management system for carbon steel oil and gas pipelines was developed based on the constructed model, which makes corrosion failure prediction more convenient and faster and provides a reference for the accurate prediction and efficient control of oil and gas pipeline corrosion failure.

Boiling combustion behaviors and heat feedback of pool fire of diesel fuel–water emulsification

AbstractIn the process of submarine oil exploitation and crude oil shipping, the offshore oil leakage accidents occur frequently. In the process of oil spill weathering on the sea, the oil is potentially mixed with water to form oil–water emulsification. The in situ burning is a low‐pollution and high‐efficiency method to eliminate the spilled oil. Meanwhile, as an alternative fuel, the emulsified diesel fuel has the advantage of energy saving and emission reduction. The combustion behaviors of pool fire of diesel fuel–water emulsifications are experimentally studied using three circular fuel reservoirs (10, 15, 20 cm) and five mass proportions of water (0%, 5%, 10%, 15%, 20%). The unsteady combustion process of emulsified diesel fuel is appreciated based on combustion phenomenon, mass burning rate, and flame length. The effects of pool diameter, ratio of water content, and initial fuel thickness on burning rate and flame length are revealed. The primary heat transfer mode in controlling the combustion behavior is explored according to the coupling factors of physical boundary of fuel reservoir, flame, and wall temperatures. This work is of great significance for understanding the combustion behavior of oil spill on the sea and optimizing the removal scheme of oil spill pollutants.

Adaptive Compressive Sensing: An Optimization Method for Pipeline Magnetic Flux Leakage Detection

Leakage from a submarine oil pipeline would have a great impact on the environment and ecological balance. Accurate detection of pipeline defects can ensure safety in the transportation of oil resources. The traditional detection optimization algorithm may lead to the absence of effective features. An adaptive compressive sensing image data augmentation method that analyzes the pixel distribution of small defect features has been proposed to solve these issues. On the basis of Focal-EIoU, a new box loss of Focal-GIoU is proposed which is suitable for pipeline defect detection. Furthermore, the incorporation of bi-level routing attention diminishes the reliance of Yolov5 on specific inputs effectively, thereby enhancing the generalization ability of the detection model. Comparative experiments show that compared with the conventional Yolov5 model, this method improves mAP50 and mAP50:95 by 6.4% and 15.1%, respectively, with mAP50 reaching 91.5% and mAP50:95 reaching 52.9%.

Inhibition on methane hydrate formation by polyacrylate superabsorbent hydrogel

Hydrate blockage in submarine oil and gas transport pipelines has always been the focus of attention in the oil and gas industry. Using superabsorbent hydrogels (SAHs), three-dimensional network structures with numerous hydrophilic groups, to prevent hydrate formation in gas/oil pipeline has been endowed with theoretical potential. In this work, the inhibition of traditional polyacrylate SAHs on methane hydrate formation was systematically studied via both numerical and morphological analysis. In methane hydrate formation from SDS solution (1 mmol/L), SAHs at relatively low swelling ratio of 10 and 5 produced obvious inhibition on hydrate nucleation, prolonging the induction time from 27.6 ± 14.5 min to 155.5 ± 157.1 and 334.2 ± 126.6 min, respectively. And the water fixation effects of SAHs could prevent methane hydrate growth from efficiently, with the inhibition efficiency reaching 65.83 ± 1.82 %, 81.82 ± 1.83 %, and 87.96 ± 1.66 % at swelling ratio of 20, 10, and 5, respectively. When used in simulated DI water/decane (W/O) mixture, at water content of 30 %, SAHs performed well at swelling ratio of 50 (mass ratio of 0.6 %), preventing methane hydrate formation by 94 % and keeping the mixture with low viscosity and good fluidity; at water content of 70 %, SAHs produced excellent performance at swelling ratio of 50–100 (mass ratio of 1.4%–0.7 %), preventing methane hydrate formation by 80 % and avoiding increasing the viscosity of the mixture. The results in this work confirmed the promising application potential of SAHs in gas/oil pipeline flow assurance.

