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11 pages, 2026 KiB

Open AccessArticle

Experimental Study on the Alteration in Pore Structure of Chang 7 Shale Oil Reservoirs Treated with Carbon Dioxide

by Can Shi, Meng Yang, Wei Liu and Wentong Zhang

Processes 2025, 13(4), 1015; https://doi.org/10.3390/pr13041015 - 28 Mar 2025

Viewed by 243

Understanding the changes in the pore structure of reservoirs in the presence of CO₂ is critical for carbon neutrality, especially for shale oil reservoirs with ultra-low permeability and porosity. However, studies examining the alteration in the pore structure of shale oil reservoirs [...] Read more.

Understanding the changes in the pore structure of reservoirs in the presence of CO₂ is critical for carbon neutrality, especially for shale oil reservoirs with ultra-low permeability and porosity. However, studies examining the alteration in the pore structure of shale oil reservoirs that have been treated with CO₂ remain limited. Thus, in this paper, nuclear magnetic resonance (NMR) and low-temperature nitrogen adsorption (LNA) technologies were employed to address this issue. The results show that the permeability and porosity of shale oil reservoirs increase after exposure to CO₂. The permeability improves by 49.03%, and the porosity increases by 29.54%. The NMR results reveal that the pore structure of shale oil reservoirs is altered. Specifically, increases of 11.14%, 74.54%, and 990.02% in the presence of CO₂ are observed for micropores, mesopores, and macropores, respectively. CO₂ is more sensitive to macropores, followed by mesopores and micropores. Furthermore, the LNA results indicate that some small pores expand into larger pores, leading to a decrease in the number of small pores and an increase in the number of larger pores. Combining the results of NMR and LNA, it is found that the increase in big pores is the reason behind the enhancement in permeability and porosity. This paper sheds light on the change in the pore structure of shale oil reservoirs after exposure to CO₂, further guiding the evaluation of CO₂ storage capacity. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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24 pages, 9456 KiB

Open AccessArticle

Optimization and Application of Bio-Enzyme-Enhanced Gel-Breaking Technology in Fracturing Fluids for Tight Sandstone Gas in the Linxing Block, Ordos Basin

by Jiachen Hu, Gaosheng Wang, Weida Yao, Yu Li, Meiyang Jing, Tian Lan, Zhongxu Xie and Anxun Du

Processes 2025, 13(2), 440; https://doi.org/10.3390/pr13020440 - 6 Feb 2025

Viewed by 719

Abstract

The main tight sandstone gas reservoirs in the Linxing block of the Ordos Basin exhibit a temperature range of 35–60 °C. Under these low-temperature conditions, conventional oxidative gum breakers used in fracturing operations react sluggishly, fail to break the gum completely, and can [...] Read more.

The main tight sandstone gas reservoirs in the Linxing block of the Ordos Basin exhibit a temperature range of 35–60 °C. Under these low-temperature conditions, conventional oxidative gum breakers used in fracturing operations react sluggishly, fail to break the gum completely, and can cause significant reservoir damage. In order to achieve complete breakage of the fracturing fluid and reduce the damage to the fracture and reservoir, active bio-enzyme-enhanced breakers have been incorporated into fracturing fluid formulations, so as to achieve rapid breakage, re-discharge at low temperature, and reduce the contact time between the fracturing fluid and the formation, which is critical for enhancing production efficiency. Based on the preliminary success of bio-enzyme-enhanced fracturing technology, this paper carries out an optimization study of bio-enzyme-enhanced fracturing technology for the low-temperature reservoir in the Ordos Linxing block. The study simulates the temperature recovery of the injected fluids under different reservoir temperatures during the fracturing process, aiming to further optimize the concentration of the bio-enzyme-enhanced fracture breakers in the fracturing phases, and to achieve optimized fracturing technology which is more in line with the temperature environment of the fluids. This can further optimize the concentration of the bio-enzyme breaker added at each fracturing stage, and achieve enhanced breaking in a stepwise manner that is more in line with the fluid temperature environment, thus improving the efficiency and production capacity for subsequent production. The optimized fracturing fluid system, incorporating the tailored concentration of the bio-enzyme breaker, was applied to 54 wells in this block, resulting in about a two-times improvement in production compared to conventional non-optimized methods, with many wells achieving high output. These results demonstrate the strong applicability of the optimized breaker procedure in this geological context. Additionally, this study investigated an optimization model for the well shut-in time during winter operations involving low-temperature fracturing fluids in low-temperature reservoirs, providing a valuable design basis for future production planning. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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20 pages, 5914 KiB

