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Processes
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Development of Advanced Drilling Engineering
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Development of Advanced Drilling Engineering

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: 15 May 2026 | Viewed by 1649

Special Issue Editor

Dr. Yuqiang Xu

E-Mail Website
Guest Editor
School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Interests: drilling engineering design; drilling risk control; wellbore integrity evaluation and control; intelligent drilling and completion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The energy industry is constantly evolving, with drilling engineering at the forefront of this transformation. This Special Issue focuses on the latest advances in advanced drilling engineering, particularly in deep-water, deep-earth, and unconventional oil and gas drilling, and intelligent drilling engineering.

Deep-water drilling has advanced significantly, enabling access to previously untapped resources in the ocean. The successful drilling of wells in ultra-deep waters, such as China’s attempt in the South China Sea, exemplifies the technological capabilities now available. Additionally, deep-earth drilling, as demonstrated by the completion of the 10910-meter-deep Well Shendi-Tak1 in China, has broken new ground in exploring the Earth's interior.

Additionally, more research efforts are being directed towards unconventional oil and gas drilling, crucial for energy diversification, and intelligent drilling engineering, which has the potential to enhance efficiency and safety. We welcome contributions that present novel concepts, research findings, and case studies in these areas.

This Special Issue, “Development of Advanced Drilling Engineering”, seeks high-quality papers on drilling engineering research. Topics of interest include, but are not limited to, the following:

  • Energy industry;
  • Drilling engineering;
  • Advanced drilling;
  • Deep-water drilling;
  • Deep-earth drilling;
  • Unconventional oil and gas drilling;
  • Intelligent drilling engineering;
  • Drill cuttings disposal;
  • Environmentally friendly drilling fluids.

Dr. Yuqiang Xu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • advanced drilling engineering
  • deep-water/deep-earth drilling
  • unconventional oil and gas drilling
  • intelligent drilling technology

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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16 pages, 1310 KB  
Article
Intelligent Monitoring of Lost Circulation Risk Based on Shapelet Transformation and Adaptive Model Updating
by Yanlong Zhang, Chenzhan Zhou, Gensheng Li, Chao Fang, Jiasheng Fu, Detao Zhou, Longlian Cui and Bingshan Liu
Processes 2025, 13(12), 3981; https://doi.org/10.3390/pr13123981 - 9 Dec 2025
Viewed by 194
Abstract
As unconventional hydrocarbon resources gain increasing importance, the risk of lost circulation during drilling operations has also grown significantly. Accurate and reliable risk diagnosis methods are essential to ensure safety and operational efficiency in complex drilling environments. This study proposes a novel lost [...] Read more.
As unconventional hydrocarbon resources gain increasing importance, the risk of lost circulation during drilling operations has also grown significantly. Accurate and reliable risk diagnosis methods are essential to ensure safety and operational efficiency in complex drilling environments. This study proposes a novel lost circulation risk monitoring framework based on time-series shapelet transformation, integrated with Generative Adversarial Network (GAN)-based data augmentation and real-time model updating strategies. GANs are employed to synthesize diverse, high-quality samples, enriching the training dataset and improving the model’s ability to capture rare or latent lost circulation signals. Shapelets are then extracted from the time series using a supervised shapelet transform that searches for discriminative subsequences maximizing the separation between normal and lost-circulation samples. Each time series is subsequently represented by its minimum distances to the learned shapelets, so that critical local temporal patterns indicative of early lost circulation can be explicitly captured. To further enhance adaptability during field applications, a real-time model updating mechanism is incorporated. The system incrementally refines the classifier using newly incoming data, where high-confidence predictions are selectively added for online updating. This strategy enables the model to adjust to evolving operating conditions, improves robustness, and provides earlier and more reliable risk warnings. We implemented and evaluated Support Vector Machine (SVM), k-Nearest Neighbors (kNNs), Logistic Regression, and Artificial Neural Networks (ANNs) on the transformed datasets. Experimental results demonstrate that the proposed method improves prediction accuracy by 6.5%, measured as the accuracy gain of the SVM classifier after applying the shapelet transformation (from 84.7% to 91.2%) compared with using raw, untransformed time-series features. Among all models, SVM achieves the best performance, with an accuracy of 91.2%, recall of 90.5%, and precision of 92.3%. Moreover, the integration of real-time updating further boosts accuracy and responsiveness, confirming the effectiveness of the proposed monitoring framework in dynamic drilling environments. The proposed method offers a practical and scalable solution for intelligent lost circulation monitoring in drilling operations, providing a solid theoretical foundation and technical reference for data-driven safety systems in dynamic environments. Full article
(This article belongs to the Special Issue Development of Advanced Drilling Engineering)
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21 pages, 8836 KB  
Article
Strain-Softening-Based Elliptical Wellbore Model for Horizontal In-Situ Stress Prediction and Wellbore Stability Analysis in the Wujiaping Formation of Kaijiang-Liangping Block, Eastern Sichuan Basin, Sichuan Province
by Xinrui Yang, Qiang Wang, Ji Xu, Meng Li, Kanhua Su, Qian Li, Liangjun Xu, Qiang Pu, Guanghui Shi, Wen Tang, Chen Jing, Bo Xu and Qifeng Qin
Processes 2025, 13(10), 3326; https://doi.org/10.3390/pr13103326 - 17 Oct 2025
Viewed by 366
Abstract
Marine shale is highly prone to wellbore collapse due to its high pore pressure, propensity for hydration and swelling, distinct bedding planes, and low tensile strength. Horizontal in situ stress serves as a critical parameter for wellbore stability analysis; however, its accurate prediction [...] Read more.
Marine shale is highly prone to wellbore collapse due to its high pore pressure, propensity for hydration and swelling, distinct bedding planes, and low tensile strength. Horizontal in situ stress serves as a critical parameter for wellbore stability analysis; however, its accurate prediction is extremely challenging in complex geological environments. Conventional studies often simplify the wellbore as a circular shape, neglecting its natural elliptical deformation under non-uniform in situ stress, which leads to reduced predictive accuracy. To address this limitation, this study establishes an elliptical wellbore model that incorporates the strain-softening characteristics of shale. Theoretical models for stress distribution in both elastic and plastic zones were derived. The strain-softening behavior was validated through triaxial compression tests, providing a foundation for analytical solutions of stress distributions around circular and elliptical wellbores. Furthermore, an elliptical wellbore-based model was developed to derive a new prediction equation for horizontal in situ stress. Numerical programming was employed to compute stress distributions, and finite element simulations under various aspect ratios corroborated the theoretical results, showing excellent agreement. Results demonstrate that the elliptical wellbore model captures the near-wellbore stress state more accurately. As the aspect ratio increases, the extreme values of radial and tangential stresses increase significantly, with pronounced stress concentrations observed around the 180° and 360° positions. Predictions of horizontal in situ stress based on the proposed model achieved over 89% accuracy when verified against field data, confirming its reliability. This study overcomes the limitations inherent in the traditional circular wellbore assumption, providing a more precise analytical method for wellbore stability assessment in Marine shale under complex geological conditions. The findings offer a valuable theoretical basis for wellbore stability management and drilling engineering design. Full article
(This article belongs to the Special Issue Development of Advanced Drilling Engineering)
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Review

