bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and Application of Tail Gas Oxidation-Absorption Technology Combined with Claus Process for Natural Gas Purification
Authors: Tang Quanwu , Li Jing , Fu Jingqiang , Fan Rui , Hu Chao , Lai Bing , Ma Yue , Li Mingsong , Che Peiyuan , Chen Tianxin 
Published: February 2025

Abstract
Natural gas consumption is growing around the world, thereby natural gas purification becomes increasingly important. Claus process is an industrialized sulfur recovery system to convert hydrogen sulfide (H2S) to sulfur, but there would be huge sulfur dioxide (SO2) emissions. To lower SO2 emissions of the tail gas from natural gas purification, an innovative tail gas oxidation-absorption technology in combination with Claus process has been developed and applied in Petrochina Southwest Oil & Gas Field Company, China. In this paper, the tail gas oxidation-absorption technology combined with Claus process was described in detail, and key operation parameters namely burner temperature, oxygen volume fraction of the burner, concentrations of the amine-based SO2 absorbent, pH of lean amine solution and molar rate of the amine-based SO2 absorbent versus heat stable salts were studied and analyzed in an industrial-scale. The key operation parameters were optimized as follows. The tail gas of Claus process was burned at 810±5℃ with a burner, and the oxygen volume fraction of the burner was controlled between 3.3v% and 3.7v%. The amine-based SO2 absorbent concentration varied between 21w% and 25w%. The pH of lean amine solution was confirmed from 5.0 to 5.7. Besides, extremely the molar rate of the amine-based SO2 absorbent versus heat stable salts was controlled between 10:14 and 10:11. Consequently, the SO2 emissions can achieve below 100mg/m3, which was much better than the SO2 discharge standard of natural gas purification plants (GB39728-2020) in China. This was helpful for exploiting high-sulfur natural gas and reducing the SO2 emission from natural gas processing in the world.
Improvement of Well Positioning Using Multi-Attributes as Principal Tools for Lithology Prediction and Reservoir Characterization: A Malaysia X Field Case Study
Authors: Tan S. , Fahmi F. , Zainuddin N. , Yong C. , Pezzoli M. , Jacob C. , Chen S. 
Published: February 2025

Abstract

Objective/Scope
This paper presents a case study that focuses on the seismic reservoir characterization in the X field located in the Balingian province, approximately 200 km offshore, Sarawak.
Understanding the subsurface geology is essential for oil and gas exploration because it directly impacts the effectiveness of exploration and production efforts. In the case of the X field, the interpretation of its depositional setting required a comprehensive approach, which integrated various data sources, specifically 3D seismic multi-attributes and well log data. The use of 3D seismic data provides a volumetric view of the subsurface, allowing geoscientists to visualize geological structures and stratigraphy. Multi-attributes from seismic data, such as acoustic impedance, Vp/Vs ratios, and total sand probability, enhance the interpretation by revealing variations in lithology and fluid content. These attributes help to identify potential reservoirs and understanding of their spatial distribution. In greenfield developments, particularly when the number of wells is limited, significant challenges such as reservoir distribution and prediction of fluids in reservoirs must be considered. Limited well data typically restricts the understanding of reservoir properties to localized areas, complicating the extrapolation of these findings across the entire field. Consequently, the integration of well logs and 3D seismic data is essential for characterizing reservoir complexity beyond the well locations. While well logs deliver required insights into the physical properties of rocks and fluids at specific sites, their coverage is confined to small segments of the reservoir. Therefore, integrating seismic data becomes important because, it allows for the inference of reservoir characteristics in the gaps between wells, leading to a more comprehensive understanding of the subsurface.
A Total Optimization Drilling System Approach Delivering a Critical Build-Up Section in the Middle East
Authors: Bashir M. , Algaiar M. , Farhat M. , Al Dhamen A. , Alohaid A. 
Published: February 2025