Open AccessArticle

Numerical Simulation Study of the Optimization on Tubing-to-Sediment Surface Distance in Small-Spacing Dual-Well (SSDW) Salt Caverns

by Lei Wang, Zheng Chu, Jiang He, Yujia Zhai, Junming Huang and Haonan Yang

Processes 2025, 13(2), 322; https://doi.org/10.3390/pr13020322 - 24 Jan 2025

Viewed by 562

Abstract

The small-spacing dual-well (SSDW) technique plays a crucial role in the establishment of underground salt cavern gas storage reservoirs. However, during the cavity dissolution and brine discharge processes, insoluble sediment is prone to being carried into the discharge tubing with the brine, leading [...] Read more.

The small-spacing dual-well (SSDW) technique plays a crucial role in the establishment of underground salt cavern gas storage reservoirs. However, during the cavity dissolution and brine discharge processes, insoluble sediment is prone to being carried into the discharge tubing with the brine, leading to tubing blockages or clogging, which disrupts injection and withdrawal operations and severely affects both project efficiency and the safety of the gas storage facility. This study systematically analyzes the influence of the gap between the injection and discharge tubing and the surface of the sediment-on-sediment movement, deposition, and tubing safety in SSDW salt caverns. Through numerical simulations, this study investigates the influence of tubing layout on the internal flow field distribution of the cavern and the suspension behavior of sediment, revealing the changing trend of the risk of sediment entering the tubing at different distances. The results show that a rational tubing distance can significantly lower the risk of sediment backflow and tubing entry, while maintaining high brine discharge efficiency. Based on the simulation results, an optimized tubing layout design suitable for SSDW salt caverns is proposed, offering technical direction to guarantee the safe and effective functioning of underground salt cavern gas storage sites. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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25 pages, 10233 KiB

Open AccessArticle

Advanced Insights into Methane Hydrate Production: Influence of Pressure, Saturation, and Permeability Dynamics

by Yunjian Zhou, Yufa He, Yu Chen and Shihui Sun

Processes 2025, 13(1), 80; https://doi.org/10.3390/pr13010080 - 1 Jan 2025

Viewed by 969

Abstract

The decomposition of hydrate during hydrate mining can reduce the strength of the formation and induce engineering geological disasters. Clarifying the decomposition characteristics of geological hydrate during hydrate mining is of great significance for preventing marine geological disasters. This study comprehensively examines the [...] Read more.

The decomposition of hydrate during hydrate mining can reduce the strength of the formation and induce engineering geological disasters. Clarifying the decomposition characteristics of geological hydrate during hydrate mining is of great significance for preventing marine geological disasters. This study comprehensively examines the effects of various extraction conditions, including production pressure, hydrate saturation, and permeability, on methane hydrate decomposition during depressurization-based extraction. Key findings show that reduced production pressure significantly increases gas and water production rates due to an enhanced pressure differential, albeit at the cost of potential geomechanical instability. Variations in hydrate saturation reveal that lower-saturation reservoirs initially exhibit higher production due to faster pressure propagation and greater porosity, whereas high-saturation layers may sustain production in the later stages. Permeability changes impact pressure diffusion and heat transfer within the formation; higher permeability leads to faster initial production but causes rapid energy depletion, requiring supplementary energy inputs to maintain production. These findings provide essential insights for optimizing methane hydrate extraction, ensuring high productivity while mitigating formation stability risks. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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17 pages, 5112 KiB

Open AccessArticle

Impact of Temperature on Cement Displacement Efficiency: Analysis of Velocity, Centralization, and Density Differences

by Xiaowei Tang, Jian Zhang, Dewei Liu, Guoshuai Ju and Xiaofeng Sun

Processes 2024, 12(12), 2923; https://doi.org/10.3390/pr12122923 - 20 Dec 2024

Viewed by 669

Abstract

This paper investigates the impact of temperature on the rheological behavior of cement slurry and drilling fluid and examines how various factors, such as displacement speed, casing centralization, and density difference, influence displacement efficiency during cementing operations. Using numerical simulations validated against experimental [...] Read more.