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19 pages, 1827 KB  
Review
Rotary Steerable Drilling Technology: Bottlenecks Breakthroughs and Intelligent Trends in China Shale Gas Development
by Hao Geng, Bingzhong Zhang and Yingjian Xie
Processes 2025, 13(11), 3471; https://doi.org/10.3390/pr13113471 - 29 Oct 2025
Viewed by 831
Abstract
Rotary Steerable System (RSS) enhances directional drilling efficiency by over 300% via dynamic bit adjustment during string rotation. This study aims to systematically address these bottlenecks, quantify technical boundaries, and propose actionable breakthrough paths for China’s RSS technology in shale gas development. To [...] Read more.
Rotary Steerable System (RSS) enhances directional drilling efficiency by over 300% via dynamic bit adjustment during string rotation. This study aims to systematically address these bottlenecks, quantify technical boundaries, and propose actionable breakthrough paths for China’s RSS technology in shale gas development. To address China’s shale gas RSS bottlenecks, this study proposes a “Material-Algorithm-System” tri-level strategy centered on an innovative “Tri-loop System.” Key innovations include (1) silicon nitride–tungsten carbide composite coatings to enhance thermal resilience, tested to withstand 220 °C, reducing thermal failure risk by 40% compared to conventional materials; (2) downhole reinforcement learning optimization; (3) a “Tri-loop System” integrating downhole intelligent control, wellbore-surface bidirectional communication, and cloud monitoring, shortening downhole command response latency from over 5 s to less than 1 s. In practical shale gas development scenarios—such as the Sichuan Basin’s deep coalbed methane wells and Shengli Oilfield’s tight reservoirs—this tri-level strategy has proven effective: the high-frequency electromagnetic wave radar increased thin coal seam drilling encounter rate by 23%, while the piezoelectric ceramic micro-actuators reduced tool failure rate by 35% in 175–200 °C environments. This approach targets raising China’s shale gas RSS application rate to 60%, supporting sustainable oil and gas exploration. Full article
(This article belongs to the Special Issue Development of Advanced Drilling Engineering)
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