bluuebunny/crossref_metadata_2025 huggingface dataset:
EOR Mechanisms and Applications of Thermal Composite Technologiesin Deep Heavy Oil Reserves
Authors: Tang Y. , Ge Q. , Lun Z. , Yin X. , Wu M. , Ma T. , Qi Y. , Zhang S.
Published: May 2024

The heavy oil reservoirs in China are predominantly deep-seated, with high heterogeneity and oil viscosity. Heavy oils situated at depths exceeding 900m constitute 62% of the nation's total reserves. By the increase of steam stimulation cycles, traditional thermal recovery techniques tend to yield diminishing benefits. Thus, Sinopec is establishing a series of thermal composite EOR technologies, primarily targeting deep, heavy oil reserves.

In this study, we've engineered high-temperature and high-pressure micro-visualization experiments to elucidate the microscopic mechanisms underlying thermal composite oil recovery. Our findings show the presence of wall-adhering oil films and filamentary flows during low-temperature hot water flooding. Specifically, at 150°C, the phenomenon of oil-water slug displacement occurs. At 350°C, steam manifests as isolated, nebulous clusters within the oil phase, subsequently leading to the oil phase's adherence to the wall in a turbid state. Upon encountering small pores, steam induces capillary condensation, indicating its liquefaction and heat release in regions with low permeability, thereby enhancing thermal efficiency. Chemical flooding has been observed to yield fine oil-in-water emulsions at pore throats due to its occlusive action, optimizing flow capacity. Notably, the combination of high-temperature steam and chemical agents promotes spontaneous emulsification upon contact with crude oil, generating a flow of finer oil-in-water emulsions. Our "heat+CO2" findings show that at 0.3 MPa, gaseous CO2 tends to form bubbles, subsequently leaving an oil film after gas flooding. Contrastingly, after supercritical CO2 flooding at 10 MPa, almost no oil film residues are found on the wall. At 20 MPa, CO2 dissolution and extraction make the oil phase components segregate at later stage. The combined effects of "steam, chemical agents, and gas" have been identified to significantly enhance oil extraction rates.

Based on our understanding of EOR mechanisms, we have conducted field tests. A thermochemical composite steam drive was executed in the highly-heterogeneous Ng5 block deep heavy oil reservoir in Shengli Oilfield, which has suffered from gas channeling induced by steam. This makes the horizontal displacement more uniform. The coefficient of variance in steam injection speed is significantly reduced to 0.13, surging daily oil extraction by up to fourfold. The recovery rate is increased by 27 percentage points, achieving 62.2%. For the challenges of steam injection impediments and crude oil recovery issues in the Zheng 411 block of deep super heavy oil in Wangzhuang Oilfield, a pilot scheme was launched to bolster thermal development through the combined effects of viscosity-reducing agents and CO2. Our data indicates that single-well production soared from 127 tons to 1,812 tons—a staggering 13.3-fold increment—with the oil-to-steam ratio peaking at 0.88.
Proposing an Adaptable Subsurface Data Assessment Workflow for Identifying Fluid Pathways in Fractured Carbonate Reservoirs
Authors: Olmeda Mariana , Funk Erich
Published: May 2024

The understanding of reservoir fluid pathways and their dynamic behaviour through time is essential for a successful development of a fractured carbonate reservoir. This work aims to propose an adaptable data analysis workflow to optimize the characterization of the reservoir throughout its life cycle. Accounting for different maturity stages and geological scenarios, the proposed evaluation sequence supports an optimum assessment of the reservoir architecture and the understanding of its production behaviour and evolving performance.

The methodology involves the dynamic evaluation and integration of geo-parameters, such as fault damage zones, fracture corridors and connected vuggy layers. The corresponding workflow enables a flexible data assessment of flow-dominating permeability zones and the degree of their spatial connectivity between wells and areas of undrained reservoir potential. The interpretation of image logs, regional field work and outcrops, seismic-scale faults, karstic sections, fractures and sub-seismic damage zones are combined to characterize flow zones and their corresponding hydraulic hierarchy expressed in the dynamic behaviour at well-scale.

The results integrate all information extracted and interpreted from available data sets, determining the preferential networks for fluid movement and how these can be linked to current field development strategies and reservoir management initiatives. The utilized flexible workflow accommodates both parallel and sequential tasks and is adaptive to each given geological case, supporting a streamlined data analysis towards an optimized understanding of reservoir dynamics. The reservoir assessment based on this methodology allows to establish conceptual flow scenarios and their potential impact on field performance. This analysis does also help identifying favourable areas for well placement, including refinements of optimum well design, strategic packer placement and production mitigations aimed towards a stable and sustained field life.

This paper is a contribution to the continuous learning process in field development optimization of heterogeneous fractured carbonate reservoirs. By implementing a flexible data analysis workflow, adaptive to complex geological and variable data scenarios, this work identifies the dynamic range of potential hydrocarbon and water pathways that will determine reservoir performance and helping to optimize the strategy for its development.
Addressing Complex Structural Imaging Challenges in Southern Caspian Sea Through Modern OBN Acquisition and Processing
Authors: Hu Xin. , Lyu Xiaolin. , Wang Wei. , Ding Cengzhen. , Khdhaouria Mourad. , Rouis Lamia. , Rondon Aldrin. , Qi Qunli. , Zhao Min.
Published: May 2024

The Greater Cheleken Area (GCA) developed by Dragon Oil, is situated on a complex NW-SE dextral transcurrent zone which separates the Northern from the Southern Caspian Basin (SCB). Complex fault systems such as highly faulted Pliocene-Pleistocene flower structures and various mud volcanoes creating slow-velocity and high-absorption dimming zone, which bring huge difficulties and challenges in seismic imaging.

