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Abstract With the continuous operation of oil and gas stations and petrochemical equipment, it has been found that steel small bore pipelines have different degrees of corrosion defects, which have led to pipeline cracking and medium leakage, and have increasingly attracted great attention of their oil and gas and chemical enterprises. In order to ensure the safe operation of the small diameter pipes with external surface corrosion defects, the influence law of the size of corrosion defects on the bearing capacity of the small diameter pipes were studied by finite element analysis and test simulation method, and the damage mechanism and failure form were analyzed, and the failure pressure prediction formula of the small diameter pipes with defects was fitted. It provides technical guidance for the applicability evaluation of corrosion-containing steel small diameter pipes in oil and gas chemical stations or installations.

Abstract Sliding-induced subsurface microstructure evolution is believed to be decisive for determining the friction and wear performance of metallic contacts as well as the development of tribo-magnetization. This expects to develop a new prediction method of wear state by elucidating the correlation between subsurface microstructure evolution and corresponding magnetic domain changes. Herein, subsurface microstructure evolution including crystal and magnetic domain under tribological action is investigated experimentally. Our results demonstrate that dislocation mediated plastic deformation decisively influences microstructural changes during tribological contact, further determining the magnetic domain structure. Specifically, sliding-induced plastic deformation causes an increase in the width of magnetic domains, but depth-dependent derived microstructure formed under severe plastic deformation such as the refined grains and sub-grains, in turn, promoted the refinement of magnetic domains and their discontinuity, forming depth-dependent magnetic domain structure. These results are helpful to clarify the evolution of tribo-magnetization and the pinning effect of dislocations on magnetic domains.

Subsea wellheads and Christmas trees are commonly utilized in deepwater oil and gas development. However, the special structure of subsea wellheads makes it difficult to monitor casing–casing annular pressure buildup, which in turn poses a greater risk to the integrity of the wellbore. In order to analyze the effect of changes in the casing-free section and the sealed section on the variation in annulus volume, a new annular pressure buildup model of casing-cement sheath-formation deformation was established and verified according to the elastic deformation theory. Furthermore, the influence of casing deformation on annulus pressure buildup was analyzed. Results indicate that the error of annulus pressure buildup predicted by the multi-string mechanical model proposed in this paper that considers the deformation of the casing sealing section is approximately 13% lower than the one that does not consider this factor. This paper provides guidance for the design of casing strings in deepwater oil and gas wells, ensuring safe production.

Eddy current thermography (ECT) is a non-invasive testing method that combines electromagnetic induction and infrared thermography to identify flaws in materials that conduct electricity. However, ECT faces difficulties in accurately locating and classifying defects owing to its low signal-to-noise ratio and complex defect patterns. In this paper, we propose a new method that integrates an improved faster region-convolutional neural network (R-CNN) and an adaptive Canny algorithm to enhance the defect detection performance of ECT. An improved faster R-CNN is a deep neural network that can automatically detect and locate multiple defects in a single ECT image, whereas the adaptive Canny algorithm is an edge detection technique that can identify defect boundaries. The proposed method was tested using a dataset of ECT images with different types of defects. The results demonstrated that our method achieved better accuracy, precision, and speed than existing methods.

Oil and gas production systems have the characteristics of high operation and maintenance risk and great accident influence. With the deep integration of informationization and industrialization, the development direction and necessary choice of the oil and gas industry is to develop the oil and gas production system into the interconnected, multi-domain interactive cyber-physical intelligent system. In order to avoid or reduce the complex, diverse and potentially unknown safety risks in the process of oil and gas production, improve the safety and reliability of oil and gas production system and increase the production efficiency, this paper analyzes the safety problems occurring in the intelligentization process of oil and gas production system and constructs a system from the perspective of operation and maintenance based on key elements of intelligent safe operation and maintenance technology, combined with the typical production scenarios in the oil and gas production industry. And the following research results are obtained. First, the connotation of intelligent safe operation and maintenance technology is clarified, the key elements and existing problems and challenges of intelligent safe operation and maintenance technology are analyzed, and the “1-2-3-4-5-6” intelligent safe operation and maintenance technology system of oil and gas production system is constructed, which empowers six key technologies with key elements of oil and gas production to realize the essential safety of oil and gas production system. Second, the intelligent safe operation and maintenance technology actively promotes the application and implementation of condition monitoring, health management, risk assessment, intelligent early warning technologies in typical production scenarios such as drilling and extraction, storage and transportation, refining and chemical industry in up, middle and down streams of oil and gas production. Third, in view of the characteristics of oil and gas production system under digital transformation, it is proposed to develop the intelligent safe operation and maintenance technology with the functions of intelligent decision-making, active prevention and comprehensive safety in the future to help the safe construction in the field of oil and gas production and promote the safe and healthy development of the oil and gas industry. In conclusion, the research on intelligent safe operation and maintenance technology system of oil and gas production system is conducive to the safe construction in the field of oil and gas production, which will not only provide technical support for the realization of trouble-free oil and gas production system, but also provide reference for the intelligent development of the world oil and gas industry.