This paper investigates the impact of temperature on the rheological behavior of cement slurry and drilling fluid and examines how various factors, such as displacement speed, casing centralization, and density difference, influence displacement efficiency during cementing operations. Using numerical simulations validated against experimental data, we explore how these factors interact under different temperature conditions. Results indicate that temperature changes significantly affect the flow characteristics, displacement interface stability, and overall displacement efficiency. Findings demonstrate that optimizing these parameters according to temperature conditions can significantly enhance cementing performance and reduce the risk of fluid channeling and instability. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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17 pages, 3748 KiB

Open AccessArticle

Kick Risk Diagnosis Method Based on Ensemble Learning Models

by Liwei Wu, Detao Zhou, Gensheng Li, Ning Gong, Xianzhi Song, Qilong Zhang, Zhi Yan, Tao Pan and Ziyue Zhang

Processes 2024, 12(12), 2704; https://doi.org/10.3390/pr12122704 - 30 Nov 2024

Cited by 1 | Viewed by 563

Abstract

As oil and gas exploration and development gradually advance into deeper and offshore fields, the geological environment and formation pressure conditions become increasingly complex, leading to a higher risk of drilling incidents such as kicks. Timely diagnosis of kick risk is crucial for [...] Read more.

As oil and gas exploration and development gradually advance into deeper and offshore fields, the geological environment and formation pressure conditions become increasingly complex, leading to a higher risk of drilling incidents such as kicks. Timely diagnosis of kick risk is crucial for ensuring safety and efficiency. This study proposes a kick risk diagnosis method based on ensemble learning models, which integrates various time-series analysis algorithms to construct and optimize multiple kick diagnosis models, accurately fitting the relationship between integrated logging parameters and kick events. By incorporating high-performance ensemble models such as Stacking and Bagging, the accuracy and F1 score of the models were significantly improved. Furthermore, the application of the Synthetic Minority Over-sampling Technique and Tomek Links (SMOTE-Tomek) data balancing technique effectively addressed the issue of data imbalance, contributing to a more robust and balanced model performance. The results demonstrate that integrating time-series analysis with ensemble learning methods significantly enhances the predictive reliability and stability of kick monitoring models. This approach provides a dependable solution for addressing complex kick monitoring tasks in offshore and deepwater drilling operations, ensuring greater safety and efficiency. The findings offer valuable insights that can guide future research and practical implementation in kick risk diagnosis. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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30 pages, 10377 KiB

Open AccessArticle

An Intelligent Kick Detection Model for Large-Hole Ultra-Deep Wells in the Sichuan Basin

by Xudong Wang, Pengcheng Wu, Ye Chen, Ergang Zhang, Xiaoke Ye, Qi Huang, Chi Peng and Jianhong Fu

Processes 2024, 12(11), 2589; https://doi.org/10.3390/pr12112589 - 18 Nov 2024

Viewed by 864

Abstract

The Sichuan Basin has abundant deep and ultra-deep natural gas resources, making it a primary target for exploration and the development of China’s oil and gas industry. However, during the drilling of ultra-deep wells in the Sichuan Basin, complex geological conditions frequently lead [...] Read more.

The Sichuan Basin has abundant deep and ultra-deep natural gas resources, making it a primary target for exploration and the development of China’s oil and gas industry. However, during the drilling of ultra-deep wells in the Sichuan Basin, complex geological conditions frequently lead to gas kicks, posing significant challenges to well control and safety. Compared to traditional kick detection methods, artificial intelligence technology can improve the accuracy and timeliness of kick detection. However, there are limited real-world kick data available from drilling operations, and the datasets are extremely imbalanced, making it difficult to train intelligent models with sufficient accuracy and generalization capabilities. To address this issue, this paper proposes a kick data augmentation method based on a time-series generative adversarial network (TimeGAN). This method generates synthetic kick samples from real datasets and then employs a long short-term memory (LSTM) neural network to extract multivariate time-series features of surface drilling parameters. A multilayer perceptron (MLP) network is used for data classification tasks, constructing an intelligent kick detection model. Using real drilling data from ultra-deep wells in the SY block of the Sichuan Basin, the effects of k-fold cross-validation, data dimensionality, various imbalanced data handling techniques, and the sample imbalance ratio on the model’s kick detection performance are analyzed. Ablation experiments are also conducted to assess the contribution of each module in identifying kick. The results show that TimeGAN outperforms other imbalanced data handling techniques. The accuracy, recall, precision, and F1-score of the kick identification model are highest when the sample imbalance ratio is at 1 but decrease as the imbalance ratio increases. This indicates that maintaining a balance between positive and negative samples is essential for training a reliable intelligent kick detection model. The trained model is applied during the drilling of seven ultra-deep wells in Sichuan, demonstrating its effectiveness and accuracy in real-world kick detection. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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16 pages, 9520 KiB

