bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unlocking Oil Reserves Sustainably : CO2 Injection for Enhanced Oil Recovery (EOR) in the Sarir C-Field
Authors: Rajandran K. V. , Bataee M. , Bennour Z. 
Published: September 2024

Abstract
The ever rising global demand for energy and the need to reduce greenhouse emissions have led to the exploration of sustainable oil extraction methods. At the forefront of these methods, Carbon Dioxide ( O2) Injection for Enhanced Oil Recovery (EOR) has peaked the interest of many throughout the industry as a means of Carbon Sequestration while still increasing production rates. This thesis will explore the feasibility and potential of CO2 injection and sequestration in a mature reservoir that has been exhibiting declining production rates as of late. The Upper Sarir Sandstones has tremendous potential for EOR and given the petrophysical and fluid properties of the reservoir, it is the perfect case study to assess the feasibility of CO2 injection and sequestration in a mature oil reservoir. This study will be carried out by reservoir characterisation and modelling in which a 3D Model of the Upper Sarir Sandstones will be built and CO2 injection simulation will be employed. This thesis canters on optimizing production rates in the Upper Sarir Sandstones, with a specific focus on the Sarir C Field. The study employs modelling techniques to evaluate the efficacy of immiscible and miscible CO2 injection methods in enhancing oil recovery over a 20-year production cycle. Comparative analysis reveals that while natural production achieves an EOR of 34.2%, both miscible and immiscible CO2 injection methods significantly elevate the recovery factor (RF) to 47.9% and 43.5%, respectively, emphasizing the substantial production benefits of both approaches. An in-depth exploration of the underlying mechanisms influencing RF enhancement distinguishes the pressure-based displacement mechanism of immiscible CO2 injection, which improves reservoir fluid mobility, from the solubility-driven approach of miscible CO2 injection, reducing oil viscosity and fostering sustained high production rates. Despite the initial advantage of immiscible injection, the thesis underscores the superior long-term recovery and sequestration suitability of miscible CO2 injection, attributed to its solubility trapping potential.
A preliminary model assessing CO2 trapping capabilities, rooted in rock-fluid hysteresis, indicates the Sarir C Field's promise for trapping injected CO2. Although lacking certain geological considerations, the field demonstrates increasing dynamically trapped gas saturation across the 20-year production cycle, suggesting its viability for future sequestration initiatives. The findings of this thesis aims to contribute and deepen the knowledge in the CO2 injection and sequestration methodology while promoting sustainable and responsible practices in the Oil & Gas Industry
Site-Level Carbon Storage Potential Estimation in Offshore China
Authors: Li Jiudi , Sheng Zhichao , Huang Yongjie , Yan Shumei , Zhang Le , Zhu Ruizhe , Liu Yuan , Tian Yutong , Wu Jiayi 
Published: September 2024

Abstract
To counteract the trend of global warming and to achieve the objective of "net zero emissions by 2050", many countries are conducting pilot research projects or experiments on carbon storage by exploring the technologies and practices for future deployment. One of the most critical elements for carbon storage is the storage capacity. Many previous authors have proposed their own methods to evaluate storage capacity in the saline aquifer environment, yet those methods are mainly designed for basin or depression-level evaluations. Because the methods vary from each other significantly make them impractical for a site-level storage capacity evaluation.
The work this paper presents aims to estimate the storage capacity by means of a geoengineering approach in the site-level with an actual offshore China example. The key components of this approach include creating the geology and geomechanical model, evaluating the containment properties, and estimating the barrier stress conditions, etc. Considering the actual geology model properties and the dominant saline aquifer storage mechanisms, the authors chose multiple hot areas to conduct reservoir simulations with carbon dioxide injection, where saturation attack tactics were used to withdraw the storage efficiency factor and maximum capacity in different scenarios. This approach eventually allowed the authors to evaluate the true capacity of this site.
This paper provides a systematic example of evaluating carbon storage capacity in the site level. The geoengineering approach also covers optimization of the injectivity and the containment of the barriers with an actual example, which is an important supplement to the existing carbon dioxide storage method, which focused mainly on the large-scale evaluation. Because this site-level workflow drops down to the actual geology and geomechanical environment, it may well prove better value towards the implementation of CO2 injection planning, operation, and monitoring in the later stages.
Gas Hydrate-Assisted CO2 Storage in Subsurface Systems
Authors: Hamdi Z. , Cheong W. C. , Bataee M. , Partoon B. 
Published: September 2024

