bluuebunny/crossref_metadata_2025_split huggingface dataset:
Digital Dexterity: Building Capabilities in the Era of AI
Authors: AlFedaghi Hadla S. 
Published: November 2024

Technology is synonymous with change. From the industrial revolution to the digital age, each technological advancement has reshaped the way we work, live, and interact. Today, we stand on the precipice of a new era, driven by artificial intelligence (AI) and digital transformation. Establishments that fail to adapt to these changes risk obsolescence, while those that embrace digital dexterity—the ability to adapt, adopt, and use technology for better outcomes—position themselves for sustained success. Digital dexterity is defined as the ambition and capacity to use technology for better business outcomes [1]
Statistics underscore the importance of digital transformation for organizations. According to a 2023 Gartner report, 91% of businesses are involved in some form of digital initiative, and 87% of senior business leaders say digitalization is a company priority [1] Moreover, McKinsey & Company found that companies integrating digital capabilities are 23% more profitable than their less-digitized peers [2] Furthermore, organizations with high digital dexterity report a 37% higher employee productivity and a 30% increase in employee satisfaction [2]
Digital capabilities are essential for modern businesses. The incorporation of advanced digital platforms and platforms can streamline operations, enhance decision-making, and foster innovation. Organizations that prioritize digital transformation are better equipped to respond to market changes, optimize processes, and deliver superior customer experiences. For example, predictive maintenance powered by AI can foresee equipment failures before they happen, reducing downtime and maintenance costs significantly. Additionally, AI-driven analytics help optimize drilling operations, leading to more efficient resource extraction and better decision-making [3]
Resilient and High -Performance Multi-Medium Multi-Channel Wireless Long-Range Mesh Network for Offshore Automated and Remote Communication
Authors: Yahya M. , Abidin W. F. Zainal 
Published: November 2024

Abstract
High-speed Internet has been a very challenging implementation for offshore automated applications and remote communication to reduce operating costs significantly. The satellite network is commonly used in offshore operations, but its high latency and low reliability can be unsuitable for mission-critical operations. Another network medium, like digital microwave radio (DMR), is also commonly used in offshore operations to provide communication networks to multiple remote locations using a mesh configuration to extend the network range up to thirty kilometres. DMR has physical limitations, such as limited antenna height that limits line-of-sight wireless transmission range, regulated maximum bandwidth, and spectrum utilisation. However, decreasing the transmission bandwidth can increase the DMR transmission range, resulting in lower data speed. Overcoming the constraints of DMR as the wireless network solution for offshore, a multi-channel DMR configuration can be implemented to compensate for the lower data speed when transmission bandwidth is reduced. Many solutions in the market provide built-in aggregated data transmission using multi-channel DMR systems, but the solutions are restricted with small spectrum utilisation and high degradation of aggregated data transmission when hopping over multiple network nodes. A non-aggregated multi-channel data transmission method is an approach to mitigate such limitations. It is a cost-effective solution for multi-channel DMR systems. It can be agnostic and is independent of any wireless medium and type that can be used as a network channel and combined into a multi-channel wireless network system. The non-aggregated multi-channel data transmission controls the appropriate amount of data packets and the right time to transmit the data packets over all channels. The parallel data transmission is seemingly concurrent at microsecond time. The solution can improve network performance, reliability, and latency during severe weather conditions due to long-range and multiple network hops with parallel transmission paths. The solution has been implemented and used successfully at numerous offshore sites in the South China Sea using multi-medium and multi-channel wireless with significant performance results.
TransUNet: Accelerating Multiphase Flow Prediction in Geological Carbon Storage Systems
Authors: Tariq Zeeshan , Feng Zhao , Hoteit Hussein , Abualsaud Moataz , He Xupeng , AlMajid Muhammad , Sun Shuyu , Yan Bicheng 
Published: November 2024