Open AccessArticle

A Numerical Simulation of the Effect of Drilling Fluid Rheology on Cutting Migration in Horizontal Wells at Different Drilling Fluid Temperatures

by Ye Chen, Wenzhe Li, Xudong Wang, Pengcheng Wu, Xiumei Wan, Zhiqiang Wang, Jinhui Li and Xiaofeng Sun

Processes 2024, 12(11), 2428; https://doi.org/10.3390/pr12112428 - 4 Nov 2024

Viewed by 994

Abstract

In recent years, significant breakthroughs have been made in the exploration of deep to ultra-deep oil and gas reserves onshore in China. These conventional deep to ultra-deep reservoirs are typically buried at depths exceeding 4500 m, with bottom-hole temperatures surpassing 150 °C. The [...] Read more.

In recent years, significant breakthroughs have been made in the exploration of deep to ultra-deep oil and gas reserves onshore in China. These conventional deep to ultra-deep reservoirs are typically buried at depths exceeding 4500 m, with bottom-hole temperatures surpassing 150 °C. The high temperatures at the bottom of the well are more likely to cause deterioration in drilling fluid properties, altering its rheological properties and reducing cutting transport efficiency, which can lead to wellbore cleaning issues. In this paper, the numerical simulation method is used to analyze the influence of cutting particle size, drilling fluid flow rate, drill pipe rotation speed, and drill pipe eccentricity on the annular cutting concentration under different wellbore drilling fluid temperature conditions. The results show that at the same cutting particle size, as the drilling fluid temperature increases, the cutting concentration in the annulus increases sharply. The increase is the largest when the particle size is 3 mm, and when the drilling fluid temperature is 220 °C, the cutting concentration increases by 79.7% compared to at 200 °C and by 279% compared to at 180 °C. When the flow rate increases from 0.5 m/s to 1.0 m/s, the annular cutting concentration at drilling fluid temperatures of 220 °C and 200 °C decreases by 70.5% and 50.4%, respectively. The higher the drilling fluid temperature, the better the cutting removal effect when increasing the drill pipe rotation speed. However, when the rotation speed exceeds 120 rpm, the change in cutting concentration with increasing rotation speed becomes insignificant. When the drill pipe eccentricity is small, an increase in drilling fluid temperature leads to a significant rise in annular cutting concentration. However, when the drill pipe eccentricity is large, changes in drilling fluid temperature have a smaller impact on cutting concentration. The research findings can provide engineering guidance and theoretical support for the design of drilling fluid hydraulic parameters for cutting transport and rheological parameters in high-temperature wellbores. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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15 pages, 2821 KiB

Open AccessArticle

Intelligent Lost Circulation Monitoring Method Based on Data Augmentation and Temporal Models

by Detao Zhou, Chenzhan Zhou, Ziyue Zhang, Mengmeng Zhou, Chengkai Zhang, Lin Zhu, Qihao Li and Chaochen Wang

Processes 2024, 12(10), 2184; https://doi.org/10.3390/pr12102184 - 8 Oct 2024

Viewed by 891

Abstract

Deep and offshore drilling operations face complex geological formations, uncertain formation pressures, and narrow safety density windows, making them susceptible to lost circulation risks. To address these challenges, this paper introduces an innovative, intelligent lost circulation monitoring model that incorporates geological lithology information. [...] Read more.