In 2022, an OBN seismic acquisition survey was carried out aiming to resolve the imaging problems that exist in a legacy dataset. The main objectives for the 3D OBN seismic survey are: proper imaging of structures, faults and fractures characterization, stratigraphy, petrophysical properties, gas columns and clouds mitigation and fluid contacts in clastic reservoirs cited between1500-4700m depth. The implementation of the seismic acquisition is successful, and a fast-track 3D data cube has been produced showing good results.

The meticulous processing sequence has been completed and the results of the 3D seismic data processing and interpretation are very encouraging, showing a clear improvement compared to the legacy 3D seismic data set. This processing workflow and key techniques used in the project are presented in this manuscript.
A New PDC Bit Selection Method Based on 3D Realistic Cutter Damage Simulation Aimed at Maximizing Product Life-Cycle
Authors: Reboul S. , Pelfrene G. , Saleh K. , AlJarki J. , Al-Otaibi M. , AlShammari M. , AlShammari A. , Ali M. , Al-Salem M. , Aldandan A. , El-Genidy E. M. , Gamal M. , Tissot V.
Published: May 2024

Increasing the life of PDC bits without compromising on bit performance is crucial in drilling operations. It allows the operator to reduce non-productive time and the bit manufacturer to increase the reliability and the repairability of its products. This paper introduces a new PDC bit selection method designed to maximize the durability of the selected bit based on simulations of 3D realistic cutter damage.

During PDC bit drilling operations, any damage caused to one cutter tends to overload others and compromise the balancing and the durability of the whole cutting structure. The impact of various kinds of bit failure and cutter damage on the performance of different cutting structures is estimated. The analysis is performed with the help of a 3D bit-rock interaction model which simulates the drilling process considering both the drill bit and the hole being drilled as 3D meshed surfaces. The simulator is based on a generic computational geometry algorithm which estimates the exact volume of rock removed by each cutter while making minimal assumptions on the geometry of the cutter. Any cutter shape, including damaged ones can be simulated based on this model. Thus, realistic dull conditions can be applied to PDC cutters to analyse how the bit performs once damaged.

A series of simulation scenarios involving different failure mechanisms like abrasive wear, broken cutters, or lost cutters, have been conducted on a series of targeted 9 ¼ in. bit designs aimed to be run in an application in South East Kuwait. Bit designs have been ranked with respect to simulated performance indicators like drillability, steerability, stability, tool face control and also to their ability to withstand mild to catastrophic failure events. Based on this analysis, the top ranked bit design has been selected, manufactured and successfully run in the field. For the first time in the area, the bit achieved two sections (9 ¼ and 6 ½) in one, showing both a high durability and a good compatibility with the directional system used along the formation sequence drilled.

While the classical bit selection process is usually limited to the comparison of different bit designs in a given drilling scenario, the present paper demonstrates how this process can be further optimized by selecting the bit which also guarantees a maximum level of performance when subjected to worst case failure scenarios. This new method should benefit both the operator and the bit manufacturer as it is designed to achieve longer intervals, reduce operating costs and increase the global bit performance.
Application of Multi-Oriented Nozzle for Clean Out Sand Fill in Highly Deviated Well had Succeed to Unlock Oil Reserve in Hpht Oil Well
Authors: Elwan M. , Mousa H. , Shahin E. , Elshiekh M. , Wahib O. , Mansour M.
Published: May 2024

In highly deviated oil wells with inclination angles exceeding 50 degrees, accessing the well can be challenging, especially with solids fill. Rig-less coiled tubing offers a solution, but offshore platforms face logistical and weather challenges. Proper selection of Rig-less coiled tubing clean out BHA minimizes intervention, ensuring operational efficiency. For highly deviated wells with sand fill, a multi-oriented nozzle proves optimal, reducing cleaning time and minimizing debris settle down risk. A case study is presented, showcasing successful cleanout in a high pressure-high temperature well, achieving outstanding results, providing efficient sand fill removal while minimizing operational risks in such a high-pressure, high-temperature (HPHT) oil well.

In offshore operating companies including Gulf of Suez Petroleum Company "GUPCO" rig-less coiled tubing considered one of the high challenges approach meanwhile still the most cheapest option to perform intervention that normal slick-Line and Electric-Line not feasible or applicable due to in-accessibility or fill down hole the tubing or casing that stop against access the lower reservoir intervals downhole while still through tubing perforation has been proved to be the cheapest stimulation method, when compared to tubing conveyed perforation type that is always accompanied with rig work-over. So using rigless coiled tubing has become a smart solution that will clean all debris and fill in the casing and get access to the proposed additional perforation reservoir and this became more challenging hence in the highly deviated reservoir that normal cleaning procedures will not guarantee the highest sweeping efficiency.