Abstract
Deep learning-based surrogate models provide an effective alternative to numerical simulations for addressing subsurface multiphase flow challenges, such as those encountered in Geological Carbon Storage (GCS). In this study, we implemented deep learning based surrogate model as an alternative to complex GCS simulations using TransUNet, an enhanced U-Net architecture that incorporates Transformer models. TransUNet predicts the spatial and temporal evolution of CO2 plume saturation and pressure buildup in saline aquifers by leveraging the capabilities of Transformers. TransUNet is designed to effectively extract features from the structured data, considering spatial relationships and leveraging the Transformer architecture to capture both high-level and detailed information concurrently. Initially, we established physics-based numerical simulation models to account for both injection and post-injection periods of GCS. Employing Latin-Hypercube sampling, we generate a diverse range of reservoir and decision parameters, resulting in a comprehensive simulation databases. We train and test the TransUNet model on two different datasets: a radial model to establish a code benchmark, and the 2D complex model to validate the performance efficiency. Throughout the TransUNet training process, we utilize Mean Squared Error and the spatial derivative as the loss functions. The TransUNet model demonstrates robust performance on the radial model, achieving an R2 of 0.9982 and 0.9963 on testing dataset for saturation and pressure buildup predictions, respectively. Similarly, the model with updated hyper-parameters exhibits comparable performance on the 2D complex model, with R2 values of 0.9986 and 0.9967 on testing dataset for saturation and pressure buildup predictions, respectively. Notably, the Normalized Absolute Error (NAE) for all mappings consistently hovers around 1%, indicating the effectiveness of the trained models in predicting the temporal and spatial evolution of CO2 gas saturation. Moreover, the prediction CPU time for the TransUNet model is significantly lower at 0.02 seconds per case compared to the physics-based reservoir simulator's, 2500 seconds per case for the radial model and 1500 seconds for the 2D complex Cartesian model. This underscores the capability of the proposed method to provide predictions as accurate as physics-based simulations while offering substantial computational timesavings.
Industry Guidelines for Setting the CO2 Specification in CCUS Chains
Authors: Phillips C. , Haghighi H. 
Published: November 2024

Abstract
Impurities in captured CO2 can adversely affect the material integrity, operation and injectivity in CCUS chains and setting the CO2 specification requires an understanding of the impact of impurities across the whole chain.
Carbon Capture, Utilisation and Storage (CCUS) is one of the key pathways towards a net-zero future and significant growth is required in this industry. However, limited literature is currently available which supports setting a CO2 specification considering the full CCUS value chain.
A Joint Industry Project (JIP) was therefore formed to collate current knowledge surrounding impurities and to create guidelines to support industry in setting CO2 specifications for effective and economic CCUS chains. This paper discusses the guidelines, which can be downloaded from the JIP webpage [1].
The JIP comprised industry and research experts to provide a comprehensive and holistic understanding of the impact of impurities and to determine the required CO2 conditioning to meet safety, environmental, technical and operational requirements.
As shown in Fig. 1, the JIP addressed a suite of Work Packages to cover the full value chain of CCUS, considering capture of CO2 from various industrial sources and transportation via different options through to permanent sequestration in geological storage. Additional foundation Work Packages including Thermodynamics, Reaction Chemistry and Materials & Corrosion were created to underpin the entire CCUS chain.
Figure 1 JIP Work Packages [1]
Each Work Package provides a comprehensive report where the current knowledge on the impact of impurities is given and opportunities for further research identified. The reports include information such as:
A logical workflow methodology for setting a CO2 specification. Guidance on effective thermodynamic modelling of CO2 with impurities plus a comparison of the most advanced modelling methodologies against experimental data. Identification of potential chemical reactions which can lead to corrosion and/or solids deposition impacting material integrity and injectivity. Guidance for material selection and corrosion control in the presence of impurities. Review of impurity content on dispersion of released CO2. A review of CO2 capture and purification processes including a review of impurities on liquefaction. Impact of impurities on compression / pumping equipment design and operation. Discussion on the challenges of impurities on metering and sampling technology selection and calibration. Safe design and operation of pipeline and shipping transportation. Impact of impurities on injectivity, reservoir permeability and caprock integrity in saline and gas depleted reservoirs. A review of levelized cost of CO2 abatement methods and examples of impurity removal economics.
As a suite of reports, these guidelines will support readers in their understanding of the impact of impurities and aid in the setting of a CO2 specification for CCUS projects.
A Fixed Single-Point Mooring Innovation Solution for Offshore LNG-FSRU Import Terminal
Authors: Xuanze Ju , Baohui Dong , Xianwu Meng , Changquan Yin , Chong Li , Zhendong Xu , Chunchao Li , Shu Yang , Hanbao Chen , Yingni Luan , Wenjun Shen , Amaechi Chiemela Victor 
Published: November 2024

