bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Importance of Tracking Hydrogen H2 in Complex Natural Gas Networks
Authors: Erickson Dale D. , Holbeach James , Golcznski Danny , Morrissy Shane A. 
Published: April 2022

Abstract

Objectives/Scope
Many midstream operators are developing plans to introduce Hydrogen (H2) into natural gas networks in concentrations of 0 to 20%. It is important to keep the concentration in all locations in the network within these limits, to reduce H2 induced cracking of pipelines and because most burners in the US are not designed for the different heating values (Wobbe Index) associated with the H2 mixtures, and flame speed present with H2 flames. This paper presents a model which dynamically tracks H2 concentrations, and associated Wobbe Index, in a complex delivery network and discusses the operational challenges associated with the introduction of H2 in these systems.

Methods, Procedures, Process
The model is based on proven technology which has been used on gases of variable quality for 30 years. The key item currently however is the new addition of H2 to the composition mix. The model is dynamic and responds to changes in the H2 concentration and flowrate. It is envisioned that the H2 supply to these networks will be variable (for example solar generated H2). This paper will present several case studies showing how H2 affects an existing gas distribution network and the paper will also discuss how H2 impacts the thermodynamics used in the calculation engine.

Results, Observations, Conclusions
The case studies will show that for even simple events like a customer trip, high concentration H2 packets can travel into pipelines that normally do not receive H2. As H2 travels through the pipeline, parameters within the system start to change such as the pipeline pressure drop increases and the compressor duty and outlet temperature increase.

Novel / Additive Information
The model tracks gas packets dynamically in the network (packet size is based on dispersion length) and calculates the density and energy content based on the local concentration. It then has a built in EOS (equation of state) based on GERG 2008 to calculate the density. Even with this complexity the model can run at speeds 100 times real-timefor a network that has approximately over 1,000 km of pipe.
Modelling of Conductor Jetting Operation Using a Moving-Grid CFD Model
Authors: Gomes Anderson Fernando De Carvalho , Barboza Beatriz Ramos , Cutrim Fabio Sawada , Cytrangulo Lucas Silva , Nardi Luiz Fernando Bermero , Ito Mario Cesar , Da Costa Paulo Roberto Siqueira , Dias Rafael 
Published: April 2022

Abstract
Jetting is a widely applied technique for conductor installation, which allows great time savings in comparison to conventional drilling and cementing of the conductor.
According to Kan et al. (2018), the key parameters for a successful jetting operation are: pump rate, ratio of bit-to-conductor dimensions and bit stick-out, that is, the length of bit bottom out of conductor shoe, during jetting. The influence of these key parameters was studied, with regards to excavation rate.
The present work used a finite volume method to model the impingement of maritime soil by a jetting assembly, comprised of a rotating drillbit and conductor. The soil was modeled as a highly viscous fluid, described by a modified Herschell-Bulkley viscosity model.
Velocity and pressure fields were obtained for the fluid surrounding the jetting assembly. The integration of static pressure acting over certain walls allowed for the calculation of fluid forces acting on the tools. Excavation rate was measured and compared to field-obtained data, for calibration purposes. The comparison of excavation rates obtained for different configurations showed that some stick-outs were more efficient than others.
By measuring the hydraulic energy of each fluid phase, it was possible to understand the physics underneath the jetting operation, which is associated to fragilizing the soil. This fragilization will eventually lead to lower drag forces, if conductor reciprocation becomes necessary.
An Innovative Method to Process and Visualize Real-Time Data Generated in Drilling Activities
Authors: Donatti Carlos Newmar , Gonçalves da Silva Fabio Rodrigues , Fasolin Karina , Girardi Vinicius , Romani Eric Cardona , Barboza Diego Cordeiro , de Oliveira Wesley Lopes , Munerato Fernando Perin , Batista João Humberto Guandalini 
Published: April 2022