Cleaning sand and debris from large diameter, deviated, or horizontal wellbores can be challenging, especially with depleted reservoirs. If the wellbores are not cleaned out properly, it would cause issues related to well production, wellbore accessibility, and damaging of intervention tools
Integrated Reservoir Management in Managing Matured Deepwater Field in Malaysia – A Host Authority Lens
Authors: Surin N. , Kok K. , Khalid R. M , Bakar M. Abu
Published: May 2024

The M field, situated offshore Malaysia with a water depth of approximately 1500 ft at the platform location, was discovered through the M-1 exploration well. Following the discovery, three appraisal wells were drilled under three different partnerships. The first oil commenced production years later, featuring eight oil producers and four water injectors. In the subsequent Phase 2 development, two additional oil producers and four water injectors were introduced.

The field area is medium-sized, 4-way dip closure with highly faulted structure, within a structurally complex, highly faulted setting. The depositional environment is characterized by deep-water turbidite lobes, where multiple reservoirs are separated by a Mass Transport Complex (non-reservoir). Enhanced lateral continuity and connectivity are anticipated in lobate systems compared to proximal channel-levee systems. Hydrocarbons were discovered in two main reservoirs, namely the K-2 and KR, along with some occurrences in the shallower P reservoir. The lower K-2 signifies a sand-rich distributary channel system, while the upper K-2 reflects a mud-rich, unconstrained overbank environment. The KR reservoir is primarily composed of distal lobe deposits, featuring fine-laminated sand sequences.

The M field is a toe thrust hanging wall anticline situated at the intersection of 2 regional thrust fault trends. Isochore analysis at the KR reservoir level suggested that the 2 regional thrust faults were initially extensional and were then simultaneously inverted in the beginning of the later KR reservoir to early K reservoir. Besides the 2 thrust faults, several other faulting phases have had their imprint on the M field structure such as: Gravity driven arcuate extensional faults that tip out downwards.Gravity driven linear extensional faults.Vertical parallel minor normal faults.Back thrust.
Navigating the Challenges for Brownfield Development Thru Application of Multi-Zone Single Trip Tool in Complex Well Architecture
Authors: Salleh N. , Mat S. Wan , Ghazali M. M , Wardi M. S. , Hwan R. Cheol , Bela S. Magna
Published: May 2024

Field BM is an oilfield in off the coast of Sarawak, offshore Malaysia that has been producing for more than 50 years with much infill opportunities lying around. The recent drilling campaign in July until September 2023 has unlocked new potential breakthrough in the area. With more than 200 strings in place, drilling and completing a new well in the area is a great challenge. Navigating through the complex well design, team has taken the challenge to complete the well with cheapest cost, in short, execution optimization is required while not compromising the well productivity.

Due to the nature of targeted reservoirs having weakly consolidated sand, downhole sand control is a must and the most proven method for Field BM is the internal gravel pack. Well 42 was designed with five (5) zones High-Rate Water Pack (HRWP) in 7″ casing. Utilizing the available conductor slot/surface location, it was completed as a high angle well at maximum of 85 degrees deviation to reach all the targeted reservoirs. Having to perform 5 zones HRWP treatment, team was looking for optimization to expediate the execution in effort to reduce the well cost. Hence from the original plan of conventional stack pack technique, team selected 7″ Enhanced Single-Trip Multizone system for Well 42 with estimated reduced execution timing by 50%. The multi-zone single trip system enables single trip multi-zone perforation, single trip of workstring gravel pack operation of all five (5) zones and selectively flow each zone with the screen assembly.

Post drilling reservoir section of Well 42, some changes on the reservoir targets are required where the total reservoir section has increased, and the pumping technique also change from HRWP to Fracpack. The flexibility of the multi-zone single trip system where longer intervals with various zone lengths and higher pressure rating up to 10,000 psi provides the team with alternative option to accommodate the drilling surprises. Within the short time gap between drilling and completion, team managed to deliver the well incorporating all the changes and successfully delivered the well with the production as per target.

Fracpack method is applied in some of the zones as optimization in effort to prolong the effectiveness of the sand control post drilling as no oil-water contact observed from the open hole log. Well 42 is the first in the world 7″ multi-zone single trip system with the highest number of zones in high angle well (5 zones, well maximum inclination of 85 degrees).
Transforming Knowledge Management System with AI Technology for Document Archives
Authors: Tharayil Sarafudheen M. , Alshami Reem A. , Aljaafari Shahd F. , Alnajashi Arwa A.
Published: May 2024

This paper aims to develop an innovative framework to enhance extracting knowledge encapsulated in scanned archived documents, the search and retrieval functionalities of Knowledge Management Systems (KMS) through exploiting artificial intelligence (AI) mechanisms. The framework leverages state-of-the-art techniques in natural language processing (NLP), and deep learning (DL) to handle the challenges of heterogeneous and unstructured data sources. The framework is a multi-staged approach. For data preparation, it employs heuristic and rule-based techniques for extracting data within scanned archive documents. After that, utilize the indexing approach to organize the extracted data. Furthermore, harness the power of the Large Language Model (LLM) to find the similarity between the user query and documents for information retrieval functionality. The proposed framework is evaluated in comparison with traditional approaches of data extraction, search, and information retrieval. This study shows that employing rule heuristics accelerates extraction time by targeting specific document parts. Additionally, our experiments demonstrate superior search speed with the IVF indexing method, and highlight the effectiveness of our innovative parallelism approach in optimizing query processing. Furthermore, consistent performance across different indexing methods on the BeIR dataset was consistent, except for a noticeable drop in accuracy for PQ index.
Strategy Development to Address the Challenges of CO2 Storage in Depleted Gas-Condensate Carbonate Reservoirs. A Case Study from the Sajaa Field, U.A.E.
Authors: Robert M. J. , Jain S. , Golaco C. , Hassan H. , Stojic S. , Shady M. , Author F. G.
Published: May 2024