With the continuous expansion of oil and gas stations in construction scale in China, the requirements for safe production, operation and management are becoming more and more stringent. However, the visualization application and comprehensive display of current pipelines and station entities are very scarce, and it is impossible to view the regional distribution and operation data of such stations in a three-dimensional scene. In addition, facility and equipment models highly consistent with the actual situations have not yet been established. In response to those problems, a systematic solution of intelligent oil and gas stations based on digital twin was proposed. Specifically, according to the digital twin theory, an equal-scale high-precision station model was established on the basic platform, i.e. ArcGIS system, by the 3Ds Max software to build a digital twin-based station that could truly map the physical station. Based on that, an intelligent cyber-physical system of oil and gas stations was created with the help of advanced sensing, big data analysis and human-computer interaction technology. As a demonstration, the system design and development was applied to a compressor station in Shaanxi, proving that the system could realize the three-dimensionality display of all elements in the station, the real-time monitoring of station status, and the overall decision-making on station management. Hence, it is helpful to comprehensively improve the level of macro supervision, major supervision and precise supervision of stations for safe production.

The textual generalization of accident risk factors is an important step to establish the knowledge graph of accident risk factors of the oil & gas storage and transportation enterprises. In order to solve the problem of semantic representation limitations and word segmentation errors for the textual generalization of risk factors accumulated in the production process of oil & gas storage and transportation enterprises by existing event text generalization methods, a textual generalization method of accident risk factors based on the Char-Word feature based AGNES (CW-AGNES) was put forward according to the complicated and changeable text expression of safety management. Definitely, the character feature and binary word feature vectors of the oil & gas storage and transportation enterprises were obtained by Word2vec method. The text of accident risk factors is vectorized according to the pre-trained word vector model. Then, the char-word features of the text are added with the agglomerative nesting method, and the error caused by word segmentation can be reduced on the basis of retaining the semantic information of the words, so as to realize the generalization of the risk factor text. Specifically, the CW-AGNES method was applied to the actual safety management texts of the oil & gas storage and transportation enterprises. Meanwhile, comparison was made with other generalization methods. The results show that: The CW-AGNES method has a better generalization effect with 2.44%–5.74% improvement in quantitative evaluation indicators such as AMI, ARI, V-Measure and FMI. Therefore, the proposed method could provide support for the construction of accident risk knowledge graph in the field of oil & gas storage and transportation.

Recently, pipeline are widely used in oil and gas transportation. But due to corrosion and external forces, corrosion, material failure and damage may occur. In this paper, a novel alternating current field measurement (ACFM) probe and inspection system are developed for pipeline in-line inspection. To optimize inspection ability of the system, various lift-off distances and inducing frequencies are analyzed. By finite element analysis and experimental testing, the probe with a frequency of 2500Hz and a lift-off distance of 12 mm has a smaller relative error in length, and also has higher inspection sensitivity. The minimum crack inspected by the probe is 10 mm in length. The present study should be helpful to design and application of pipeline inspecting probes.

In the process of oil & gas storage and transportation, a large number of solid particles carried by the medium may lead to depressurization, blockage, corrosion, abrasion and other phenomena. In particular, the welding slag left during the pipeline construction and the sand carried during its operation can cause erosion wear to the pipeline wall and the vulnerable parts, and even lead to the failure of equipment and pipe fittings, further resulting in serious economic loss, safety and environmental protection issues. Understanding the phenomenon of erosion wear, and mastering the laws of erosion wear, are beneficial improving or alleviating the wear problems of pipelines during the production, storage and transportation of oil and gas, and further facilitating the enterprises to achieve the goal of economic, safe and efficient operation. So the current research status of solid particles on the erosion wear of materials were concluded comprehensively, the main features that affect the erosion wear were summarized, the theoretical models applicable to the erosion wear calculation under different working conditions were sorted out, and the test methods used to investigate the law of erosion wear were summarized. Meanwhile, the limitations and shortcomings of the current research on erosion wear were put forward, and the recommendations on the next steps of the research on erosion wear in the oil and gas pipeline industry were clarified briefly.

The complete mitochondrial genome of Xylotrechus namanganensis was sequenced. The genome size was 15,565 bp, which consists of 13 protein-encoding genes, 22 tRNA-encoding genes, 2 rRNA-encoding genes and 1D-loop control region. The base composition of mitogenome was biased toward A + T content, of which was 73.21%. The phylogenetic tree based on complete mitogenome sequences revealed that T. namanganensis had a closer relationship with X. grayii.