Abstract
Natural gas plays a critical role in sustainable development and energy transition because it's safe, high-heat and clean energy. LNG-FSRU is an offshore floating storage and regasification unit. Its main function is to receive, store and re-gasify LNG, plus transport the gasified natural gas. It gets transported ashore through subsea pipelines to supply gas to power plants and residential users. However, the mooring system is a key link in the engineering and production of LNG-FSRU. Similar to FPSO, LNG-FSRU has a variety of mooring types, including single-point mooring, multi-point mooring, dynamic positioning and dock moorings. Through comparative study, the Tower Yoke Mooring (TYM) system is widely used in shallow water FPSO, because of its good economic benefits, disconnectability and reliability. Therefore, we innovatively adopted a different berthing mode from the traditional terminal and developed a solution based on FSRU moored by TYM. Compared with the traditional fixed tower mooring system, the Tower Yoke Mooring (TYM) can reduce the overturning moment by reducing the height of the connection point, so as to facilitate the design of the mooring tower and its foundation, and the distance between the mooring point and the FSRU is shortened. Therefore, FSRU can adopt the Tower Yoke Mooring (TYM) solution to carry out overall scheme design research for LNG receiving terminal project. Meanwhile, compared with traditional onshore LNG receiving terminals, this innovative FSRU moored by TYM has the characteristics of a short construction period, rapid market development, smaller land area occupation and high device flexibility. It can be used in economically developed, environmentally sensitive and densely populated coastal areas. It is novel being energy transit, ensuring energy supply security and improving people's living standards in these areas. Thus, it meets the needs of local economic and social development.
A Novel Approach and Workflow for Reservoir Model Uncertainty Analysis
Authors: Madalimov Medet , Li Dachang , Dair Yerkinbek , Ehighebolo Ivbade Thaddeus , Salimova Rashida 
Published: November 2024

AbstractReservoir model-based uncertainty analysis (UA) has been widely applied in the oil industry for decades, but it is still facing some challenges, e.g., integration and visualization of multi-dimensional (4D++) categorical and continuous input parameters. Workarounds, simplifications, or neglect have been utilized for tentative solutions. This paper presents a novel approach/workflow in the aim of attacking these challenges in reservoir model UA. Experimental design improvement for UA is not the focus of this paper.The proposed workflow was successfully applied to Kashagan, a giant carbonate oil field in Caspian Sea that consists of a matrix dominated platform and a non-matrix (NM) dominated rim. Despite 7 years of production/injection history, a wide range of uncertainties exist in reservoir characterization. To understand and mitigate their impact on field performance the subsurface uncertainties, a UA study was conducted. Categorical parameters (subsurface structure, fracture/karst distributions/connectivity, rock quality regions, reservoir heterogeneity etc.) and continuous parameters (matrix/non-matrix compressibility, dual-porosity/dual-permeability coupling parameter, aquifer size/connectivity, permeability/porosity, Kv/Kh ratio etc.) were used to characterize the subsurface uncertainties. Dynamic responses within 60-year forecast (oil/gas/water production/injection rates/ratios/cumulatives, recovery factor, oil in place, elapsed time, and objective function for field total/regions) were selected for analysis. Around 1000 simulation models were designed using standard DoE methods. Statistical analysis was conducted to identify linearity/non-linearity effects, correlations between input parameters, their statistical significances, and possible inflations during regression analysis. Multidimensional scaling was used to visualize the complex input-response relationship, QC&QA the responses and identify behaviors/characters (e.g., clusters) inside of the uncertainty space, which is not apparent in the original space. It opens a window into what the uncertainty scape is like and significantly improves the robustness of P10-P50-P90 (low, mid and high) models’ selection.
The Upper Araej Member: Stratigraphic Complexity and Reservoir Insights from Offshore Abu Dhabi
Authors: Tendil Anthony J.-B. , Galluccio Laura , Lettéron Alexandre , Breislin Catherine , Hatter Stuart , Khan Rizwan , Ul Hasan Affan , De Rosa Giuseppe 
Published: November 2024