A QoS-Aware Energy-Efficient Chimp Optimization Routing Protocol with Efficient Sensor Node Deployment Strategy in Underwater Acoustic Sensor Network

As an extension of wireless sensor networks in the underwater environment, Underwater Acoustic Sensor Networks (UASNs) have led to a broad consideration of academicians. One of the problems that lower UWSN effectiveness in terms of network lifespan is premature energy depletion. It might be caused by the network nodes using different amounts of energy. In UASNs, the effectiveness and dependability of data transfer remain so adverse because of the intricate underwater environment in diverse ocean applications like surveilling atypical submarine oil pipelines. Inspired by the significance of UASNs’ quality of service in several implementations, this study proffers a metaheuristic optimization algorithm (AG) called Chimp Optimization-based Routing Protocol (CH-ORP) for UASNs obtaining intricate features of underwater (UW) medium into concern like 3D changing topology, high propagation delay, node mobility, and density, and, also, cluster head nodes’ rotation mechanism. Initially, the entire network (NW) paradigm has been considered as a three-dimensional cube out of a grid point of view, and the three-dimensional cube has been split into several little cubes by employing Delaunay Triangulation. The optimization has been carried out for lessening node failure rate and NW energy consumption rate by ideally placing the sensor nodes in UW acoustic communication. The NW topology’s steadiness has been assured by the AG, and this optimizes the node redeployment scheme by computing the fitness function for all nodes. The proffered AG’s simulation substantiations have been performed for exhibiting the CH-ORP’s efficiency that executes finer when compared to the advanced methodologies concerning energy efficiency, reliability, and end-to-end delay. It has been found that the proposed Ch-ORP achieves 698 packets received with 28% of energy consumption, 156-sec Network delay, 257 packet loss, 97.23% of PDR, and 1256 Mbps of Network throughput.

Passability and Internode Mechanics Analysis of a Multisection Micro Pipeline Robot

In submarine oil and gas pipelines, the movement of a differential pressure multisection pipeline robot mainly relies on the front and rear driving pressure difference of the fluid and the friction between the cup and the pipe wall. The passability of the pipeline is a key point to guarantee success in scanning and detecting the inner wall of a pipeline by robot. When the multisection pipeline robot moves, the force of the internode connection points changes the degree of freedom of the robot. The existence of the connection points causes speed fluctuations in the robot during the movement process which, in turn, affects the detection accuracy of the pipeline. Consequently, a systematic analysis of the connection point movement is of great importance. In this paper, a rigid–flexible, coupled, multibody, dynamic motion system is established, where a multisection micro pipeline robot is built. The cup of the robot is set as a flexible body. The motion law of the differential pressure multisection pipeline robot is analyzed through simulation, and the robot’s motion speed and internode stress of the different cabin sections are explored jointly in practice. Taking the transportation of an oil and gas pipeline into full consideration, the motion law and force of the multisection pipeline robot are analyzed by changing the bulge and turning the radius of the inner wall of the pipeline. A corresponding experimental bench is built to explore the effects of different numbers of cups and lengths of the cabin sections on the turning characteristics of the robot. Simulations and experiments results are highly similar and within the error range. To this end, the presented work provides significant information for the model selection of multisection micro pipeline robots in the fields of submarine oil and gas pipelines.

Research on 3-D Precise Mapping System for Deformation Defects of Submarine Pipeline