The Intergovernmental Panel on Climate Change (IPCC, 2022) states that both emissions mitigation and negative emissions efforts and technologies are required to limit average global warming to the 1.5°C projected scenario. CO2 geological storage is a negative emissions technology that is an enabler for direct air capture with CO2 storage (DACS) and bioenergy with carbon capture and storage (BECCS) (IEA, 2022) and tackles emissions in hard-to-abate sectors, such as the steel and cement industries.

The International Energy Agency (IEA, 2023) estimates that sequestering 1.2 Gt of CO2 per annum by 2050 through carbon capture, utilisation and storage (CCUS) is required. Geological carbon capture and storage (CCS) will account for 95% of the sequestration (IEA, 2021), with 30 – 50% of that permanently stored in depleted oil and gas reservoirs (IPCC, 2005). The IEA (2023) states that only 45 Mt CO2 was captured in 2023.

CCS projects with geological storage have concentrated on saline aquifers, such as the Quest and Northern Light projects, and in depleted fields with sandstone reservoirs, such as the Weyburn and In Salah projects. Despite their significant global potential, the focus on carbonate reservoirs and depleted gas-condensate fields has been low, reflecting in the limited amount of published material and knowledge sharing available.
Implications and Benefits of Deep Learning (CNN) in Borehole Image Interpretation: Cost Savings and Improved Accuracy
Authors: Abdel-Baset A. A.
Published: May 2024

Objectives/Scope

saving cost and increasing accuracy of the data interpretation are considered a serious challenge within the oil and gas industry. These challenges come to the surface when there are a critical discission on the drilling of new wells inside the geological units created with the normal procedures of the sedimentological studies inside any area. the main focus of this study is the application of the Convolution neural networks (CNN) techniques which outstanding performance in pattern recognition and classification to predict the borehole image facies in an efficient and accurate way inside the Qawasim Formation which was deposited during late Messinian time.

Methods, Procedures, Process

The main focus of this study is the application of the Convolution neural networks (CNN) techniques which outstanding performance in pattern recognition and classification to predict the borehole image facies in an efficient and accurate way inside the Qawasim Formation which was deposited during late Messinian time. This study presents the application of CNN workflow into five major steps including data collection, preprocessing, CNN model learning testing and evaluation. And For performance analysis. The dataset used to train and evaluate the model consists of 1350 images from three types of labeled facies (cross laminated, laminated and massive facies). The trained labeled mages will pass inside a tunnel of convolution and max pooling feature extraction filters and finally a fully connected layers neural network applied as a final stage of the classification results from the model

Results, Observations, Conclusions

The produced model demonstrates high efficiency and scalability for automatic facies classification with a reasonable accuracy reached to 82%. This model particularly useful in when quick facies prediction is necessary to support real-time decision making and for cost reduction scenarios during performing a numerous number of borehole images. The produced model is easily implementable and expandable to other clastic reservoirs in order to create a quick and accurate geological model and be implemented for the future field development plane and production enhancement from a specific zone.

Novel/Additive Information

the application of deep learning, as demonstrated in this study, will kill two birds with one stone, it increases the efficiency and accuracy Borehole image interpretations, decreasing the cost impact of the geological studies and minimize the risk by increase the accuracy of geological model for any reservoir.
A Language Model for Natural Language Interaction with Transactional Screens in the Oil and Gas Industry
Authors: Tharayil Sarafudheen M. , Aldhalaan Badr , Dossary Basim
Published: May 2024

Transactional Systems are ERP systems that offer various services for the Oil and Gas industry, such as procurements, warehousing, plant maintenance, supply chain, finance, sales, and marketing. However, interacting with transactional systems screens can be challenging for users who are not familiar with the technical details. In this paper, we propose TransLing, a language model architecture that train, fine-tune and deploy smaller LLM models to enable natural language interaction with transactional screens in the Oil and Gas industry such as SAP Screens. TransLing can generate values for user input screens based on the user questions in natural language, translate natural language questions to possible ad-hoc reports, and find transactions from the description. TransLing outperforms the baselines in terms of accuracy and usability and simplifies the technical details and the specific terminology of transactional screens for users who are not familiar with them.
Breaking Barriers: Drilling 10,000 Ft Wells in Record Time
Authors: Qaisar Hasan , Hasnain Wajih ul , Rind Mazhar Ali , Agha Ghulam Nabi , Hasan Naveed
Published: May 2024

Outlining Operator's remarkable achievement of drilling a 10,000 ft well in just 10 days, setting a new speed record in the Lower Indus Basin. Facing challenges in an industry dominated by complex wells and uncertain market conditions, Operator strategically selected candidates, conducted rigorous risk assessments, and executed a robust plan with a focus on safety.