AbstractExtensive offshore exploration has targeted the Upper Araej Member (Middle Jurassic), representing the topmost part of the Araej Formation, and numerous hydrocarbon accumulations have been discovered and developed. This study is an integrated analysis of c.320 ft of cored wells within an offshore block, focusing on the depositional architecture and factors influencing reservoir quality to reveal the Upper Araej Member's potential.The Upper Araej Member, with an average thickness of c.300 ft in the studied wells, contains two main carbonate reservoir intervals. These are characterised by stacked beds of dominantly massive, locally dolomitised, skeletal and peloidal pack-grainstone or grainstone deposited in high-energy, proximal settings. These are organised into repeated, ft-scale coarsening-upward trends. Medium- to coarse-grained peloids are abundant throughout the succession, whereas coarse-grained ooids and coated grains are mostly present within units showing parallel or cross-bedding. The local development of laminated features indicates shoal complexes with a higher environmental energy compared to the intervals where grainy sediments do not exhibit lamination. The common hardgrounds and firmgrounds in conjunction with the local reddened nature of the sediments indicate episodic short exposure of the shoal complexes and consequent erosion/cementation and/or oxidation of the sediments. The two reservoir units are separated by an interval associated with a marked increase in gamma-ray values, interpreted as possible argillaceous and/or organic-rich, distal deposits acting as a barrier at the scale of the study area.The Upper Araej Member exhibits a broad range of porosity and permeability values. Grain-supported textures are notably associated with higher reservoir quality compared to mud-supported textures. Additionally, grain size emerges as a pivotal factor affecting permeability; textural analysis of selected thin sections reveals that peloid grain size dictates the size and connectivity of interparticle macropores. Specifically, a shift from fine- to coarse-grained peloids correlates with an increase in permeability for a given porosity level, due to the formation of larger pore throat radii and enhanced connectivity. Moreover, diagenetic processes like cementation and dolomitization play crucial roles in shaping reservoir characteristics. Cementation tends to decrease porosity and permeability by filling pore spaces, whereas dolomitization can improve these properties by creating secondary porosity and improving pore connectivity throughout the Upper Araej Member.This core- and log-based integrated work not only addresses key uncertainties regarding the Upper Araej Member in Abu Dhabi but also establishes a foundation for future offshore exploration and development strategies.
Revolutionizing Complex Casing Integrity Analysis in the Middle East Using High-Resolution Acoustic Imaging
Authors: Alatigue M. F. , Egbe P. I , Aljedawi R. , Pehlke T. 
Published: November 2024

