bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling of Chemical Tracer Transport Through a Reduced-Dimension Solution for Analysis of Single-Well Tracer Tests
Authors: Velasco-Lozano Moises , Balhoff Matthew T. 
Published: September 2024

Abstract
Modeling tracer transport in petroleum reservoirs is an important technique for accurately estimating residual oil saturation, characterizing high-conductivity pathways, and determining well connectivity. Single-well tracer tests (SWTTs) are essential for evaluating the sweep efficiency of conventional and enhanced oil recovery (EOR) methods, as they allow for the rapid quantification of oil displacement near the injector well, thereby assessing both technical and economic aspects before implementing a field-scale recovery plan. However, current methods for examining SWTTs rely on time-consuming numerical simulations that require significant expertise. In this work, we introduce a novel two-dimensional solution for modeling the flow of chemical tracers in SWTTs, representing the first mathematical approach that enables real-time, field-scale tracer transport modeling.
Our model is derived through the analysis of tracer flow in porous media, utilizing a key transformation variable to convert the classic two-dimensional differential equation into a novel one-dimensional expression equivalent to solute transport in single-phase flow. This mathematical approach incorporates an approximated full hydrodynamic dispersivity term to account for mechanical and molecular dispersion mechanisms, resulting in an accurate estimation of tracer advance in the x - y directions as a function of the steady-state velocity field. We validated our two-dimensional solution by comparing it against multiple numerical SWTT simulations under conditions of residual oil saturation, demonstrating that the model achieves an error of less than 3 feet in estimating the location of tracer slugs. Our approach provides a practical, real-time tool for approximating tracer flow and location in the reservoir, significantly reducing the number of initial simulations required to evaluate tracer properties before building robust reservoir models for heterogeneous systems. We believe that this model serves as a valuable tool for rapid tracer transport analysis and enhances the efficiency of field-scale recovery planning
Cost-Effective Sealing of Geothermal Wells by Modifying Existing Elastomers
Authors: Liu S. , Taleghani A. Dahi 
Published: September 2024

Abstract
Sealing a geothermal well has been a challenging problem due to high temperatures surrounding the well, which may induce thermal deformation and degradation to the constituent polymer of a seal, impairing the hydraulic integrity of the well and thus reducing the thermal energy production of the well. To address this issue, this study focuses on developing an advanced nano-reinforcement technique to create thermally resistant polymer nanocomposites for sealing geothermal wells. The surface property of graphite nanoplatelets (GNPs) is improved via acid functionalization introducing stable carboxyl (-COOH) groups. Subsequently, polymeric nanocomposites are synthesized by respectively compounding various concentrations, namely 1.5 wt.%, 3.0 wt.%, 6.0 wt.%, and 9.0 wt.%, of modified GNPs with ethylene propylene diene monomer (EPDM). The compounding method enables GNPs’ dispersion within the EPDM matrix and GNPs’ connection to the matrix. It is found that incorporating 6.0 wt.% of modified GNPs increases the high-temperature storage modulus of EPDM by up to 210.11% and enhances the loss modulus by 156.27%. Compared to pure EPDM, the developed nanocomposites demonstrate superior deformation resistance by effectively dissipating energy. Furthermore, the nanocomposite containing 6.0 wt.% of GNPs possesses noticeably higher thermal stability than pure EPDM. These findings suggest that this prepared nanocomposite holds significant potential as a sealing material for geothermal wells.
A Sustainable Path Forward: Delivering Canada’s Longest Montney Lateral
Authors: Garda I. 
Published: September 2024