The exemplary performance showcased here stands as a testament to adept benchmark-setting achieved through meticulous well engineering. Operational enhancements played a pivotal role in mitigating non-productive time, seamlessly integrating strategies like simultaneous operations (SIMOPS) and effectively reducing Invisible Lost Time (ILT). The judicious application of cutting-edge technology, notably advanced cutter technology, further propelled the efficiency of drilling operations across a spectrum of formations. This multifaceted approach not only optimized performance but also underscored the commitment to continual improvement, establishing a noteworthy standard in the realm of well engineering, with a focus on achieving excellence in every facet of the process.

In surmounting challenges spanning drilling fluid technology, hydraulics, Bottom Hole Assembly (BHA) designs, and aligning contractor efforts, the operator triumphantly accomplished the fastest well-drilled in the Lower Indus Basin. The noteworthy achievement translates to a substantial reduction in overall drilling time, showcasing a testament to operational efficiency. This success not only stands as a benchmark for future well endeavors but also yields invaluable insights for addressing economic challenges and strategically prioritizing early production. The optimization of drilling fluid technology and BHA designs, coupled with precise attention to hydraulic considerations, underscored a holistic approach to overcoming obstacles. This accomplishment not only solidifies the operator's prowess in the Lower Indus Basin but also sets a precedent for industry-leading practices in well-drilling endeavors.

The paper thoroughly outlines the planning and execution process, providing crucial insights, best practices, and identifying opportunities in fields where prioritizing efficient well economics and early production are paramount considerations. This comprehensive documentation serves as a valuable resource for industry professionals seeking to optimize their approach in similar operational contexts.
The First Drilling Dedicated Artificial Intelligence ChatGPT Pilot
Authors: Alfarisi O. , Singh R. , Singhal R. , M. Alzarooni R. , Fernandes S. , Ayvaz Y. , Vijayan M. , Mohamed J.
Published: May 2024

Can drillers extract insights from successful and challenging cases by writing one sentence? Today, the drillers either dig, for days or weeks, the mixed-structured data of the Daily Drilling Report (DDR), the structured drilling data, or both to extract knowledge about successful cases (e.g., a record rate of penetration) and challenging cases (e.g., stuck pipe and Non-Productive Time (NPT)). The objective is to have the drilling operations insights extracted with no time from the current and historical data reports.

We propose a more efficient knowledge extraction of drilling operations in seconds or minutes by writing one sentence using the latest artificial intelligent Chat Generative Pretrained Transformer algorithm (ChatGPT). Therefore, we launched the first drilling dedicated ChatGPT pilot. ChatGPT has pretrained models; however, in this pilot, we enable ChatGPT to learn from our drilling data to provide specific answers to our challenges accurately and efficiently. The implementation method of ChatGPT requires multiple stages: (1) Data Loading/Downloading and Document Scanning, (3) Data Indexing, (4) ChatGPT Training, and (5) ChatGPT extraction of knowledge.

Our drilling data is available in structured (tabulated), unstructured, and mix-structure formats; therefore, understanding the behavior of ChatGPT in these different formats and other training indexing and cognitive capabilities are some of the pilot targeted objectives.

This novel pilot is the first in the oil industry to use ChatGPT, particularly in drilling. Its outcome determines ChatGPT's ability to ease drilling operations by providing insight and learning from historical success and challenging cases. This paper reveals the methods and tools to quickly deliver efficient and quality answers to drilling operations to the drilling engineers.
Innovative Platform Installation Approach in Replacing Jack Up Rig for Securing Wellhead Support Structure
Authors: Shaari K. Ku , Bakar A. B. Abu , Masrom N. , Nirwana I. , Author S. Teh.
Published: May 2024

The installation phase is a critical stage in a field development involving offshore platform and poses different challenges unique to each project. Among the challenges are performing the execution at a restricted workspace location in brownfield area with the tight installation tolerance, live wellhead, and weather limitation.

Due to limited installation tolerance, innovation to the platform design had been made to allow Main Support Frame (MSF) counter rotation to cater the out of tolerance risk on positioning and orientation. Additional survey equipment deployed has increased the efficiency and accuracy prior setting down the jacket at the intended position.

Existing WHSS which was held by jack up rig and its hanging condition with pre-installed conductors all the way from the WHSS to the seafloor has caused vibration to the WHSS made it difficult to secure the exact coordinate of WHSS prior jacket installation. A good weather window is essential to reduce WHSS movement due to vibration introduced by the hanging conductors. Strong underwater current of more than 1 knot has worsened the situation, adding more variables into the equation in restraining WHSS movement before any welding connecting the jacket and WHSS can be performed.