Abstract
To mitigate risks and improve performance during the drilling of an oil well and its various hole sections, it is recommended that its operational parameters and trajectory be monitored in real-time. This activity is crucial to avoid several problems during drilling campaigns, especially if the drilling specialist can have all the data and some level of automatic interpretation on hand, so quick decisions can be made. However, most current monitoring software do not have an interactive or immersive visualization of this data, only track plots with multiple curves. To improve specialist experience, a 3D visualization system has been developed to unify both the drilling monitoring and analysis process of charts, drilling trajectory, lithology, and seismic data.
The Divisor system consists of a cloud platform that unifies and processes data from different sources and a digital 3D visualization application. Its visualization module can be used in two forms: a traditional desktop interface enhanced with 3D visualizations and an immersive mode using a Virtual Reality (VR) headset. Both allow the operator to view real-time or historical data in multiple ways, perform assessments and simulations. Additionally, in VR mode, it is possible to navigate through a full-scale virtual environment, interact with the drill hole tridimensional visualization, and freely position charts with the essential variables to be monitored. This allows for better data manipulation granting better insights related to the numerous data captured, improving the decision-making process and enhancing the interaction in troubleshooting activities.
The visualization application connects to a database that contains both static/design information and real time data, enabling a deeper analysis of all data together and the execution of artificial intelligence (AI) algorithms to generate new information and predictions according to the collected data. With both tools working in synchronization, it is possible to insert data from reports, convert them to a readable standard format, and generate visualizations customized by the user. The streamlining of consumption, analysis, and understanding of data allows for savings through the reduction in the numbers of software used as well as the time required for their implementation.
The system can also be used as a training environment using historical data to operators in order to check their capacity of response in different scenarios, as well as guarantee the consistency of the operational activities. As future work, this tool will be extended with more views in VR and desktop modes, including new data generated by AI and comparison of design data (real and simulated), as well as an integration with a Digital Twin platform.
The Social Brain & Team Decision Making: Lessons from Neuroscience on Safe, Reliable Work
Authors: Musgrave David Christopher 
Published: April 2022

Abstract
As teams plan and coordinate work, some do so better than others when ensuring a group process that is free from error. Generally, the saying ‘two brains are better than one’ is very true, but only if a focus on inoculating against social-brain hazards is installed within the work system. Examples include avoiding groupthink and other related error traps that lead to flawed planning, increased risk, or catastrophe.
Many work-related critical errors stem from the natural functioning of the brain, including when several team members come together to communicate about the work but succumb to social norms embedded in our habitual interactions with peers. It is important for organizations to apply enhanced communication processes to detect latent conditions to ensure operations are planned safely, anomalies are detected through focused attention and discussion, and so that dissenting opinions are raised despite human biology that prompts us all to remain quiet and not disrupt the status quo, or question well regarded others.
Companies around the world are improving the way important communications occur to ensure the most critical tasks execute as planned and operations are kept in control. The discipline of Human Performance Improvement has allowed organizations to now take better control of the human factor with a focus on communication, job task design enhancement, and employee education on error prevention. Science based interventions that harness the power of the social brain and improve decision quality and foster situational awareness, yield powerful results that allow employees to detect weak signals amongst equipment but also the team, and other latent error conditions that are aligning to create a brewing storm leading to upset operations, injuries, or catastrophe. We know a lot about how human beings naturally interact at work, so keeping the helpful portion of this in place and addressing natural limitations built within our neuroscience are the key to sustainably safe operations respectful of the people who run them. Results include: Capacity-Yield/On time performance improvements of 27% to 65%Rework/waste reductions of 27% to 45%Absenteeism reductions of 15% to 37%Talent retention improvement of 21% to 60%Productivity increases of 18% to 47%Recordable injury reductions of 25% to 95%
As our systems and work design continues to improve, the greater the impetus to apply human performance science to address the human side of how work really gets done. Most interventions focus on awareness training, and presentation of academic models to people who execute the work. A better approach harnesses the science but integrates it into the natural way work happens. Knowing how people tick, paired with practical tweaks to systems makes all the difference.
Reliability of Residual Curvature Method Used in Deepwater Applications in Terms of the Critical Buckling Load
Authors: Lee Liang-Hai 
Published: April 2022

Abstract
Recently residual curvature method (RCM) has gained significant attention in deepwater applications due to its advantage in cost saving over other mitigation measures used in flowlines subjected to HP/HT condition. It provides an out-of-straightness feature as a triggering agent for global lateral buckling at designated locations to absorb the flowline expansion if properly designed. Although the residual curvature method has been implemented in shallow water regions installed by reel-lay vessels,only a few projects use residual curvature method for thermal mitigation in deepwater regions due to the reliability of triggering lateral buckle in relation to the amount of rotation along the pipe axis. This paper presents a systematic study using common deepwater pipeline geometric, material properties and operational conditions to demonstrate how to determine the safety margins of residual curvature method used in deepwater applications.
Strategy Shifting in Reservoir Management Plan through Integrated Data Analysis for a Mature Reservoir Offshore Malaysia: Lessons Learnt and Pavement to the Best Practices
Authors: Mithani Aijaz Hussain , Ranjan Rakesh , Salleh Khiril Shahreza , Lien Wee Hoo , Md Zainuri Md Zarin 
Published: April 2022