In pursuit of the reduction of environmental impact and increased cost effectiveness, drilling operations in the Western Canadian Sedimentary Basin (WCSB) face the unique challenge of increasing total drainage out of each surface location while reducing land impact. A major unconventional oil and gas operator and a directional drilling service provider have partnered to consistently extend lateral section lengths over 5 km and to drill the longest lateral in Canada’s Montney Play to date.
The major E&P company and the service provider had delivered the first 5 successful wells with aRotary Steerable System (RSS) in 2022, having drilled the operator’s longest and fastest Montney well to date, comprised of 4734m. To consistently cross the 5km mark in the 2023 drilling campaign, both companies worked together in vibration mitigation techniques, tool ruggedness, bit selection, drillstring optimization, mud properties and utilization of vibration mitigation tools, both axial and torsional. A data-based, engineered, well-by-well strategy was customized for each of the 4 distinctive targets within the Montney formation, based on previous and current campaign findings.
Through the analysis of previous 2022 drilling campaign and development of the 2023 campaign, twomain vibration mechanisms are identified as performance limiters and affecting reliability. The ability of the RSS to measure real-time High Frequency Torsional Oscillation (HFTO), one of the most damaging mechanisms in modern drilling,is utilized to reduce risk of tool damage in hard formations as the Montney. Furthermore, the analysis of high frequency vibration data is utilized to challenge the effectiveness of different types of vibration mitigation tools. The impact of mud properties in bit cutting structure,weight transfer and RSS functionality are evaluated in real time with Pressure While Drilling sensors.
The article describes the use of this data to modify tool configuration, BHA, and vibration mitigation tool selection. This led to the achievement of the longest lateral section in all Canada’s Montney Play with 5287 meters, along with the longest RSS run in the Montney and the longest global run for this 4.75" RSS with 5125m. In addition to the increase in reach, performance has allowed to reduce cost per meter drilled by 12%.
Ability to measure HFTO in real time increases awareness against damaging vibration within modern drilling applications. Furthermore, high-frequency 3-axial recorded vibration data allows for re-evaluation of the effects that vibration mitigation tools have in the BHA under specific circumstances.
The paper confirms the feasibility of extended lateral length benchmarks in the Montney, not achievable years ago due to tool reliability impacting overall project costs. Consistently delivering laterals over 5,000m aids the sustainability of Oil&Gas development projects in culturally sensitive areas where surface location construction and access is under increased restriction.
Textual Data Augmentation for NER in Geosciences with LLMs
Authors: Maze Elie , Farahbakhsh Reza , Barrallon Pierre-Emmanuel , Jallais Pierre 
Published: September 2024

Abstract
Named Entity Recognition (NER) is a classic natural language processing task which aims to extract relevant and domain-specific information (e.g. meta data) from textual data. To that end, the key is to have enough labeled data for the entities we are interested to extract, and labeling sufficient domain-specific is challenging and costly especially in geoscience domains. One of the promising techniques to increase the volume of the labels is to rely on data augmentation techniques and there are several approaches to be explored on this direction. One of the directions is relying on Large Language Models (LLMs) which has recently shown promising advancement in different domains including data augmentation. Leveraging LLMs through prompt engineering or retrieval-augmented generation (RAG) based to overcome labelling difficulties for the NER task in Geoscience data is the focus of this study.
The Technology of Magnetic Subs for Downhole Scale Mitigation
Authors: Schlüter H. E. P. , Castro B. B. , de Oliveira F. S. , de Magalhäes J. V. M. , de O. Junior A. F. M. , Fontes R. A. , da Silva P. M. D. , Martins A. L. 
Published: September 2024

