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Coal destruction is an energy-driven destabilization phenomenon. In order to investigate the effect of moisture on energy accumulation and dissipation during coal destruction, uniaxial compression tests on coal samples with different water content states were carried out, and the mechanical properties and impact energy index of coal were analyzed based on this. The results showed that the uniaxial compressive strength and elastic modulus of coal samples decreased significantly with the increase of water content; the proportion of the initial compression-density stage, plastic deformation damage stage and post-peak damage stage in the full stress-strain process of coal samples increased, and the proportion of linear elastic stage decreased; the accumulation deformation energy before the peak of coal samples decreased, the loss deformation energy after the peak increased, and the impact energy index decreased. The increase of water content changed the coal sample from splitting damage to shear damage, and the particle size of crumbling pieces became larger, the number of pieces decreased, and the damage sound weakened during the damage. The uniaxial compressive strength, impact energy index and impact energy velocity index of coal samples in water-saturated condition decreased by 35.32%, 86.07% and 99.63%, respectively, compared with those in dry condition, and the coal seam water injection process can effectively reduce the impact propensity of coal seam.

The Lofoten Vortex (LV), which is identified as a quasi-permanent anticyclonic eddy, strengthens through continuous merging with external anticyclonic eddies. Our investigation used the Lagrangian method to monitor the LV on a daily basis. Utilizing satellite altimeter data, we conducted multi-year tracking and statistical analysis of merging events involving the LV. The results indicate a characteristic radius of approximately 42.72 km and a mean vorticity at the eddy center of approximately −2.23 × 10−5 s−1. The eddy exhibits oscillatory motion within the sea basin depression, centered at 70°N, 3°E, characterized by counterclockwise trajectories between 0.5°E and 6°E and between 69°N and 70.5°N. There are two types of merging events: fusion events (55%), in which eddies of similar strengths interact within a closed flow line and then merge to form a new eddy; and absorption events (45%), in which the stronger LV absorbs the weaker anticyclonic eddies without destroying the structure of the LV itself. The nodes where strong vorticity advection occurs correspond to the nodes where merging occurs, suggesting that their effect on merging can be well characterized by the vorticity advection time series. We also observe occasional fluctuations and substitution events involving the LV and external anticyclonic eddies, suggesting a dynamic succession rather than a single vortex entity. [ABSTRACT FROM AUTHOR]

This paper investigates the application of a self-coder neural network in oilfield rod pump anomaly detection. Rod pumps are critical equipment in oilfield production engineering, and their stability and reliability are crucial to the production efficiency and economic benefits. However, rod pumps are often affected by anomalies such as wax deposition, leading to increased maintenance costs and production interruptions. Traditional wax deposition detection methods are inefficient and fail to provide early warning capabilities. This paper reviews the research progress in sucker rod pump anomaly detection and autoencoder neural networks, providing a detailed description of the construction and training process of the autoencoder neural network model. Utilizing data from the rod-pumped wells of the Tuha oilfield in China, this study achieves the automatic recognition of various anomalies through data preprocessing and the training of an autoencoder model. This study also includes a comparative analysis of the differences in the anomaly detection performance between the autoencoder and traditional methods and verifies the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

In order to solve the current problems of untimely feedback information, lack of effective analysis of big data and inconvenient real-time operation in the process of coal mine anti-wind drill, an anti-wind drill command platform based on multi-system integration is designed. The platform is based on the mine anti-wind drill process and configures the platform server and client with the existing safety monitoring system, underground personnel positioning system, mine car positioning system, integrated automation system, power monitoring system, video surveillance and other system servers in the same industrial ring network. Therefore, the server and client are able to communicate directly with each system using the corresponding protocols, and big data technology is used to obtain the corresponding data effectively, classify, filter and process the data, and complete the multi-system integration. On this basis, the real-time map system, power outage and transmission system, integrated alarm system and interactive component system are designed. Real-time map system can realize dynamic update and display of maps. The important observation data such as personnel, wind direction and gas are graphically displayed on the ventilation system schematic diagram, realizing the geographic information management, analysis and auxiliary decision-making in coal mines. The power outage and transmission system can display the status of the switch in real time on the power supply system schematic diagram to realize the function of automatic search of power supply lines and remote power outage and transmission so as to guarantee the reliability and safety of power outage and transmission. The integrated alarm system responds to the abnormal information of the anti-wind drill command platform and site in real time through text and voice, and activates the corresponding emergency plan system as needed to reduce the occurrence of on-site accidents effectively. Interactive components can quickly realize remote video calls, regional personnel view, real-time data acquisition, personnel position search, personnel track query and other functions. This improves the work efficiency of personnel participating in anti-wind drill effectively. The field application results show that the platform can reduce the number of personnel participating in anti-wind drill, improve the efficiency of power outage and transmission, ensure the safety and reliability of the drill process and can be applied to rescue and disaster relief under various actual disaster conditions in mines.