Abstract
The comprehensive reservoir management plan (RMP) is essential to keep the reservoirs healthy and to produce them efficiently. This paper highlights our experiences in managing very complex, mature, and "potentially" fractured reservoir under water injection with 26 producers and 21 water injectors in offshore Malaysia. The reservoir under study is mature and very complex reservoir deposited in fluvial-deltaic depositional system mainly channel and sand bars. The reservoir connectivity remained one of the major uncertainties. A detailed integrated historical data analysis approach coupled with surveillance activities (e.g., chemical inter-well tracers) were adopted to maximize the reservoir recovery which was declining over the years. The exercise revealed many intriguing observations about the reservoir e.g., when injection rates were ramped up, pressure was dropping in nearby wells with lower water cut, while pressure and water cut was increasing in wells away from injectors. Systematic integrated data analysis performed triggeredmany possibilities e.g., unintentional fracture of reservoir caused due to reduced temperature and pore pressure, well integrity issues etc. The plans are formulated to optimize water injection for better productivity. The strategy shift in reservoir management plan may help in fracture closure and its containment while improving production. It may also help to delineate reservoir connectivity information, avoidance of water recycling, reduced unit injection cost (UIC), and safeguarding 11.5MMstb (RF improvement of 14%) of oil reserves. It also pavesthe path for best practices in managing reservoirs under water injection.This case study will provide detailed workflow of technical analysis that was carried out. It will show how even with limited data team could reach to the most likely possibility. Furthermore, it will highlight the simple, yet effective strategy adopted for improved recovery. Finally, we will recommendminimum data acquisition requirements for efficient reservoir management of reservoirs under water injection.
Stereo Image System for Inspection of Mooring Chain in the Splash Zone
Authors: Medagoda Lashika , Van Bruggen Thomas , Galea Mitchell , Morgan Hamish , Syed Tajamul , Kazzaz Abraham , Hamersley Fraser , Jolly Jordan 
Published: April 2022

Abstract
This paper outlines an optical stereo photogrammetric imaging system, called the Lantern Eye Air (LEA), for inspecting the mooring chain above the water in the area known as the splash zone. The system is mounted and deployed by a Rope Access Technician (RAT), and achieves data collection in this difficult to access region for subsequent 3D reconstruction and measurements for inspection.
Typically, splash zone mooring chain inspections are carried out using mechanical calipers which are difficult to deploy, provide measurements at discrete locations only and are dependent on the proficiency and judgement of the operator on the field. The LEA system overcomes these problems, providing objective, accurate and repeatable measurements based on reconstructed photorealistic 3D models. Imagery of the chain links is captured systematically which was used to generate 3D reconstructions and establish measurements of bar diameter and inter-grip length.
A splash zone inspection was undertaken on an offshore platform. The 3D metrology bar diameter measurements were within 1.7% of caliper measurements based on 2σ (95% confidence). Similarly, the 3D metrology inter-grip length measurements were within 0.9% of caliper measurements based on 2σ (95% confidence). Application of a systematic validation procedure following the inspection placed the expected uncertainty of measurements at the 1% range. Similarly, the uncertainty in caliper measurements has been estimated to be 2% based on the use of a standard handheld caliper and measurement procedure laid out in the ABS Guide for the Certification of Offshore Mooring Chain and the 2020 Life Extension Mooring Platform Chain Inspection. Considering these uncertainty bounds, the 3D metrology measurements can also be deemed consistent with the ground truth dimensions.
Based on the results, the LEA and 3D metrology measurements are consistent with current techniques and provide a more systematic and repeatable basis for mooring chain inspection and measurement in the splash zone. This is anticipated to improve the consistency and comparability of inspections and will enable precise change tracking between inspections.
Integration of Formation and Drilling Parameters to Generate a Deterministic ROP Model
Authors: Khan Mohammad Rasheed , Sadeed Ahmed , Kalam Shams , Abu-Khamsin Sidqi , Abdulraheem Abdulazeez , Khan Rizwan Ahmed , Abbasi Asiya 
Published: April 2022

Abstract
Drilling performance is greatly driven by the rate of penetration (ROP) and its optimization. Therefore, accurate prediction of ROP before drilling can help take measures to achieve drilling objectives smoothly. Numerous inter-twined formation and drilling parameters affect the ROP. Consequently, optimizing and predicting ROP is a complex challenge faced by the industry. This study proposes a novel computational intelligence-based (CI) model to predict ROP as a function of multiple readily available mud- and petrophysical- logs. Furthermore, multiple algorithms are utilized, and a comparative analysis is presented.
Adaptive Neuro Fuzzy Inference System (ANFIS), along with Artificial Neural Network (ANN) based algorithms are utilized to analyze the data and develop models. A process-based approach is followed starting with systematic data analysis, which includes a selection of the most relevant input parameters, data cleaning, filtering, and data-dressing to ensure optimized inputs into the computational models. This step allows for developing ROP predictor as a function of pivotal formation-related logs such as neutron, density, wave velocity, and gamma ray. Moreover, historical drilling-related parameters such as weight on bit, mud pump parameters, and bit flow rate are also used as model inputs. Next, CI model parameters are tuned for both ANN and ANFIS through a sensitivity analysis on the number of neurons and the cluster radius, respectively. Finally, a comparison of ANN and ANFIS models is performed using graphical and statistical analysis.
The developed models are tested on an unseen dataset to verify their efficiency. An error metrics analysis, comprising of average percentage error, root mean squared error, and the correlation coefficientis performed. This analysis ranks the respective CI models based on the highest performance efficiency and lowest prediction error. Resultantly, it is observed that the ANN-based model can perform better than the ANFIS model by accurately predicting ROP. The superior performance of ANN is due to its ability to map the complex non-linear interactions of formation and drilling parameters to the resultant ROP.
Bridging Knowledge Gaps Through an Integrated Structured Production Engineering Knowledge Management Program: A Story to Tell and Adopt
Authors: Kadem Mohammad , Yateem Karam , Alghamdi Abdullah , Shurafa Mujtaba , Saiood Hussain 
Published: April 2022