Abstract
Inorganic scale is a relevant cause for production losses in offshore operations. In the development of pre-salt fields calcium carbonate crystallization, especially when the flow is submitted to abrupt depressurization, often cause problems in reservoir selectivity and production string obstruction. The conventional strategy for this kind of problem is to continuously inject chemicals to prevent precipitation. The low reliability of injection devices, which frequently fail, and the possibility of adopting downhole completion configurations which do not allow injection at the lower zones stimulated the industry to search for alternative mitigation strategies.
The use of magnetic fields to help in minimizing the adhesion of calcium carbonate crystals to downhole surfaces. The proposed mechanisms include the effect of the magnetic field in generating fewer adhesive polymorphs (vaterite) in relation to the more stable ones (calcite). A discussion on this topic has been widely addressed in the literature. The goal of the present article is to describe the construction of real scale prototypes of a magnetic sub, a device to be attached to the production string to generate the necessary magnetic field to achieve the scale mitigation requirements. The strategy for magnetic and mechanical design is described.
In addition, a protocol to establish the strategy for field installation in a field development project is detailed. The focus is to equip a given well with several subs and compare the production records with a correlation well with no subs installed. Finally, an update of the status of field installations is presented, with the proposed evaluation methodology customized for each field.
Research on the Effects of re-employment on Active Healthy Aging in China
Authors: Hongqin Zhang , Zepeng Li , Junhan Zhou 
Published: September 2024

Abstract

With the rapid development in China, the population aged over 60 has exceeded 290 million in China. It’s an important group that cannot be ignored in society. A proportion of them choose to re-enter the workforce after retirement. What is the impact of re-employment of the elderly on Active Healthy Aging (AHA)? There is an urgent need to establish metrics for measuring Active Healthy Aging (AHA) and to understand the willingness of Chinese elderly individuals to re-enter the workforce. These efforts aim to provide a solid theoretical foundation for promoting healthy aging in China. Building on the latest definitions from the World Health Organization (WHO) regarding healthy aging, this article utilizes data from the China Health and Retirement Longitudinal Study (CHARLS) database and macroeconomic data from provincial-level statistics in China. Employing the entropy method, a framework for Active Healthy Aging Indicators (AHAI) is constructed, comprising three primary indicators, 14 secondary indicators, and 50 tertiary indicators. Through an analysis based on this indicator framework, the total effect, mechanism effect, endogeneity, and heterogeneity of re-employment on healthy aging are examined. The following conclusions are drawn: Firstly, according to entropy method calculations, the level of healthy aging in China is relatively low and exhibits an east-west disparity, necessitating immediate improvements. Secondly, re-employment positively influences healthy aging, a relationship confirmed through robustness tests. Thirdly, investigating the mechanism effect with income as a mediating variable reveals that re-employment leads to increased income, consequently promoting improvements in healthy aging indicators. Fourthly, heterogeneous analysis across different age groups indicates that re-employment positively impacts healthy aging among individuals aged 45-65, while for those aged 65-75, it has a negative effect. Additionally, significant urban-rural disparities exist in the relationship between re-employment and healthy aging. The findings of this study provide a theoretical foundation for the development of indicators related to healthy aging in China and globally. Furthermore, they offer valuable policy recommendations for advancing retirement delay policies, advocating for healthy aging awareness, improving the healthy aging service environment, and encouraging elderly participation in public services and social activities.
Tillage residual film recycling machine screening simulation test and research
Authors: Ren De Zhi , Zheng Qi , Zhang Dong Yuan , Wang Wei 
Published: September 2024

Abstract

Aiming at the problems of incomplete separation of residual film and soil, increased impurity rate, and reduced residual film recovery rate due to the paste sieve in the process of separating residual film and soil in the tillage residual film recycling machine, a vibrating sieve and chain brush combined separating and recycling device is proposed, which carries out the sieving and cleaning operation of residual film and soil by driving the vibrating sieve to swing and the chain brush to rotate through the eccentric shaft. Based on the kinematic analysis, the effect of the combined motion of the vibrating chain brush on the separation of residual film and soil was carried out, and the law of the separation of residual film and soil was analyzed; The maximum amplitude, vibration frequency and chain brush revolutions of the vibrating screen of the tillage residual film recycling machine are used as test factors, and the recovery rate and impurity rate of the screening device are used as evaluation indexes. The Box-Behnken test showed that the best combination of parameters was 10.88mm maximum amplitude、 8.97Hz frequency and 1.66r/s chain brush revolution, under the best combination of parameters, the predicted values of recovery rate and impurity rate were 91.12% and 91.12% respectively. The predicted values were 91.12% and 0.19%, respectively. Field tests showed that the combination of vibrating screen and chain brush operated smoothly in the field, and the recovery and winding rates were 89.65% and 0.32%, respectively. This study can provide a reference for the optimization and improvement of the structure of the sieving device of the tillage layer residual film recycling machine.
An Enhanced Deep Learning approach for crop health monitoring and disease prediction
Authors: Gupta Bhoopesh , Kanmani Sujithra , E Elakiya , Sah Sweeti , Mohanty Sachi Nandan , B Surendiran 
Published: September 2024