Abstract The submarine oil pipeline has many advantages, such as large oil transportation capacity, and being fast and economical. However, long-term laid submarine oil pipelines are affected by reciprocating load of water flow, subsidence caused by soil liquefaction, ship anchorage operation, etc. In severe cases, it causes overall distortion of a small section of the submarine pipeline, profoundly affecting the safety of the submarine pipeline, which is a significant safety hazard for the health of the marine environment and potentially impacting social and economic benefits. Taking the Cezi-Zhenhai submarine pipeline in the sea area between Ningbo and Zhoushan as an example, many deformation defects in the pipeline have been found through internal inspection, and there is a trend of further deterioration. However, the existing external detection of submarine pipeline deformation can only collect limited data through mechanical dots for rough inversion. This does not meet the accuracy requirements of repairing existing submarine pipeline clamps. Therefore, we propose a real-time visualization surveying and mapping system for the submarine pipeline based on a 3-D laser and a separately designed electronic control system. Our research team performed actual mapping work for the Cezi-Zhenhai submarine pipeline and achieved an excellent mapping control effect. A steady monitoring image and good control effect of moving parts are obtained, and the data obtained by 3-D laser processing perfectly represent the actual state of the submarine pipeline. Predictably, the large-scale application of this system will provide a solid technical guarantee for the health of submarine pipelines.

SSWT-UUNet++ Submarine Oil Pipeline Spill Detection Approach

The existing leak detection methods of submarine oil pipelines mainly rely on compositing synthetic aperture radar (SAR) satellite images to detect oil spills on the sea surface or installing underwater cameras to monitor the joints of submarine pipelines manually. The former is poor in timeliness and high in cost, while the latter is inflexible. Aiming at this, this paper studies the underwater image processing method of intelligent oil spill recognition using an underwater camera. Nevertheless, this method is currently faced with challenges such as poor quality of datasets, unclear goals, and scarce quantity. The U-Net++ algorithm can theoretically reduce the dependence on the number of datasets. However, the pixel feature extraction method used by U-Net++ is difficult to achieve the segmentation effect of oil spill images, so a new network architecture SSWT (Suitable Superpixel With Texture)-UNet++ based on texture superpixel is proposed. In SSWT-UNet++, the input is the oil spill image with texture superpixel division, and the output was changed to the middle layer. In addition, the resolution of each layer and the ratio of up/down sampling were adjusted. This algorithm completes the classification of oil spill texture superpixels and finally realizes oil spill detection according to the minimum bounding rectangle of the classification result of the oil spill region. Experimental verification shows that the final detection effect of the proposed algorithm is higher than that of other algorithms, with an average precision of 0.985.

Study on the stability of oil-water annular flow under different amplitude

Compared with the traditional transportation of high-viscosity crude oil, water annular transportation has the advantages of low energy consumption and no change in crude oil composition. With the continuous development of marine heavy oil transportation, submarine oil pipelines are inevitably subjected to vibration and impact, affecting the annular flow in the pipeline. In this paper, the VOF model in Fluent software is used to simulate the stability of oil-water annular flow in a horizontal pipeline under different amplitudes and the interface characteristic parameters of annular flow. In addition, the influence of vibration on oil-water annular flow in the horizontal pipeline under different marine environments is studied. The results showed that the vibration parameters have an influence on the flow of oil-water annular flow in the horizontal pipeline. Under the condition of constant inlet velocity, the eccentricity degree of oil core is analyzed to reveal the law that the stability of annular flow decreases with the increase of amplitude. The relationship between the eccentricity of oil core and the vibrational parameters of pipes are explored in this paper. At the same time, the unit pressure drop under the condition of pipe vibration and its mechanism are studied. These results could provide references for parameters optimization of heavy oil-water annular flow transportation under vibration conditions.

Numerical Study of Leakage and Diffusion of Underwater Oil Spill by Using Volume-of-Fluid (VOF) Technique and Remediation Strategies for Clean-Up