All the above challenges were successfully mitigated via the identified measures and the platform was successfully installed allowing the secured WHSS to be released from the jack up rig. Innovation to the platform design and installation methodology are essential in ensuring its completion in such environment and constraints.
Viscosity Modeling of Solvent-Water-Heavy Oil/Bitumen Systems at High Pressures and Elevated Temperatures
Authors: Hu Bingge , Yang Daoyong
Published: May 2024

This work presents a new framework for quantifying the viscosity of a solvent-water-heavy oil/bitumen system as a function of thermal energy, solvent dissolution, and water concentration, respectively. By collecting experimental measurements in a pressure range of 0.9 to 5.0 MPa and a temperature range of 298.2 to 463.3 K, the Peng-Robinson equation of state (PR EOS) together with modified alpha functions respectively for hydrocarbons and water as well as binary interaction parameters (BIPs) has been integrated to quantify the aqueous/liquid/vapor (ALV) and LV phase equilibria. By treating heavy oil/bitumen as either a single pseudocomponent (PC) or multiple PCs, such a framework, along with the volume translation (VT) strategy, effective density, and six mixing rules, successfully reproduces the experimentally measured viscosity from 0.7-566.0 mPa•s with an accuracy of 41.1%, 10.2%, 26.3%, 36.4%, 47.2%, and 47.3% (1 PC) and 30.2%, 9.1%, 19.3%, 35.5%, 40.0%, and 30.1% (4 PCs), respectively. Adding water to a solvent-heavy oil/bitumen mixture can either increase or decrease its viscosity, mainly depending on thermal energy and solvent dissolution. Water concentration in feed plays a crucial role on the mixture viscosity at LV equilibria other than ALV equilibria. Heavier solvents are found to have a superior capacity for diluting heavy oil/bitumen at the same solvent concentration, and water has the same ability for reducing mixture viscosity when it is in liquid phase. At a higher temperature, water as a vapour shows its better ability in diluting heavy oil/bitumen than some solvents (e.g., CO2 and C3H8). Such a newly proposed framework makes it possible to not only dynamically and accurately predict the viscosity for the aforementioned mixtures under various conditions, but also seamlessly integrate it with any reservoir simulators for accurately evaluate and optimize the performance of a hybrid solvent-steam process in a given heavy oil reservoir.
Protective role of polyethylene glycol towards the damaging effects of cadmium
Authors: Amist Nimisha , Khare Shubhra , Azim Zeba , Singh Narsingh Bahadur
Published: May 2024

This study aimed to evaluate the role of drought-induced changes on effects of cadmium (Cd) in plants. Cd is most hazardous and important environmental pollutant. Water deficit is most common environmental stress encountered by plants and affects most of the plant functions. The present study assessed the effect of Cd and water deficit on Capsicum frutescens seedlings in single and combined treatments. The seedlings of Capsicum were grown in hydroponic solution and treated with Cd. The seedlings were subjected to water deficit with help of polyethylene glycol (PEG). The other set of seedlings was treated with combined Cd + PEG. In the absence of PEG maximum Cd accumulation were observed. The root and shoot growth of the seedlings were affected under all treatments with maximum inhibition in Cd. Pigment, protein and sugar contents and nitrate reductase activity decreased significantly in all treatments while proline content increased. Induction of oxidative damage occurred through the formation of free radicals which caused alteration in electrolyte leakage, lipid peroxidation and activities of antioxidant enzymes viz. superoxide dismutase, catalase, ascorbate peroxidase, guaiacol peroxidase and non enzymatic non-protein thiol content and ascorbic acid in the stressed seedlings. Water deficit buttressed the toxic effect of Cd on chilli seedlings.
The geologic history of marine dissolved organic carbon
from iron oxides
Authors: Galili Nir , Bernasconi Stefano , Nissan Alon , Alcolombri Uria , Aquila Giorgia , Bella Marcella Di , Blattmann Thomas , Haghipour Negar , Italiano Francesco , Jaggi Madalina , Kaplan-Ashiri Ifat , Lechte Maxwell , Porter Susannah , Rudmin Maxim , Spencer Robert , Wohlwend Stephan , Hemingway Jordon
Published: May 2024

Dissolved organic carbon (DOC) is the largest reduced carbon reservoir in modern oceans¹,². Its dynamics regulate marine communities and atmospheric CO₂ levels³,⁴, whereas ¹³C compositions track ecosystem structure and autotrophic metabolism⁵. However, the geologic history of marine DOC remains entirely unconstrained⁶,⁷, hindering our ability to mechanistically reconstruct coupled ecological and biogeochemical evolution.
To address this, we developed the first direct proxy for past DOC signatures using co-precipitated organic carbon in iron ooids, and we applied this to 26 marine iron ooid-containing formations deposited over the past 1650 million years.
Predicted DOC concentrations were near modern levels in the Paleoproterozoic then decreased by 90-99% in the Neoproterozoic before sharply rising in the Cambrian. We interpret these dynamics to reflect three distinct states: (i) small, single-celled organisms combined with severely hypoxic deep oceans; (ii) larger, more complex organisms and little change in oxygenation; (iii) continued organism growth and a transition to fully oxygenated oceans⁸,⁹.
Furthermore, modern DOC is significantly ¹³C-enriched relative to the Proterozoic, likely due to changing autotrophic fractionation driven by biological innovation; together with isotopically invariant carbon inputs to Earth's surface¹⁰, this implies increasing relative organic carbon burial through time. Our results reveal new connections between the carbon cycle, ocean oxygenation, and the evolution of complex life.
Real time dynamic ultrasound guided endotracheal intubation: A future foreseen
Authors: Syal Kartik , Chandel Ankita , Kanwar Manjit Singh
Published: May 2024