Abstract
The Hydrate-based CO2 Storage/Sequestration technique has the potential to contribute to achieving Sustainable Development Goal (SDG) 13 by enabling efficient and safe storage of CO2. This paper explores the potential of CO2 storage through gas hydrate formation in depleted hydrocarbon reservoirs, an innovative approach to mitigating climate change by reducing atmospheric CO2 levels. The current applications and potentials of gas hydrates are examined, highlighting their role in energy production, CO2 reduction via oceanic injection, energy storage, and other uses. Geological considerations are analyzed, emphasizing the self-sealing potential of CO2 hydrates, the mechanisms of CO2 sequestration through hydrate formation, and the impact of hydrate presence on reservoir permeability. Simulation studies provide insights into the feasibility and efficiency of this method. Various approaches for CO2 hydrate sequestration are discussed, outlining the practical steps and technological requirements involved. The environmental implications and potential challenges of CO2 hydrate sequestration are evaluated, considering the ecological impacts and long-term sustainability. This comprehensive review suggests that while CO2 storage through gas hydrate formation in depleted hydrocarbon reservoirs holds significant promise, it necessitates further research and technological advancements to address the identified challenges and fully realize its potential as a viable climate mitigation strategy.
A Digital Avatar for Field Surveillance – Integrated Sand Production and Erosion Program
Authors: Dabholkar D. S. , Gupta G. 
Published: September 2024

Abstract
Oil and gas field face several unique flow assurance challenges during production lifecycle. Among all, sand production poses one of the most severe flow assurance risks. Large sand particles tend to settle in the pipeline forming pockets of sand beds while the small particles are carried away with fluid and causes erosion in (subsea and onshore) production facilities. Sand build-up in pipelines significantly reduces operational efficiency due to higher pressure demands on the system. Operational inefficiencies and frequent field shutdowns not only translate into increased operational expenditure (OPEX) but also results in higher carbon emissions and carbon footprints in the environment.
An integrated sand production and erosion program (ISPEP) was developed with the aim to provide faster and precise digital solutions to enhance field surveillance and pipeline integrity. It uses comprehensive approach to understand sand transport in the system and tracks the deposition and bed forming conditions by utilizing field measurements and multiphase software outputs data ingestion, acquisition, processing, transformation, and conceptualization. It provides real-time actionable insights at locations that are experiencing erosional issues in complex production networks, and erosion rate estimates along with total metal loss due to erosion issues. Several methods are included and compared simultaneously in this program which make it robust and accurate.
Field specific operational envelopes obtained from ISPEP are deployed as part of the digital solution. The program continuously monitors field conditions against these envelopes, identifies risks and alert operations personnel upon exceeding various preset thresholds. This empowers operators to better assess the erosion risks, allowing them to take the necessary corrective actions to mitigate or prevent failure. Machine learning algorithm in the backend provides automatic calibration functionality based on field's operating scenarios, sand production rates, etc. that ensures the solution is always representative of field and continue to provide reliable information.
Currently, deployed at various fields with European and Asian operators, the advisory program has proven to be an asset for field's safety and integrity and is positively impacting OPEX by reducing downtime through early intervention and increasing uptime through real-time surveillance.
Evaluation of Custom Acid Formulations in Sand Control Operation: Case Studies and Key Lessons
Authors: Choodesh A. , Chantarataneewat W. , Peerakham C. 
Published: September 2024