Abstract
High-resolution acoustic imaging was deployed for the first time in the Middle East to assess cased hole well integrity and completion performance in several different wells. These integrity-based inspections represent the first time this novel technology was ran in for the purpose of investigating well integrity risks. This paper introduces this new technology, showcases and validates its core applications in well integrity assessments, and highlights the findings from the three wells logged in 2023.
This solid-state acoustic imaging technology utilizes up to 512 independent sensors that encompass the sensors head. Each of these sensors captures amplitude or acoustic intensity signals and time of flight measurements which are then processed into 3D renderings, conventional 2D logs, and submillimetric measurements of all defects using proprietary surface detection and defect localization algorithms. The sensor array is controlled entirely electronically via software to focus the acoustic energy at the casing wall, this focal distance can be adjusted on the fly enabling multiple casing or tubing strings of varying diameters to be assessed in a single run.
This technology inspects cased wells for inner and outer diameter corrosion and pitting, casing deformation, connection defects such as over-torquing, breaches, and perforated/engineered punches, resulting in more efficient and valuable cased hole integrity inspections.
This paper showcases the results of laboratory validation of well integrity defects imaged using this technology. In addition, the paper presents example of a well inspected throughout 2023. Several unique findings were observed and the novel images from some of the most impactful findings are presented in this paper.
Single-Chip Silicon Photonic Engine for Analog Optical and Microwave Signals Processing
Authors: Deng Hong , Zhang Jing , Soltanian Emadreza , Chen Xiangfeng , Vaissiere Nicolas , Neel Delphine , Ramirez Joan , Decobert Jean , Singh Nishant , Torfs Guy , Roelkens Gunther , Bogaerts Wim 
Published: November 2024

Abstract

We present a photonic engine that processes both optical and microwave signals, and can convert signals between the two domains. Our photonic chip, fabricated in IMEC's iSiPP50G silicon photonics process, is capable of both generation and detection of analog electrical and optical signals, and can program user-defined filter responses in both domains. This single chip integrates all essential photonic integrated components like modulators, optical filters, and photodetectors, as well as tunable lasers enabled by transfer-printed indium phosphide optical amplifiers. This makes it possible to operate the chip as a black-box microwave photonics processor, where the user can process high-frequency microwave signals without being exposed to inner optical operation of the chip. The system's configuration is locally programmed through thermo-optic phase shifters and monitored by photodetectors, and can select any combination of optical or microwave inputs and outputs. We construct multiple systems with this engine to demonstrate its capabilities for different RF and optical signal processing functions, including optical and RF signal generation and filtering. This represents a key step towards compact and affordable microwave photonic systems that can enable higher-speed wireless communication networks and low-cost microwave sensing applications.
Association Between Time of Day and Carbonaceous PM2.5 and Oxidative Potential in Summer and Winter in the Suncheon Industrial Area, Republic of Korea
Authors: Seoyeong Choe , Yu Geun-Hye , Song Myoungki , Oh Sea-Ho , Jeon Hajeong , Ko Dong-Hoon , Bae Min-Suk 
Published: November 2024

Abstract

PM2.5 samples were collected in Suncheon during the summer (June 2-11, 2023) and winter (January 15-21, 2024). The chemical composition analysis included carbonaceous components (OC, EC), secondary ionic components (NH4+, NO3-, SO42-), dithiothreitol - oxidative potential (QDTT-OP), and volatile organic compounds. Results showed higher summer PM2.5 concentrations due to photochemical reactions and higher winter concentrations from heating and stable atmospheric conditions. The OC/EC ratio indicated greater secondary organic aerosol formation in summer. Oxidative potential (QDTT-OPv) was higher in summer (0.12 µM/m³) than winter (0.09 µM/m³), correlating strongly with OC in summer. Health risk assessment of BTEX revealed higher concentrations in winter, with benzene as the primary contributor to lifetime cancer risk (LTCR). The cumulative hazard quotient (HQ) was higher in winter, indicating increased non-carcinogenic risk. The study highlighted that oxidative potential is more influenced by chemical composition than physical characteristics, suggesting that regulating PM2.5 concentration alone may be insufficient. VOCs, as precursors of SOA, showed a positive correlation with QDTT-OPv, with benzene exhibiting the strongest correlation in winter. These findings emphasize the need for targeted management of specific PM2.5 components to mitigate health risks effectively.