Background
The dynamic use of ultrasound for tracheal intubation is yet to be explored. The study reports the successful use of real time sonography for tracheal intubation in a cohort of 30 patients undergoing laparoscopic cholecystectomy under general anaesthesia.
Aim
To assess the feasibility of ultrasound guided intubation (UGTI) and to define the methodology to be deployed for performing ultrasound guided intubation (UGTI).
Methods
In this prospective study we included a cohort of 30 patients undergoing laparoscopic cholecystectomy under general anaesthesia. We used the real time ultrasound image to determine the hockey stick angulation of tube, corresponding to the angle seen on ultrasound between oral and laryngotracheal axis in slight head extension in supine position and then dynamic ultrasound guidance was used to advance the endotracheal tube through glottis.
Results
We were able to perform endotracheal intubation successfully in 76.6% patients with an average intubation time of 94.69 ± 24.7 seconds.
Conclusion
This study defines the probable methodology, to be used while performing ultrasound guided intubation. Also, UGTI can prove to be a minimally invasive real time infallible and fool proof technique for endotracheal intubation over traditional laryngoscopy.
EnSCAN: ENsemble Scoring for prioritizing CAusative variaNts across multi-platform GWAS for Late-Onset Alzheimer's Disease
Authors: ERDOĞAN Onur , İYİGÜN Cem , SON Yeşim AYDIN
Published: May 2024

Late-Onset Alzheimer Disease (LOAD) is a progressive and complex neurodegenerative disorder in the aging population. LOAD is characterized by cognitive decline, such as deterioration of memory, loss of intellectual abilities, and other cognitive domains depending on traumatic brain injuries. Alzheimer's Disease (AD) presents a complex genetic landscape that remains elusive, which restrains the early and differential diagnosis of LOAD. While Genome-Wide Association Studies (GWAS) enable the examination of statistical interactions among individual variants within specific loci, traditional univariate analysis may overlook intricate relationships between these genetic elements. Machine learning (ML) algorithms, on the other hand, prove invaluable in unraveling concealed, novel, and significant patterns by considering nonlinear interactions among variants. This approach enhances our comprehension of the genetic predisposition underlying complex genetic disorders. When working on different platforms, majority voting can not be applied because the attributes differ. Hence, a new post-ML ensemble approach is developed to select significant SNVs over multi-genotyping platforms. We proposed the EnSCAN framework using a new algorithm to ensemble selected variants even from different platforms to prioritize candidate causative loci, which consequently helps improve ML results by combining the prior information captured from each multi-model of each dataset. The proposed ensemble algorithm utilizes chromosomal locations of SNVs by mapping to cytogenetic bands, along with the proximities between pairs and multi-model via Random Forest validations to prioritize SNVs and candidate causative genes for Alzheimer Disease. The scoring method is scalable and can be applied to any multi-platform genotyping study. We present how the proposed EnSCAN scoring algorithm prioritizes the candidate causative variants related to LOAD among three GWAS datasets.
Machine learning predicts lifespan and underlying causes of death in aging C. elegans
Authors: Ezcurra Marina , Kern Carina , Manescu Petru , Cuffaro Matt , Au Catherine , Zhang Aihan , Wang Hongyuan , Gilliat Ann , Gems David
Published: May 2024

Senescence (aging) leads to senescent pathology that causes death, and genes control aging by determining such pathology. Here we investigate how senescent pathology mediates the effect of genotype on lifespan in C. elegans by means of a data-driven approach, using machine learning (ML). To achieve this we gathered extensive data on how diverse determinants of lifespan (sex, nutrition, genotype) affect patterns of age-related pathology. Our findings show that different life-extending treatments result in distinct patterns of suppression of senescent pathology. By analysing the differential effects on pathology and lifespan, our ML models were able to predict >70% of lifespan variation. Extent of pathology in the pharynx and intestine were the most important predictors of lifespan, arguing that elderly C. elegans die in part due to late-life disease in these organs. Notably, the mid-life pathogenetic burst characteristic of hermaphrodite senescence is absent from males.
Influence of Input Motion Uncertainty in Developing Slope-Specific Seismic Fragility Curves Based on Nonlinear Finite Element Simulations
Authors: Cho Youngkyu , Kim Byungmin
Published: May 2024

In the seismic fragility assessment for geotechnical structures, the selection of input motion set for nonlinear dynamic finite element (FE) analyses has solely been based on the methods used in an incremental dynamic analysis (IDA), despite methods adopted in structural engineering for cloud analysis (CA), and multiple stripe analysis (MSA). This study investigates uncertainties in the seismic fragility curve of slopes arising from input motion sets used in nonlinear dynamic FE analysis to develop a probabilistic seismic demand model (PSDM). We consider a FE slope model and four sets of input motions based on CA (Set 1: 632 unscaled ground motion records), IDA (Set 2: random sampling with four sample sizes of 7, 14, 28, and 50 from Set 1, scaled to five PGA values, iterated 20 times), and MSA [Sets 3 and 4: different suites of ground motion records at five PGA levels spaced equally on linear and logarithmic scale, respectively, from Set 1, considering as many records as possible (maximum sample size) and 20 iterations of random sampling for three sample sizes of 3, 6, and 9 out of the maximum sample size]. Comparisons of the seismic fragility curves from Sets 2, 3, and 4 relative to the curves from Set 1 reveal that Set 4 (with a sample size of 9, involving 45 analyses) is more computationally efficient than Set 2 (with a sample size of 50, totaling 250 analyses) and would yield the curve stochastically closer to the one from Set 1. It is worthwhile to consider the input motion set based on the MSA with PGA levels evenly distributed on a logarithmic scale than the IDA-based set when compiling large numbers of ground motion records is limited.
Thermodynamic studies of complexes in Cu(II)/Uridine- 5’-diphosphoglucuronic acid system
Authors: Stachowiak Klaudia , Zabiszak Michal , Grajewski Jakub , Teubert Anna , Bajek Anna , Jastrzab Renata
Published: May 2024