Abstract

Global warming and lack of immunity in crops have recently resulted in a significant increase in the spread of agricultural diseases. This leads to large-scale crop destruction, less cultivation, and ultimately financial loss for farmers. Identification and treatment of illnesses have become a big issue because of the fast development in disease diversity and lack of farmer knowledge. This paper investigates the application of deep learning for crop disease prediction using a newly acquired dataset of leaf images from Ghana. The dataset focuses on four major crops: cashew, tomato, cassava, and maize. The paper introduces hybrid deep learning models in terms of various evaluation metrics in identifying healthy and diseased plants based on leaf images. This paper also developed a novel hybrid model for this new dataset. The hybrid model ResNet50 + VGG16 resulted in higher precision and accuracy in its predictions, evidencing strong performance and reliability. This work contributes to the development of accurate and accessible tools for crop disease diagnosis, potentially leading to improved agricultural practices and increased crop yields. Through the integration of newer and advanced deep learning techniques, this research will provide a significant step in the field of agriculture for monitoring crop health disease and prediction.
Design and Experiment of Air-suction Drum-type Seedling Seeder for shaped vegetable seeds
Authors: Li Yanjun , Liu Yunqiang , Ning Yichao , Wu Hongxin , Zhao Yaqian 
Published: September 2024

Abstract

In order to meet the requirements of hole tray seedling transplanting operation for tomato, pepper and other shaped vegetable seeds, and to solve the problems of poor seeding performance of shaped vegetable seedling seeder, this study designed an Air-suction Drum-type Precision Seedling Seeder. The basic structure and working principle of the seeder were elaborated, the key components were designed, and the distribution of the airflow field in the flow paths of the suction nozzles of three different hole types was simulated and analyzed by Fluent software; the relationship between the main influencing factors of the seeder’s operational performance (suction air pressure, clearing air pressure, and vibration frequency of the seed cassette) and the sowing indexes (replanting rate, cavity rate, and qualification rate) was investigated and the relationship between the factors and the sowing indexes (reseeding rate, cavity rate, and qualification rate) was analyzed by the quadratic orthogonal combination experiment method. The relationship between the main factors (suction air pressure, clearing air pressure and vibration frequency of seed supply box) and the seeding indexes (reseeding rate, empty hole rate and pass rate) was studied, and the effects of the factors and their interactions on the indexes were analyzed and the parameters were optimized by multi-objective optimization method. The results show that: the factors affecting the seeding qualification rate in the order of suction air pressure, clearing air pressure and vibration frequency, the optimal parameter combination of suction air pressure 16.0kPa, clearing air pressure 3.4kPa, vibration frequency of 50Hz, in the optimal parameter combination of the sowing test, to get the replanting rate, the rate of empty holes, the qualification rate of the time were 1.4%, 1.7% and 96.9%, respectively.It shows that the performance of this seeder is better adapted, accurate and efficient, and can meet the requirements of shaped vegetable seeding operation. The results of the study can provide a reference for the research and development of the shaped vegetable seedling seeding machine.
Research of 3D-AGCN Schizophrenia Classification Model
Authors: Yin Guimei , Yuan Jie , Chen Yanjun , Guo Guangxing , Shi Dongli , Wang Lin , Zhao Zilong , Zhao Yanli , Zhang Manjie , Dong Yuan , Wang Bin , Tan Shuping 
Published: September 2024