Abstract
Knowledge management is the process of defining, structuring, storing, and sharing knowledge and experiences of employees within an organization to increase workplace efficacy and improve general decision-making capabilities. This paper aims to shed light on a structured production engineering knowledge management program and its initiatives for enhancing an organization's performance with associated factors such as learning from remote locations and the availability of subject matter experts.
Knowledge management structure has three main pillars: organizational culture, governance, and technology, which are all integrated to obtain an effective production engineering knowledge management structure. The cultural pillar is captured by formulating a two-year plan and implementing knowledge management process requirements, benchmarking the best practices, and revising the target on a regular basis. Technology is captured through the production engineering community of practice, where people gather in one place to share knowledge and best practices. Governance has a structured architectural plan where the key performance indicators of production engineering knowledge assets and events are monitored regularly.
The Knowledge Asset Index was exceeded due to the implementation of several initiatives such as the incubation of specific instruction manuals for Intelligent Field equipment, which aims to address layouts of roles and responsibilities involving all concerned organizations to maintain healthy Intelligent Field equipment. For the Knowledge Events Index, the organization's subject matter expert conducted an in-house Intelligent Field training course and technical publication writing workshops to improve all engineers' awareness and training for more than 200 professionals. With an excellent implementation of the production engineering community of practice plans, the knowledge management team won an award due to a remarkable participation index increase. The results show that well-planned knowledge management has a number of advantages to an organization. Some of these benefits include increased workplace efficiency, which allows consistency in information provided to knowledge recipients, improved skill growth and development in employees, and improved decision making in the organization.
This paper will serve as a motivation to knowledge management structures by implementing knowledge performance measures pertaining to production engineering. The benefits of this process to future quantifications are that it allows even quicker decision-making skills in the workplace and works to reduce organizations' training times, which can result in bridging knowledge gaps.
Pioneering Industry's First Oil Degradable, Nano-Composite Formulations, for HPHT Temporary Sealing
Authors: Roy Ting , Ben Naceur Kamel , Singh Manjinder , Markel Daniel , Harp Leonard , Ardic Hifzi , Wilkinson Christian , Roy Indranil 
Published: April 2022

Abstract
The Oil and Gas industry is continuously evolving and of late adopting novel and new technologies while transitioning to harness sustainable energies. To improve material efficiency and reduce overall carbon footprint, we have seen the evolution of brine dissolvable alloys, dissolvable PGA/composites, and of late dissolvable bulk-metallic-glass-composites and high-entropy alloys. The triggers for dissolution of these materials are often common downhole-fluids of an aqueous-nature. These materials undergo accelerated corrosion via anodic-dissolution or hydrolysis, facilitated by elevated downhole temperatures.
While these technologies have matured over the last decade into readily available and economic offerings, our industry has lacked significant progress in materials which dissolve in hydrocarbons, while remaining unaffected by aqueous fluids. Motivated to bridge this technology gap, we have embarked on a project to pioneer an industry first oil-degradable metal-matrix nanocomposite.
A focused application for this novel material, will be eliminating the use of wash pipes through intelligent use of a port-isolation temporary-seal, preventing communication from ID-to- OD during deployment in brine, while opening up on demand during production. This can be "Game Changing" for Operators, saving them rig-time and costs in the millions of dollars. A oneway ball-valve for deploying sand-screens using our oil-degradable ball as a temporary seal has been envisioned. The ball will seal against flow-ports when running-in-hole, precluding annular- to-tubular communication. Once screens are set, and the well tied-in to flow, produced oil will drive the sealing-ball away. The ball is retained in a cage to allow unrestricted production. In reality, this solution presents challenges. Production of solids, and asphaltenes often build up around the caged ball leading to restricted production, often needing costly intervention. The ideal scenario would be if the ball-seals can be removed by dissolution in the produced hydrocarbons. This will ensure unrestricted production, reduce the possibility of intervention and rig-time loss, all-in-all a step towards lowering our carbon-footprint.