Deep and offshore drilling operations face complex geological formations, uncertain formation pressures, and narrow safety density windows, making them susceptible to lost circulation risks. To address these challenges, this paper introduces an innovative, intelligent lost circulation monitoring model that incorporates geological lithology information. This model not only utilizes real-time drilling parameters, but also encodes geological information such as rock type as inputs to the model. By combining these key lithological features, the model can comprehensively assess wellbore stability and reduce the lost circulation risks. In this paper, the Conditional Tabular Generative adversarial network (CTGAN) model is used to enhance the data of small-sample risk data, which can effectively expand the data distribution space and improve the performance of the model. This paper conducts a comparative analysis of intelligent monitoring results using artificial neural networks (ANNs), long short-term memory (LSTM), and temporal convolutional networks (TCNs). The results show that the TCN achieves an identification accuracy of 93.7%. Furthermore, the analysis reveals that the inclusion of lithology information significantly enhances the model’s performance, resulting in a 7.1% increase in accuracy. The false alarm rate of the model can be reduced by 10.2%, considering the fluctuation of the logging curve caused by the on/off condition of the pump. This indicates that the introduction of lithology information and the condition of the pump on−off provide advantages in monitoring and identifying lost circulation risks, enabling a more precise assessment of wellbore stability and a reduction in lost circulation incidents. The method of lost circulation monitoring proposed in this paper provides an important safety guarantee for the oil drilling industry. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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13 pages, 2820 KiB

Open AccessArticle

Research and Application for Alternate Production Technology of Dual-Branch Horizontal Wells in an Offshore Oilfield

by Dong Zhang, Fenghui Li, Yanlai Li, Xu Zheng, Chunyan Liu, Hongjie Liu and Xiang Wang

Processes 2024, 12(8), 1753; https://doi.org/10.3390/pr12081753 - 20 Aug 2024

Viewed by 793

Abstract

Old-well sidetracking is a key method for controlling low-productivity wells in the Bohai oilfield. This study employs reservoir engineering and numerical simulation techniques to investigate the maximum drainage radius and natural coning control mechanism in heavy-oil reservoirs with bottom water. Based on these [...] Read more.

Old-well sidetracking is a key method for controlling low-productivity wells in the Bohai oilfield. This study employs reservoir engineering and numerical simulation techniques to investigate the maximum drainage radius and natural coning control mechanism in heavy-oil reservoirs with bottom water. Based on these findings, an alternate production technology was developed for dual-branch horizontal wells. The technology creates a new branch through sidetracking, connecting and isolating the old and new wellbores using a combination of wall hangers and branch guides. Initially, the old wellbore with an ultra-high water cut is temporarily sealed. When the new branch reaches a high water-cut stage, production is switched back to the old wellbore. This technology was successfully applied to three wells in the Bohai oilfield, resulting in the new branch achieving expected production levels, while reopening the old wellbore increased daily oil output by 27 m³ and reduced water cut by 5.6%. Cumulative oil production from these wells reached 95,000 m³. This technology improves well-slot resource utilization, enhances recovery rates, and has significant potential for broader application. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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19 pages, 6463 KiB

Open AccessArticle

Wellbore Temperature Prediction Model and Influence Law of Ultra-Deep Wells in Shunbei Field, China

by Zhigang Dang, Xiuping Chen, Xuezhe Yao, Zhengming Xu, Mengmeng Zhou, Weixing Yang and Xianzhi Song

Processes 2024, 12(8), 1715; https://doi.org/10.3390/pr12081715 - 15 Aug 2024

Cited by 3 | Viewed by 1415

Abstract

The reservoir in the Shunbei field is characterized by ultra-deep, ultra-high temperature, and ultra-high pressure. During the drilling process, the circulating temperature at the bottom of the well is higher than the temperature resistance of downhole instruments, which leads to frequent problems of [...] Read more.

The reservoir in the Shunbei field is characterized by ultra-deep, ultra-high temperature, and ultra-high pressure. During the drilling process, the circulating temperature at the bottom of the well is higher than the temperature resistance of downhole instruments, which leads to frequent problems of device burnout and no signal. Therefore, it is of great significance to accurately predict the wellbore temperature field of ultra-deep directional wells. In this paper, the influence of the drilling string assembly, the flow channel structure and the flow pattern on the convective heat exchange coefficient is considered. Based on the energy conservation equation, a numerical model of wellbore-formation transient heat transfer is developed. Then, the model was verified by the real data of two ultra-deep wells in Shunbei block, China, and the results showed that the prediction errors of bottom-hole temperature were all within 2%. Finally, the key factors and rules of the wellbore annulus temperature are analyzed. The results show that the bottom-hole temperature decreases with the decrease of inlet temperature, the thermal conductivity of drilling fluid, and the thermal conductivity of drill pipe, and increases with the decrease of flow rate, the density of drilling fluid, viscosity of drilling fluid, and specific heat capacity of drilling fluid. The inlet temperature has the greatest influence on the outlet temperature, and the specific heat of the pipe string has a minor influence on the wellbore annulus temperature. The research results of this paper provide an accurate wellbore temperature field prediction method for ultra-deep directional wells in the Shunbei block, China, which is of great significance for temperature-controlled drilling. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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17 pages, 11064 KiB