Abstract

Previous deep learning-based brain network research has made significant progress in understanding the pathophysiology of schizophrenia. However, it ignores the three-dimensional spatial characteristics of EEG signals and cannot dynamically learn the interactions between nodes. To address this issue, a schizophrenia classification model based on a three-dimensional adaptive graph convolutional neural network (3D-AGCN) is proposed. Each subject's EEG data is divided into various segment lengths and frequency bands for the experiment. The attention mechanism is then used to integrate the node features in the spatial, feature, and frequency band dimensions. The resulting adaptive brain functional network features are then constructed and fed into the GCN model. This adaptive approach eliminates the human-specified criteria for feature selection and brain network construction. The trial results demonstrated that, when using a 6-second segment length and time-domain and frequency-domain features, patients with first-episode schizophrenia achieved the highest classification accuracy of 83.11%. This method outperforms other feature selection and brain network modeling approaches, providing new insights and directions for the early diagnosis and recognition of schizophrenia.
Impact of Falls From Occupational Injuries: a Comparative Analysis of Mortality and Disability Across Sociodemographic Index 2010 to 2019.
Authors: Vella Christine , Meampel Julian Zammit 
Published: September 2024

Abstract

This study investigates the impact of falls from occupational injuries on disability, focusing on a comparative analysis across different Socio-Demographic Index (SDI) categories from 2010 to 2019 using data from the GBD database. The primary aim is to identify trends, disparities, and contributing factors to the rate of Years Lived with Disability (YLD) resulting from occupational falls. A retrospective cross-sectional observational design was employed, analyzing data from various global regions categorized by high, middle, and low SDI.
The results indicate a significant disparity in disability outcomes related to occupational falls across SDI categories. Lower SDI groups consistently showed higher rates of YLD, suggesting an increased burden and a lack of sufficient occupational health policies and safety measures in these regions. The regression analysis revealed a statistically significant relationship between SDI groups and the rate of YLD (p-value = 0.004), while the relationship between year and the rate of YLD was not statistically significant (p-value = 0.197).
These findings are crucial for informing policies and interventions to reduce occupational falls. The study highlights the need to enhance safety standards, especially in low SDI areas, and suggests that global health policies prioritize tailored interventions for different sociodemographic groups. Understanding these disparities and contributing factors provides evidence-based insights to help mitigate the impact of occupational injuries on worker health and well-being.
A proposed mechanism for the regulation of the annual life cycle based on pupal chamber construction behavior in the Japanese pine sawyer
Authors: Kim Su Bin , Heo Jin Woo , Kim Dong-Soon 
Published: September 2024

Abstract

The Japanese pine sawyer (JPS), Monochamus alternatus Hope, is an important vector of the pine wood nematode, Bursaphelenchus xylophilus (Steiner and Buhrer), which causes pine wilt disease (PWD). Although more than 50 years have passed since JPS was proven to be a PWD vector, surprisingly, the exact life cycle has not yet been fully understood. We could interpret the selection of JPS’s life cycle based on the hypothesis established through this study: a dual regulation of the critical larval age (a minimum 4.2-instar and average 4.8-instar) and cue stimulus (tentatively a cold temperature) in diapause induction expressed by the behavior of pupal chamber construction. The fourth larval instars above the critical age can initiate the tunnel for their pupal chamber when they meet the cue, followed by the selection of the four-instar pathway (4-IP), which indicates the number of instars before pupation. If there is no cue during the fourth instar, the larvae will develop into the fifth instar, and 5-IP can be selected when meeting the cue. However, no cue leads to repeated molting up to the 10th instar. The third or fewer larval instars overwinter without the selection of IP and develop to the final instar the following year to emerge into adults the next year (entering a two-year life cycle). Also, we could explain most of the phenomena that are not well understood in the JPS’s overwintering behavior, such as the pupation on the wood’s surface and unplugged entrance holes. Consequently, our hypothesis will be helpful for future studies of diapause mechanisms and the selection of IP in JPS and related species.