Abstract
Cased hole gravel packing is a widely used sand control technique in the oil and gas industry to prevent sand production and maintain well productivity. In reservoirs with unconsolidated sand, implementing effective sand-control practices is crucial to prevent the production of reservoir sand. In addition to sand production, clay and fines migration pose major challenges, potentially resulting in production impairment or leading to failures. Certain reservoirs may contain fine particles or other obstructions that can hinder the effectiveness of gravel pack placement and well productivity.
For this case, improvements to conventional cased hole gravel pack placement were initially pursued using high-rate water pack (HRWP) or fracture and pack gravel (FPG) techniques. Along with these placement technique improvements, there is also the risk of formation damage from incompatible brine or other introduced fluids/solids, as well as formation fines content, especially in Plio/Pleistocene sandstones with low resistivity. Sandstone acidizing is also considered to enhance reservoir permeability and productivity by dissolving and removing formation damage, such as formation fines, mud solids, and potential scale from the pore spaces and near-wellbore region of sandstone reservoirs.
This paper provides insights into the custom acid formulations comparing to the conventional sandstone acid/mud acid recipe (with hydrofluoric acid (HF) and hydrochloric acid (HCl).) treatments, with a comprehensive laboratory testing results focused on improvement, not only for near-wellbore treatment but also for deeper penetration and fines stabilization wherever possible. The importance of these formulations being tailored to the specific needs of the reservoir ensures that they are not only effective but also efficient for the sand control.
Real-Time Well Status Prediction Using Artificial Intelligence Techniques for Accurate Rate Allocation
Authors: Al Kadem Mohammad , Alajmi Abdulrahman , Ansari Najmul , Alali Mohammed 
Published: September 2024

Abstract
Knowing well operating conditions can help to allocate the rate accurately; however, there are several factors that govern the well status such as wellhead or downhole temperature and pressures. In this study, artificial intelligence techniques will be used to estimate and predict well status using combination of surface and subsurface parameters in offshore areas.
Artificial intelligence (AI) techniques have proven their robustness in tackling petroleum engineering problems. Several techniques can be customized to what each problem requires in terms of accuracy and utilization. In this paper, four Machine Learning algorithms (ML) were used to estimate and then predict well operating status. The four algorithms were Gradient Boosting Machine (GBM), Random Forest (RF), Decision Tree (DecT), and Support Vector Machine (SVM). Surface parameters were fed into each model to estimate well operating status. Data were sub-categorized based on well type. Upstream wellhead pressure, downstream wellhead pressure, choke valve position and upstream wellhead temperature were used as features to create each model. Moreover, a prediction model was developed to specify well status at specific circumstances.
The four Machine Learning (ML) algorithms were utilized with datasets covering tens of gas wells. The ML models were optimized in terms of its unique parameters for better results. Random Forest (RF) was proved to provide better results with least average absolute relative error and accuracy of 99% between actual and predicted well status although the other two methods gave reasonable errors. Additionally, the selected model was integrated with a real-time dashboard along with all attainable well parameters. Also, accuracy of the rate allocation was achieved after considering the well status from the selected model including all wells. The prediction model demonstrated acceptable results when comparing to the actual well operating status considering the optimization runs for each dataset.
The well status prediction model can assist in monitoring well performance proactively by studying the relationship between well parameters which can further enhance the rate allocation process. Also, this can help with identifying opportunities for well profitability and maximizing revenue by avoiding production loss.
Projected changes in climate extremes over Tanzania
Authors: LUHUNGA PHILBERT MODEST 
Published: September 2024

Abstract

Understanding projected changes in climate extremes at local and regional scales is critical for reducing society’s vulnerability to such extremes, as it helps to devise informed adaptation strategies and contributes to informed decision-making processes. In this paper, we analyse projected changes in climate extremes across regions in Tanzania using outputs of high-resolution regional climate models from the Coordinated Regional Climate Downscaling Experiment program (CORDEX-Africa). The indices analysed here are those recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) to characterise climate extremes over different regions. The results revealed that Tanzania would experience an increased number of warm days and nights during the present, mid, and end centuries under the RCP4.5 emission scenarios The number of consecutive wet days (CWDs) and consecutive dry days (CDDs) are likely to increase across regions. Areas along coastal regions would experience increased intensity and frequency of extreme rainfall events in the present, mid, and end centuries under the RCP4.5 emission scenario. These increases in extreme climate events are likely to pose significant damage to property, destruction of infrastructure, and other socioeconomic livelihoods for people in many regions of Tanzania. It is therefore recommended that appropriate policies are put in place to help different sectors and communities at large adapt the impacts of extreme climatic events.
Controllable tip exposure of ultramicroelectrodes coated by diamond-like carbon via direct microplasma jet for enhanced stability and fidelity in single-cell recording
Authors: Liu Jingquan , Du Zhiyuan , Xu Qingda , Xi Ye , Xu Mengfei , 曹 佳伟 , Wang Longchun , Li Xiuyan , Wang Xiaolin , Liu Qingkun , Lin Zude , Yang Bin 
Published: September 2024