Open AccessArticle

Research on Structural Design and Optimisation Analysis of a Downhole Multi-Parameter Real-Time Monitoring System for Intelligent Well Completion

by Gang Bi, Shuaishuai Fu, Jinlong Wang, Jiemin Wu, Peijie Yuan, Xianbo Peng, Min Wang and Yongfeng Gong

Processes 2024, 12(8), 1597; https://doi.org/10.3390/pr12081597 - 30 Jul 2024

Cited by 1 | Viewed by 1410

Abstract

In this paper, based on electro-hydraulic composite intelligent well-completion technology, a new type of downhole multi-parameter real-time monitoring system design scheme is established. Firstly, a multi-parameter real-time monitoring system with a special structure is designed; secondly, its reliability is analysed by applying the [...] Read more.

In this paper, based on electro-hydraulic composite intelligent well-completion technology, a new type of downhole multi-parameter real-time monitoring system design scheme is established. Firstly, a multi-parameter real-time monitoring system with a special structure is designed; secondly, its reliability is analysed by applying the method of numerical simulation; finally, in order to verify the reliability of the simulation results, a principle prototype is developed, and indoor experimental tests of fluid flow are carried out. The experimental results show that the flow rate is directly proportional to the differential pressure, and when the flow rate is certain, the higher the water content, the higher the differential pressure. The indoor experimental flow rate of 400~1000 m³/d is measured with high accuracy, and the error range is within 5%. Numerical simulation and experimental results with a high degree of fit, a flow rate of 400–1000 m³/d, the two error range within 10%, the integrated flow coefficient of the experimental value is stable between 0.75–0.815, the simulation value is stable between 0.80–0.86. The mutual verification of the two shows that the flow monitoring design meets the requirements and provides a reference basis for the structural design of the intelligent, well-completion multi-parameter real-time monitoring system. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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15 pages, 4372 KiB

Open AccessArticle

Intelligent Monitoring Model for Lost Circulation Based on Unsupervised Time Series Autoencoder

by Liwei Wu, Xiaopeng Wang, Ziyue Zhang, Guowei Zhu, Qilong Zhang, Pinghua Dong, Jiangtao Wang and Zhaopeng Zhu

Processes 2024, 12(7), 1297; https://doi.org/10.3390/pr12071297 - 22 Jun 2024

Cited by 1 | Viewed by 1099

Abstract

Lost circulation, a common risk during the drilling process, significantly impacts drilling safety and efficiency. The presence of data noise and temporal evolution characteristics pose significant challenges to the accurate monitoring of lost circulation. Traditional supervised intelligent monitoring methods rely on large amounts [...] Read more.

Lost circulation, a common risk during the drilling process, significantly impacts drilling safety and efficiency. The presence of data noise and temporal evolution characteristics pose significant challenges to the accurate monitoring of lost circulation. Traditional supervised intelligent monitoring methods rely on large amounts of labeled data, which often do not consider temporal fluctuations in data, leading to insufficient accuracy and transferability. To address these issues, this paper proposes an unsupervised time series autoencoder (BiLSTM-AE) intelligent monitoring model for lost circulation, aiming to overcome the limitations of supervised algorithms. The BiLSTM-AE model employs BiLSTM for both the encoder and decoder, enabling it to comprehensively capture the temporal features and dynamic changes in the data. It learns the patterns of normal data sequences, thereby automatically identifying anomalous risk data points that deviate from the normal patterns during testing. Results show that the proposed model can efficiently identify and monitor lost circulation risks, achieving an accuracy of 92.51%, a missed alarm rate of 6.87%, and a false alarm rate of 7.71% on the test set. Compared to other models, the BiLSTM-AE model has higher accuracy and better timeliness, which is of great significance for improving drilling efficiency and ensuring drilling safety. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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