Abstract
Wellbore stability, stuck pipe, trajectory control, drilling vibrations, downhole tools failure, low rate of penetration, hole condition, and running the production liner to bottom are the most common challenges while drilling a critical directional build-up section of a major oil field in the Middle East. This results in increasing the non-productive time and elevated drilling costs. To improve this section deliverability, a cross discipline approach was implemented to improve the drilling efficiency and help running the production liner successfully to the planned target depth.
An integrated drilling engineering, geomechanics, directional drilling, drilling fluids, and drill bits team was assembled to address the section challenges by thoroughly analyzing the offset wells hazardous drilling events, optimizing the well trajectory and bottom-hole assembly design. The team further constructed geomechanics wellbore stability model and recommended the optimal mud weight window. This study was coupled with enhanced drilling fluids solutions and novel bit design based on the rock mechanical and petrophysical data. In addition, the integrated approach called for Realtime formation evaluation, equivalent circulating density monitoring, hole cleaning efficiency monitoring, and drill string vibrations monitoring along with torque and drag analysis each stand drilled in the execution phase.
The firm implementation of the integrated approach helped delivering the preset run objectives including reaching the section target depth without wellbore stability issues, significantly reducing the drill string vibrations thus saving the directional tools and allowing drilling the section in a single run. The run also achieved a record penetration rate (ROP) with 36% increase over the average field ROP record. The optimized connection time and downlinking schedule as well as the minimized back reaming intervals resulting from the stable wellbore saved more than 60 hours of rig time compared to the planned target time and helped running the production liner successfully to bottom.
The pre-planning study including the wellbore instability analysis, integrated roadmap, real-time monitoring, post-drill evaluation and outcomes are all presented in this paper to serve as evidence on the importance of integrated multi-disciplinary approach to improve drilling efficiency and reduce drilling costs in challenging drilling environments.
Navigating High-Pressure Realms: The Synergistic Application of Instrumented Coiled Tubing and Through Tubing Inflatable Packers for Well Integrity Restoration in West Kuwait Workovers: A Novel Case Study
Authors: Slama Mohamed Hedi , Bu-Mijdad Mohammed Moussa , Badrawy Kareem , Sunagatov Rustem , Sebaih Mohannad Adel , Fajardo Sergio Rondon , Al-Yahya Mohammed Mosa'ad , Al-Adwani Mubarak Jaber , Regaey Mohsen , Al-Hamdan Abdulaziz , Yakubu Victor Adinoyi , Shadad Nawaf Bader , Ali Al-Obaidly Mubarak Mohammed , A/Gawad Adel 
Published: February 2025

Abstract
This paper aims to introduce an avant-garde strategy to uphold well integrity amidst workover rig interventions. By harnessing cutting-edge instrumented coiled tubing (CT) and through tubing inflatable retrievable packer (TTIRP) technologies, this study addresses high-pressure and sour terrains in West Kuwait, elucidating the pivotal role such technologies in restoring well functionalities.
The intervention approach employed the utilization of instrumented CT for well conditioning and temporary well suspension, utilizing real-time downhole telemetry to ensure accurate placement and setting of the TTIRP within the production liner close to the uncased reservoir section. Following successful anchoring of the TTIRP, the CT was disconnected from the packer assembly and a sand plug was utilized to protect the fishing neck. The CT was then retrieved to the surface, and a slickline dump bailer was utilized to spot cement on top of the sand plug. Once the cement had set, the CT was run to displace the wellbore with kill fluid. Upon confirmation of re-established barriers in the well, the workover rig was utilized to remove the failed Christmas tree and install the BOP. The CT was then rigged up and run back-in-hole to mill the cement plug, circulate out the sand, and retrieve the TTIRP to the surface.
The subject well, drilled in 1998, presented a significant challenge with a maximum potential wellhead pressure of nearly 8,000 psi and a plug-back true depth of around 13,400 ft. The well was completed with 3 1/2-in. production tubing set close to 11,800 ft MD, a 5-in liner until 12,900-ft and a 4-1/2-in uncased openhole section until PBTD. The reservoir pressure was close to 9,300 psi. The utilization of instrumented CT and high-pressure rotary jetting tool enabled a thorough well circulation and the conditioning of the setting depth of the TTIRP resulting in a shut-in wellhead pressure of 4,500 psi throughout the intervention.
The outcomes garnered from this groundbreaking intervention protocol, especially in such volatile high-pressure and sour settings, are seminal for effective well workovers. The synergistic alignment of instrumented CT and TTIRP remains central in adeptly sealing off the reservoir section. The lessons learned from this case study serves as a valuable reference for operators in the Middle East with analogous well complexities.
Key Techniques of Ultra-Low Signal to Noise Ratio Data Processing, a Case Study in Sarawak, Malaysia
Authors: Du H. , Zhang H. , Chen Y. , Ru C. Siu , Isa B. Bin , Ming T. Tai 
Published: February 2025

Abstract
Seismic exploration in coastal areas often encounters significant challenges due to complex near-surface conditions. In areas such as Sarawak, Malaysia, these challenges are exacerbated by rapid changes in the thickness of weathered layers, geological irregularities, and variations in near-surface velocities, all of which contribute to severe seismic data distortions. Such degradation in data quality can complicate static corrections and velocity picking during processing, potentially resulting in "no data" zones. Such distortions increase the risk of misinterpretation, ultimately impeding effective hydrocarbon exploration and production.
Conventional seismic processing methods have not fully addressed these issues in Sarawak, leading to suboptimal exploration outcomes. The legacy processing results from this region exhibit a lack of clarity in the structural imaging, and in many cases, entire sections are devoid of usable seismic reflections. The complex near-surface conditions caused significantly both long-wavelength and short-wavelength static correction challenges and the absorption effects of inconsistent wavelet behavior, while the extremely low signal-to-noise ratio further complicates accurate subsurface interpretation.
To address these challenges, this paper presents a new reprocessing approach that integrates advanced tomographic static correction, relative amplitude preserved denoising techniques, and combined surface-consistent processing to tackle inconsistencies of wavelet in Sarawak. By focusing on issues related to statics, wavelet consistency, and signal-to-noise ratio, this study demonstrates that these methods can significantly enhance subsurface imaging accuracy, supporting more reliable exploration in the region.
A Report Generation System for Well Logging Industry Based on Large Language Model and Retrieval Augmented Generation
Authors: Li Pin , Liu Yubo , Zhou Jun , Zhang Juan , Zhou Yuange 
Published: February 2025