Abstract

Precise and long-term electroanalysis at the single-cell level is crucial for the accurate diagnosis and monitoring of brain diseases. The reliable protection in areas outside the signal acquisition points at sharp ultramicroelectrode (UME) tips has a significant impact on the sensitivity, fidelity, and stability of intracellular neural signal recording. However, it is difficult for existing UMEs to achieve controllable exposure of the tip functional structure, which affects their ability to resist environmental interference and shield noise, resulting in unsatisfactory signal-to-noise ratio and signal fidelity of intracellular recordings. To address this issue, we chose a dense and electrochemically stable diamond-like carbon (DLC) film as the UME protection coating and developed a method to precisely control the exposed degree of the functional structure by directly fixed-point processing of the UME tip by the strong site-selectivity and good controllability of the atmospheric microplasma jet. By analyzing the interaction between the microplasma jet and the UME tip, as well as the changes in the removal length and microstructure of UME tips with processing time, the exposed tip length was precisely controlled down to the submicron scale. Biocompatibility experiments, electrochemical aging tests and real-time intracellular pH recording experiments have demonstrated that the DLC-UME with effective tip protection processed by microplasma jet has the potential to enable long-term detection of intracellular high-fidelity signals.
Preliminary Evaluation of Local Treatment Combined with Systemic Therapy for Tumor Recurrence after Surgery for Dual-Phenotype Hepatocellular Carcinoma
Authors: Zhu Heping , Shen Ruichao , li Peipei , Wang Fuqiang , Yin Zhenyu 
Published: September 2024

Abstract

Objective: To explore the clinical efficacy of interventional treatment combined with targeted therapy and immune checkpoint inhibitors（ICIs） in patients with postoperative recurrence of dual-phenotype hepatocellular carcinoma(DPHCC).
Methods: A retrospective study was conducted on the clinical data of 8 patients with postoperative recurrence of dual-phenotype hepatocellular carcinoma treated at Xiamen Traditional Chinese Medicine Hospital from January 2019 to March 2023. The clinical outcomes such as progression-free survival and overall survival after comprehensive treatment were analyzed and evaluated.
Results: All 8 patients received transcatheter arterial chemoembolization(TACE) or hepatic Artery InfusionChemotherapy(HAIC) combined with immune checkpoint inhibitors(ICIs) and anti-angiogenic drugs, with a median survival time of 4.9 months (range 1-57.2 months) and a median progression-free survival of 1.5 months (range 0-21 months). Except for patients 2 and 4, tumors continued to progress in all cases, resulting in a disease control rate of only 25%. Conclusion: The efficacy of TACE/HAIC combined with ICIs and targeted drugs for treating dual-phenotype hepatocellular carcinoma may be limited.
Enhancing Water Quality Detection for Drinking and Irrigation Using Convolutional Neural Networks
Authors: Kareem Nagham K. , Aljanabi Mohammad , Mijwil Maad M. , Rabiei Hamid , Miralles-Pechuán Luis , Chadoundry Tanupriya , Kareem Aythem Khairi , Nafea Ahmed Adil , Abotaleb Mostafa 
Published: September 2024