In order to investigate the relationship between tribo-magnetization and wear phenomena, a series of sliding-friction tests were carried out using a pin-on-block reciprocator type device, which was specially designed to generate sliding friction and to detect magnetic fields. The tribological behavior was observed by a charge-coupled device (CCD) camera in real time, and the magnetic signal was detected by using a two-axis magnetic sensor. It was found that as the friction continues, both the tangential and the normal components of magnetic field on the material surface increase gradually, and that both the average value of the tangential magnetic field ΔH(x)mean and the peak-to-peak value of the normal magnetic field Vpp at the wear scar clearly reflect changes of the wear state. Furthermore, in order to better understand the tribo-magnetization phenomenon, the changes of surface morphology and wear debris in different wear stages were analyzed. Moreover, an improved magnetic dipole model that considered the distribution of magnetic charges on the worn surface was established. This model can successfully describe the tribo-magnetization phenomenon during the stable wear stage, and should be useful for characterizing frictional wear phenomena in the future.

The ball valve is an essential piece of equipment in an oil and gas pipeline. The sand particles transported through the pipeline can cause erosion and wear to the ball valve, thus causing it to fail, leading to serious safety hazards. In this paper, the self-designed erosion experiment method was combined with computational fluid dynamics (CFD), while the Euler-Lagrange method was also introduced to optimize the Oka erosion model and Ford particle-wall rebound model. The erosion mechanism and characteristics of the ball valve sealing surface in gas-solid two-phase flow were simulated, while the erosion condition of the specimen was analyzed and compared when exposed to different factors, such as different particle velocities, impact angle, particle size, and specimen materials. The experimental data conformed well to the CFD erosion simulation data, verifying the accuracy of the CFD simulation analysis. The results indicated that the worn surface was caused by various wear mechanisms, while a “stagnation zone” was identified at the center of the specimen. The maximum erosion area, which was U-shaped, was also located at the center. The erosion rate increased in conjunction with an increase in the particle velocity and size, both of which failed to affect the erosion pattern. The erosion rate initially increased, after which it decreased with the impact angle, reaching the maximum value at an impact angle of 30°. This paper summarizes the erosion failure mechanism and characteristics in gas–solid two-phase flow and provides both technical support and a theoretical basis for the on-site maintenance of essential vulnerable parts in the pipeline, such as ball valves.

Analysis on the sliding risk of jack-up platform re-installation close to the existing footprint is conducted with finite element method. An effective countermeasure to reduce the sliding risk is suggested and an example analysis for an existed jack-up platform re-installation in a typical block with two layer soil within design driving depth in China sea area is carried out. Taking into consideration fluid seepage in pore structure, sliding contact friction, and the material and geometric nonlinear properties, a fluid-solid coupling finite element model for the spudcan-soil interaction is constructed. By comparing the numerical simulation result with the experimental result published in the literature, the reliability of the finite element model is verified. With the model, the failure process, the movement pattern of foundation and the spudcan-soil interaction under the impact of the footprint are analyzed. The study shows: in pitching pile the plastic failure zone appears at the low corner close to the spudcan first, then the area beneath the spudcan, and the plastic area becomes larger to form a connecting region finally as the loading increases continuously; the migration pattern of soil around the spudcan changes sharply with the distance between the spudcan and the footprint increasing; at the same time the peak value of the horizontal sliding force increases first then decreases gradually. In the final pitching pile position, ‘stomping’ in advance in appropriate distance and depth can reduce the sliding risk of a jack-up platform re-installation effectively. Key words: existing footprint, jack-up drilling platform, spudcan-soil interaction, sliding risk, countermeasure

In this paper, a new inducer of pulsed eddy current thermography (PECT) is presented. The use of the inducer can help avoid the problem of blocking the infrared (IR) camera’s view in eddy current thermography technique. The inducer can also provide even heating of the test specimen. This paper is concerned with the temperature distribution law around the crack on a specimen when utilizing the new inducer. Firstly, relative mathematical models are provided. In the following section, eddy current distribution and temperature distribution around the crack are studied using the numerical simulation method. The best separation distance between the inducer and the specimen is also determined. Then, results of temperature distribution around the crack stimulated by the inducer are gained by experiments. Effect of current value on temperature rise is studied as well in the experiments. Based on temperature data, temperature features of the crack are discussed.

Effective signal processing in fault detection and diagnosis (FDD) is an important measure to prevent failure and accidents of machinery. To address the end distortion and frequency aliasing issues in conventional lifting wavelet transform, a Volterra series assisted undecimated lifting wavelet packet transform (ULWPT) is investigated for machinery incipient fault diagnosis. Undecimated lifting wavelet packet transform is firstly formulated to eliminate the frequency aliasing issue in traditional lifting wavelet packet transform. Next, Volterra series, as a boundary treatment method, is used to preprocess the signal to suppress the end distortion in undecimated lifting wavelet packet transform. Finally, the decomposed wavelet coefficients are trimmed to the original length as the signal of interest for machinery incipient fault detection. Experimental study on a reciprocating compressor is performed to demonstrate the effectiveness of the presented method. The results show that the presented method outperforms the conventional approach by dramatically enhancing the weak defect feature extraction for reciprocating compressor valve fault diagnosis.