Binary system of uridine-5'-diphosphoglucuronic acid with copper(II) ions have been studied. Potentiometric studies in aqueous solutions using computer data analysis were carried out. The pH of dominance, the overall stability constants (logβ) and the equilibrium constants of the formation reaction (logKe) were determined for each complex compound formed in the studied system. Spectroscopic studies were carried out to determine the mode of coordination in the compounds studied. Biological analysis of the compounds obtained showed an increase in the biological activity of the complexes tested against the free ligand.
One-Pot Synthesized Mixed-Dimensional Graphene for Photodetectors in Near-Infrared Image Sensors and Logic Circuits
Authors: Wang Gang , Zhang Shan , Wu Huijuan , Wang Bingkun , Zhang Jinqiu , Lian Shanshui , Zhang Guanglin , Yang Siwei , Ding Guqiao , Tang Shiwei , Zheng Li , Ye Caichao
Published: May 2024

The advancement of heterostructures in two-dimensional (2D) materials plays a pivotal role in enhancing their optoelectronic capabilities. Nevertheless, existing heterostructures encounter limitations concerning light absorption efficiency and band alignment, impeding the generation and transportation of photo-generated charge carriers. To overcome these challenges, we have pioneered the development of a self-powered photodetector operating in the near-infrared (NIR) spectra. This innovative photodetector is built upon nitrogen-doped graphene quantum dots (N-GQDs), three-dimensional (3D) graphene, and germanium (Ge) Schottky junctions. By leveraging the remarkable light absorption capabilities of N-GQDs and 3D-graphene, combined with precisely aligned heterostructure band alignment, as-fabricated device manifests a robust built-in electric field. Consequently, it facilitates efficient generation and separation of photo-generated charge carriers, thereby significantly amplifying overall optoelectronic performance. The as-fabricated photodetectors exhibit exceptional responsivity (2.3 × 103 A/W) and specific detectivity (6.2 × 1014 Jones) when illuminated at 2200 nm. Extensive studies validate the outstanding reproducibility, long-term stability, and microsecond-level rise/fall times of the proposed photodetectors. Particularly noteworthy is their remarkable image sensing capability, enabling the capture of high-resolution images in the NIR range. Furthermore, we have successfully demonstrated the integration of as-fabricated photodetector into optically controlled digital logic circuits. This groundbreaking research paves the way for designing and fabricating high-performance 3D heterostructures, opening up exciting possibilities for diverse optoelectronic applications.
Assessing the link between skin Aquaporins and morphological attributes in sheep under simulated heat stress conditions: a comparative breed-based investigation
Authors: Bahadi Majdi A. , Samara Emad M. , Khan Muhammed A. , Afzal Muhammed , Al-Badwi Mohammed A. , Abdoun Khalid A. , Alghamdi Salem S. , Al-Haidary Ahmed A.
Published: May 2024

A comprehensive understanding of the functions of Aquaporins (AQPs) is indispensable for elucidating physiological adjustments to varied habitats and addressing water balance complexities amid environmental fluctuations. This experiment endeavors to investigate the relationship between cutaneous AQPs and morphological traits in two sheep breeds with differing hair textures, the Naimi and Najdi, under simulated heat stress conditions. Ten male lambs from each breed were housed individually in controlled environments and subjected to cyclic heat stress mimicking summer conditions for six weeks. Sweating rates (SR) were measured biweekly, and skin and coat samples were collected for analysis in the final week. The mRNA expression levels of Aquaporin 1 (AQP1), Aquaporin 3 (AQP3), and Aquaporin 5 (AQP5) in skin tissue were assessed. Results showed a (P < 0.05) increase in AQPs gene expression following thermal exposure in both breeds, accompanied by elevated SR. The Naimi breed exhibited (P < 0.05) higher AQP1 expression levels, correlating with differences in skin depth, coat thickness, and hair density compared to the Najdi breed, which showed (P < 0.05) heightened AQP5 expression, consistent with its thicker hair diameter. Both breeds displayed similar upregulation of AQP3, suggesting its equivalent role in facilitating perspiration during heat stress. In conclusion, the involvement of both skin AQPs and sweating response emphasizes the intricate interplay between their physical attributes and genetic predispositions in coping with heat stress, indicating a multifaceted process of thermoregulation in sheep. This research highlights the importance of understanding AQPs functions in adapting to environmental challenges and maintaining water balance in diverse habitats.