Abstract
In the well logging industry, interpretation reports are critical for evaluating subsurface geological conditions, yet their preparation is often time-consuming and inconsistent due to reliance on human experts. This paper presents a novel methodology that leverages the generative capabilities of large language models (LLMs) to automate the creation of well logging interpretation reports, significantly improving efficiency. Central to our system is an LLM-based content generation module that sources and composes report sections. To address data privacy and cost concerns, we utilize open-source LLMs deployed locally. Recognizing the limitations of general LLMs in handling field-specific inquiries, retrieval-augmented generation (RAG) framework is employed to integrate well logging domain knowledge, ensuring contextually relevant outputs. Through experimentation, it is found that prompt phrasing significantly influences LLM performance, prompting the use of prompt engineering techniques to optimize results. A blind review of 100 generated reports by well logging experts demonstrates the system's ability to produce complete, clear and coherent reports. These findings highlight the transformative potential of customized LLMs, capable of generating reports in just 10 minutes—compared to 4 hours manually—thereby revolutionizing labor-intensive processes and significantly improving work efficiency in the well logging industry.
Field-Testing Verified Digital Models for Monitoring Drillstring Fatigue Induced by Rotating-Bending, Vibration, and Stick-Slip
Authors: Yang B. , Chen W. , Du M. H. , Irsa G. , Virene P. , Bandi M. , Mohd Najmi N. Fahusnaza Nik 
Published: February 2025

Abstract
Fatigue life of a drillstring is affected by rotating-bending, vibration, and stick-slip during field operations. Tracking the drillstring fatigue life to accurately determine the remaining useful life (RUL) is critical in the prognostic health management (PHM) of the drillstring. It will provide a quantified basis to help prevent costly downhole drillstring failures, improve drilling efficiency, and implement a condition-based maintenance program.
Digital models are created to monitor the drillstring fatigue life during downhole operations. In the process, the operation data are used as the inputs to a finite element analysis (FEA) -based module of the digital models to calculate the downhole dynamic parameters. These parameters are then used to evaluate the fatigue life of the drillstring consumed by rotating-bending, vibration, and stick-slip. For rotating-bending fatigue, FEA is used to simulate component stress/strain distribution, and the strain-based Coffin-Manson method is applied to calculate the fatigue life. The vibration-induced fatigue is evaluated by generating different vibration modes and simulating the final fatigue damage by combining these modes according to field run parameters. The stick-slip-induced fatigue is calculated by correlating the stick-slip levels with baseline torque. The total fatigue damage to the component is obtained by integrating all these three fatigue estimation results based on the failure modes of the component.
The digital models were applied with eight drillstrings for more than 50 field runs. A fatigue-prone component of the hydraulic jar in the drillstring was used as an example to simulate the fatigue accumulative history from its brand-new state to the final fatigue failure. These cases covered the scenarios of fatigue failures induced by rotating-bending, vibration, and stick-slip. Among all these cases, more than 80% of the failures happened when the simulated RUL was less than 30%. Rotating-bending fatigue accounts for 14% of all related failures, vibration fatigue for 51%, and stick-slip fatigue for 35%. It was also found that at least 75% of the failures can be prevented through tracking the fatigue induced by rotating-bending, vibration, and stick-slip.
The digital models developed through this work help improve the drillstring operation reliability and prevent costly downhole tool failures while maximizing the asset usage, which also enhances the operation sustainability. The methodology can be populated to other components across the drillstring and improve the total PHM processes of the operations.
Efficient Surrogate Modeling for Subsurface Flow Simulation Using Multi-Fidelity Data with Physical Constraints
Authors: Cui Jiawei , Sun Wenyue , Li Hangyu , Liu Shuyang 
Published: February 2025