An oil spill accident will cause serious harm to marine ecology and the environment. Rapid response and effective prevention methods are required to minimize the damage of oil spill accidents. The critical problems that marine emergency rescue teams face are when the spilled oil reaches the sea surface, the extent of the spilled oil, and how far they are from the drilling platform. However, there is no reliable model to predict the diffusion distance of spilled oil. Accurately predicting the diffusion characteristics of underwater spilled oil can provide timely and accurate information for the treatment of oil spill accidents and guide the correct implementation of emergency treatment. In this paper, the computational fluid dynamics (CFD) method was used to establish a two-phase flow model for the diffusion of a submarine oil spill. The volume-of-fluid (VOF) technique was implemented to track the interface between oil–water phases. The effects of different parameters on leakage and diffusion characteristics were investigated by adjusting spilled oil velocity, ocean current velocity, crude oil density, and crude oil viscosity. The logarithmic velocity profile was adopted for ocean currents to conform to the actual flow near the sea surface. A user-defined function (UDF) was developed and applied for CFD modeling. The focus was on analyzing the diffusion range (rising height Hp and lateral migration distance Wp) from full-field data. The results indicate that the oil spill velocity, ocean current velocity, crude oil density, and crude oil viscosity impact the viscous shear force, the oil spill’s inertia force, and the current shear effect. The formula for calculating the lateral migration distance of spilled oil under different working conditions was obtained by fitting. The results of this study can provide a scientific basis for formulating an emergency treatment plan for offshore oil spill accidents and minimizing the harm to marine ecology and the environment.

Risk analysis on corrosion of submarine oil and gas pipelines based on hybrid Bayesian network

Submarine pipeline is currently the safest and most economical transportation of subsea oil and gas. Corrosion is one of the main threats to submarine pipelines because of the corrosive of the sea. Therefore, it is significative to evaluate the corrosion risk of the submarine pipelines. In this work, a fault tree model is first employed to identify the corrosion hazards in the transportation process. To overcome the limitations of the fault tree analysis for the states of the events, a Bayesian network (BN) is established through mapping from the fault tree model. Because of the limitations of objective data, experts’ judgment combining fuzzy set theory are used to determine the parameters in the BN. The dynamic nodes in the BN are divided into real-time and discrete nodes, and the dynamic characteristics of them are displayed by the evidence nodes. In this way, when a new observation occurs, the real-time risk analysis of the corroded submarine pipeline is realized. Finally, a case study is carried out to verify the risk level variation with the observing events at different moments. Results shows that the proposed model can dynamically characterize the corrosion risk of the submarine pipeline and provide suggestions for the risk reduction.

Numerical Simulation of the Hydrodynamic Performance and Self-Propulsion of a UUV near the Seabed

Unmanned underwater vehicles (UUV) face maneuverability and rapidity challenges when they are applied for detecting and repairing submarine oil and gas pipelines, and fiber cables near the seabed. This research establishes numerical models of the bare UUV and self-propelled UUV near the seabed using the computational fluid dynamics (CFD) method. The effect of dimensionless distance Hd and ReL on the hydrodynamic performance of the vehicle and the interaction between the hull and the propeller is investigated. The range of Hd is 1.5D–10D, and the ReL is 9.97 × 105~7.98 × 106. Findings indicate that: (1) There is an obvious strong coupling between the hydrodynamic performance of the bare UUV and Hd. With the increase of Hd, the hydrodynamic performance such as Cd, the absolute value of Cl and my decreases continuously and finally tends to be stable. The absolute values of Cd and Cl increase with the increase of ReL. The change trend of my is opposite to that of Cl. (2) The variation trend of hydrodynamic performance of the self-propelled UUV with Hd is consistent with those of the bare UUV. Additionally, it increases to some extent, respectively, compared with the bare UUV. (3) The self-propelled characteristics such as t, ηH, w and ηi are weakly related to Hd. The t and ηi increase with the increasing of ReL, while ηH and w decrease with the increasing of ReL.