Abstract

Water quality is essential for maintaining the health of ecosystems and the overall quality of life. It is crucial to monitor water quality for effective water resource management, as high-quality water suitable for domestic, drinking, irrigation, and industrial use is not always readily available. Polluted water has serious repercussions, leading to harmful environmental, human health, and infrastructure conditions. According to a United Nations (UN) report, 1.5 million people die each year due to diseases caused by polluted water. A recent study introduced a one-dimensional convolutional neural network (1D-CNN) approach for predicting water quality specifically for irrigation and drinking purposes. The prediction of water quality relies on physicochemical parameters. This study used two datasets—one for drinking water and the other for irrigation water—each with distinct features. The results show that the proposed model achieved 97.19% accuracy for irrigation and 100% accuracy for drinking water, demonstrating the model's effectiveness in accurately categorizing water samples suitable for drinking and providing robust support for decision-making processes related to potable water and irrigation.
Reliable diagnosis of nigrostriatal degeneration by dopamine transporter SPECT despite drug interaction with venlafaxine and bupropion
Authors: Apostolova Ivayla , Hellwig Sabine , Karimzadeh Amir , Klutmann Susanne , Meyer Philipp T. , Buchert Ralph 
Published: September 2024

Abstract

Purpose
This study examined the impact of venlafaxine and bupropion on the detection of nigrostriatal degeneration by dopamine transporter (DAT)-SPECT.
Methods
43 patients (70.7 ± 8.6y, 44% female) with [123I]FP-CIT-SPECT under venlafaxine (n = 26, 37.5-225mg/d), bupropion (n = 16, 150 or 300mg/d) or both (n = 1) were included retrospectively. The striatal specific [123I]FP-CIT binding ratio (SBR), its left-right asymmetry and the putamen-to-caudate ratio were transformed to z-scores and submitted to a cluster analysis for data-driven categorization.
Results
Two clusters were identified. The first cluster (37% cases) showed a Parkinson’s disease (PD)-like pattern: median striatal SBR/asymmetry/putamen-to-caudate z-score − 4.5/4.9/-3.8. The second cluster (63%) showed symmetric reduction with normal intra-striatal gradient: median striatal SBR/asymmetry/putamen-to-caudate z-score − 2.7/0.4/0.2. Patients with follow-up clinical reference diagnoses of neurodegenerative (n = 7) and non-neurodegenerative (n = 16) parkinsonism fell exclusively into the former or the latter cluster, respectively (p < 0.001).
Conclusion
Venlafaxine and bupropion cause uniform reduction of the striatal [123I]FP-CIT SBR that can be distinguished from PD-like reductions.
Analysis of the Correlation between Morphological Classification of the Middle Glenohumeral Ligament and Subscapularis Tears
Authors: Liu Tao , Meng Tao , Huang Zhen , Wang Yaning , Shi Hui , Wang Linwei , Lin Chao 
Published: September 2024

Abstract

Objective
The purpose of this study was to evaluate the correlation between the morphological classification of the middle glenohumeral ligament (MGHL) and subscapularis tears and to assess the necessity of releasing the MGHL.
Methods
A retrospective analysis was performed on the surgical videos of shoulder arthroscopic rotator cuff repair surgeries conducted by the same surgeon from September 2020 to September 2021. The MGHL was classified morphologically into two types: overall classification and lateral insertion classification, and the occurrence of subscapularis tears was recorded for each type. The chi-square test was used to analyze the differences in the number of subscapularis tears among the classification groups. It was approved by Binzhou Medical University Hospital Institutional Review Board(IRB No. 2023-LW-155).
Results
Out of 122 patients, 44 (36.07%) were male and 78 (63.93%) were female, with an average age of 55.03 ± 7.35 years. According to the overall classification of MGHL, there were 54 cases of Type Ⅰ (44.26%), 32 cases of Type Ⅱ (26.23%), 28 cases of Type Ⅲ (22.95%), 2 cases of Type Ⅳ (1.64%), and 6 cases of Type Ⅴ (4.92%). For the lateral insertion classification of MGHL, there were 53 cases of Type A (43.44%) and 69 cases of Type B (69%). There was no statistically significant difference in the number of subscapularis tears among the classification groups (p = 0.089, p > 0.05 for overall classification; p = 0.22, p > 0.05 for lateral insertion classification).
Conclusion
This retrospective study found no correlation between the morphological classification of MGHL and subscapularis tears. For patients with rotator cuff tears who do not have frozen shoulder, caution should be exercised when performing release of the MGHL.