Abstract
In subsurface flow simulation, data-driven deep learning surrogate models have emerged as a promising alternative to traditional simulation methods. However, a major challenge is the large amount of high-fidelity simulation data required for training, and purely data-driven flow surrogate models often lack theoretical support, limiting their applicability to engineering problems. In this study, we propose an efficient surrogate model construction method that integrates physical constraints and multi-fidelity training data. The process begins with pre-training a deep learning model using a large amount of low-cost, low-fidelity data to effectively initialize network parameters. The pre-trained model is then fine-tuned with a smaller amount of high-fidelity data. Throughout the training, physical losses constrain the model to adhere to physical principles. For the case considered here, this approach reduces the need for high-fidelity data by approximately 83% compared to traditional training methods without compromising predictive accuracy. Additionally, incorporating physical loss during model training e ffectively enhances the surrogate model's predictive accuracy, with physical loss reduced by nearly 70% compared to purely data-driven training. The method employs the Jacobian matrix to aid in model training, significantly reducing the computational cost of physical losses. Overall, this surrogate model construction method addresses the challenges of obtaining training data and the lack of physical support in surrogate models, providing reliable support for complex reservoir development decisions.
Fast AI Fault Prediction Using Sparsely Interpreted Labels
Authors: Xiong Wei , Li Lei , Cui Jingbin , Zhang Xiaofang , Dai Lihua , Xu Chen 
Published: February 2025

Abstract
Faults play a crucial role in the exploration and development of oil and gas resources. In recent years, deep learning algorithms for fault interpretation have shown signs of progress and are still in a rapid development stage. Since most of the research at this stage uses 3D synthetic data, ignoring the complex geological structure of the field data. This paper focus on the training data issue, using true fault sticks as labels. An interactive training data generation tool is utilized to automatically establish pairs of seismic data and fault labels, forming a 2D training data set characterized by local fault features. In the model training phase, a lightweight 2D UNETR++ architecture is trained using 2D true data to enhance fault recognition accuracy. Additionally, to tackle the problem of discontinuities results from 2D training data, an optimized U-Net model is used to improve the continuity. The proposed intelligent fault prediction method based on real labels can be applied for rapid prediction and identification of major faults, offering reliable data for automated fault interpretation and subsequent structural modeling.
Enhancing Sustainable Water Management in Hydraulic Fracturing with Degradable Fiber Integration
Authors: Khetib T. , Annane B. , Khelkhal H. , Glaznev I. , Enkababian P. 
Published: February 2025

Abstract
This study investigates the application of degradable fibers in hydraulic fracturing to improve fluid efficiency, reduce leak-off, and enhance effective fracture conductivity across various well and reservoir conditions. By incorporating Fracturing Loss Additives (FLAs) such as degradable fibers into the PAD stage, this research demonstrates significant reductions in leak-off coefficients and increased fluid efficiency, allowing more efficient use of fracturing fluids and supporting better proppant placement within the fractures. Five wells within distinct locations lithologies, fluid types, and fracture parameters were analyzed, and fiber concentrations were tailored to specific conditions. Results show that fluid efficiency improved by up to 30%, and effective conductivity gains were observed in most cases. The introduction of degradable fibers also led to an average water reduction of 20-30%, contributing to sustainability by enabling operators to achieve desired fracturing outcomes with reduced water usage. This study highlights the potential of degradable fibers to optimize hydraulic fracturing operations by maximizing fluid preservation and enhancing fracture performance, thereby offering a sustainable alternative for resource conservation in hydraulic fracturing operations.
Synergizing Planning and Technology: Achieve World-Class Drilling Performance: A Suriname Deep-Water Exploration Project Case Study
Authors: Norani M. R. , Ezzaty N. , Hafizi R. M. , Abidin F. Z. , Salleh M. N. , Wahab A. A. , Ibrahim A. S. , Moran L. A. , Johnston D. , Ramroop V. , Pariag E. , Mendes A. , Daniel N. A. , Rambaran K. , Millan A. J. , Huang W. , Noronha M. , Kumar A. , El-Khoury J. , Gendur J. , Martinez A. , Velez E. I. , Restrepo J. , Hayson L. , Espinola B. 
Published: February 2025

Abstract
PETRONAS Suriname explored for oil in Block 52 in the deep waters off Suriname. This block covers an area of 4,749 km2. The project, located north of Paramaribo, Suriname's capital city, within the prospective Suriname-Guyana basin, contains three wells. The project required drilling 5-km-deep exploration wells to gather essential subsurface data. The data will serve to determine the existence of oil and the length of the prospective oil reservoir.
The engineering design and implementation stages involved many challenges because the offset wells in nearby blocks experienced well control incidents, low rate of penetration (ROP), stuck wireline string events due to unconsolidated sands, and wellbore instability issues. All of these issues were major obstacles from planning and execution perspectives.
The engineering team, along with the integration service provider, collaborated in the design phase and used innovative engineering solutions for bit selections, bottomhole assemblies design, and optimum drilling fluid selection along with the use of the latest technologies for formation evaluation. Each component of the well design was analyzed to ensure optimum design and a safe operational limit with extensive risk assessment of all potential hazards along with prevention and alleviation plans.