Research on the mechanical and water-repellent properties of bionic carbon fiber reinforced plastic composites inspired by coelacanth scale and lotus leaf

Carbon fiber reinforced plastic (CFRP) laminates are widely used in vessel side plate, underwater propeller, and submarine oil pipeline because they possess superior specific strength and hydrophobicity compared with metal materials. However, conventional CFRP laminates are limited by insufficient mechanical properties and incompetent water-repellent performance. Herein, a biomimetic double-helicoidal superhydrophobic laminate (BDHSL) was designed and manufactured through a method combining hot press forming and two-step spraying. The BDHSL was composed of double-helicoidal (inspired by coelacanth scale) carbon fiber prepreg and SiO2-based coating with multiscale hierarchical structures (inspired by lotus leaf), which displayed excellent mechanical properties and water-repellency. Besides, mechanical tests were carried out systematically. Remarkably, the peak impact force of the BDHSL at the impact energy of 20 J was 2865.25 N, which increased by 136.88% compared with traditional unidirectional laminate (UL 1209.56 N). Meanwhile, the finite element simulation was conducted using 3D Hashin's failure criteria. The simulation results showed that the predicted stress-deflection curve for four types of laminates correlated well with experimental results. Moreover, the water contact angle of BDHSL reached approximately 156.5°, which indicated its superhydrophobicity. What is more, the durability and water-repellency of the SiO2-based coatings were investigated, which further confirmed its potential underwater applicability. The investigations in this work offer a promising way to effectively design and fabricate exquisitely structured CFRP laminates with hierarchically textured coatings that are more suitable for various marine applications under practical conditions, such as offshore oil drilling platform, autonomous underwater vehicle, high-speed ship, and so forth.

Bacterial Communities and Culturable Petroleum Hydrocarbon Degrading Bacteria in Marine Sediments in the Northeastern South China Sea

Marine oil spill pollution was one of the factors affecting the marine ecology of the northeastern South China Sea (nSCS). The submarine oil produced after the oil spill had a long-term impact on the microbial community in the sediment. In this study, 16S rRNA genes high-throughput sequencing and quantitative PCR were used to study the composition and distribution of bacterial communities in deep-sea sediments; meanwhile, petroleum hydrocarbon degrading bacteria were isolated, of which activity were detected. Proteobacteria and Planctomycetota were the main bacterial phyla found in the samples studied in this study. 29 bacterial strains capable of degrading petroleum hydrocarbons were isolated from S02 and S39 sediment samples, belonging to genus Stenotrophomonas, Pseudidiomarina, Sulfitobacter, Pseudomonas, Halomonas and so on. Strains from Stenotrophomonas degraded petroleum hydrocarbons efficiently. This research provided new insights into distribution pattern of benthic microbial community in the nSCS, and validated the degradation potential of petroleum hydrocarbons by indigenous bacteria.

The investigation of hardness and density properties of GFRP composite pipes under seawater conditions

Glass fiber reinforced polymer (GFRP) composite pipes are mostly used in transmission lines of submarine oil, natural gas, and chemical fluids. The alterations in mechanical characteristics of composite pipes used in submarine applications are of great importance to the lifespan of the material. Some important mechanical properties of composite materials are density and hardness value. In this study, the changes in the density and hardness values of GFRP composite pipes which were unexposed to seawater and exposed to seawater for 1, 2 and 3 months were investigated. As a result of the present study, it was deduced that the characteristics of the sample changed with the effect of seawater.

Retraction Note: Oil spill risk assessment of submarine oil pipeline based on fuzzy comprehensive evaluation and accounting

Retraction Note: Oil spill risk assessment of submarine oil pipeline based on fuzzy comprehensive evaluation and accounting

A review on submarine oil and gas leakage in near field: droplets and plume.

The 2010 Deepwater Horizon spill remains the largest catastrophic release of oil and gas into the deep sea. The irrupted oil and gas substantially impact a marine ecosystem, cause human injury, and have high societal opinions. Therefore, understanding the transport and dispersion of subsurface hydrocarbon provides an imperative substratum for the practical assessment and response of marine oil spill accidents. In this review, we summarize the major advances since the Deepwater Horizon accident, with emphasis on the observation and modeling of the droplet and the formation and dynamics of the plume. Additional complexity including more than the investigation of gas-saturated oil at high-pressure and the effect of Earth's rotation on near field plume is also outlined. We end with a few outlooks on key priorities for more precisely estimations on future oil spills.