Natural gas hydrate (NGH) trials have been performed successfully with different development methods and gas recovery drainage technologies. Multiphase flow in a wellbore and the drainage of natural gas hydrate are two important parts for its whole extraction process. Additionally, the choice of the drainage method is linked to the development method, making the drainage of NGH more complex. Jet pump drainage is usable for NGH production wells with the combined depressurization and thermal stimulation method. The objective of this study is to shed more light on the multiphase flow behavior in jet pump drainage and NGH production wells and put forward suggestions for adjusting heat injection parameters. The mechanism of jet pump drainage recovery technology for NGH wells was analyzed and its applicability to NGH development by the combined depressurization and thermal stimulation method was demonstrated. In addition, multiphase flow models of tubing and annulus were established, respectively, for the phenomenon of the countercurrent flow of heat exchange in the process of jet pump drainage and gas production, and the corresponding multiphase flow laws were derived. On the basis of these studies, sensitivity analysis and the optimization of thermal stimulation parameters were conducted. It is demonstrated that jet pump drainage gas recovery technology is feasible for the development of onshore NGH with the combined depressurization and thermal stimulation method. The laws of multiphase flow in the tubing and annulus of jet pump drainage and NGH production wells were disclosed in this study. Numerical simulation results show that the temperature and pressure profiles along the wellbore of jet pump drainage and NGH production wells during the drainage recovery process are affected by injection conditions. Increasing injection rate and injection temperature can both improve the effect of heat injection and reduce the hydrate reformation risk in the bottom of the annulus. This study offers a theoretical basis and technical support for production optimization and hydrate prevention and control in the wellbore of jet pump drainage and NGH production wells. [ABSTRACT FROM AUTHOR]

Under casing annulus gas venting, the annulus of the well is in a special state of zero-net liquid flow (ZNLF), leading to gas production without liquid at the wellhead, resulting in significant holdup issues. Therefore, conventional two-phase flow models cannot be used for calculation. To study the flow characteristics of ZNLF in the annulus of the well, this study established a visual experimental device with a total height of 5.4 m, an outer pipe inner diameter of 140 mm, and an inner pipe outer diameter of 72 mm. The flow characteristics of ZNLF were studied by controlling the casing pressure, initial liquid level, and bottom gas injection rate. The experimental results showed that the flow patterns of ZNLF are mainly bubbly flow and churn flow. Bubbly flow occurred at lower gas rates, while churn flow occurred at higher gas rates. In addition, the experiment found that when the gas injection rate and initial liquid column height were controlled to be the same, the liquid holdup decreased as the casing pressure increased. Analysis of the data patterns indicated that the slip velocity is related to the casing pressure. Based on the experimental results of ZNLF in the annulus, this study established standards for flow pattern transitions, holdup, and a pressure drop calculation model. The model results showed good agreement with the experimental results, with errors not exceeding ±5%. [ABSTRACT FROM AUTHOR]

Conventional gas well classification methods cannot provide effective support for gas well routine management, and suffer from poor timeliness. In order to guide the on-site operation in liquid loading gas wells and improve the timeliness of gas well classification, this paper proposes a production data-driven gas well classification method based on the LDA-DA (Linear Discriminant Analysis–Discriminant Analysis) combination model. In this method, considering the requirements of routine management, gas wells are evaluated from two aspects: liquid drainage capacity (LDC) and liquid production intensity (LPI), and are classified into six types. Domain knowledge is used to perform the feature engineering on the on-site production data, and five features are set up to quantitatively evaluate the gas well and to create classification samples. On this basis, in order to specify the optimal data processing flow to establish the gas well classification map, four linear dimensionality reduction techniques, LDA, PCA, LPP, and ICA, are used to reduce the dimensionality of original classification samples, and then, four classical classification algorithms, NB, DA, KNN, and SVM, are trained and evaluated on the low-dimensional samples, respectively. The results show that the LDA space achieves the optimal sample separation and is chosen as the decision space for gas well classification. The DA algorithm obtains the top performance, i.e., the highest Average Macro F1-score of 95.619%, in the chosen decision space, and is employed to determine the classification boundaries in the decision space. At this point, the LDA-DA combination model for sample data processing is developed. Based on this model, gas well classification maps can be established by data mining, and the rapid evaluation and diagnosis of gas wells can be achieved. This method realizes instant and efficient production data-driven gas well classification, and can provide timely decision-making support for gas well routine management. It introduces new ideas for performing gas well classification, expanding the content and scope of the classification work, and presenting valuable insights for further research in this field. [ABSTRACT FROM AUTHOR]