bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overcoming the Challenges of Financing Offshore Wind Projects
Authors: Azevedo Pedro , Grosse Steffen 
Published: April 2019

Abstract
The objective of this paper is to help the various stakeholders involved in offshore wind projects identify and overcome the challenges of financing offshore wind projects. It will present key considerations for debt and equity financing during the development (i.e., early stage), construction, and operational project phases. Additionally, the paper will outline the benefits of adopting a joint go-to-market approach that combines equipment, services, and financing solutions into a single bundled package. Where applicable, the strategies/conclusions outlined in this paper will be validated using real-world case studies, which serve as a benchmark for how projects can be structured to secure high levels of funding.
Funding remains a key challenge for offshore wind projects due to the quantum of capital required and often complex contractual structures. This complexity stems from the large number of contracting parties involved, and the resulting "interface risk".
With utilities less willing to finance projects on balance sheet (i.e., via equity or corporate-level debt), and increasingly partnering alongside co-investors – such as equipment manufacturers and institutional investors—tailoring projects for the project finance market has become increasingly important.
Expert financiers can help bring confidence to lenders by acting as a peer within a bank syndicate. In the case of an original equipment manufacturer (OEM) or solution provider, providing financial support in the form of debt or equity capital to the project highlights how the company has so called "skin in the game", providing the necessary vote of confidence to enable the utilization of newer technologies and consequently reduce capital costs. As many real-world projects have demonstrated, doing so helps to reduce the overall risk profile of the project – ultimately increasing its bankability and improving the likelihood of securing the level of funding required for construction.
Large Deformation Finite Element Analysis of Riser-Soil Interactions with Strain-Softening Soils
Authors: Chen Jinbo , Newlin Jason A. , Zhang Heping , Hu Shuang , Luo Meng 
Published: April 2019

AbstractDynamic analyses of steel catenary risers (SCRs) suspended from a floating platform usually show that the vicinity of the zone where the riser touches down on the seabed is important to fatigue assessments, and can be critical in realizing an economical SCR design or in assessing SCR design life extension. The motivations of the paper are to advance the understanding of the complex mechanism of SCR-soil interactions in a comprehensive yet efficient way, to supplement the extensive model test-based SCR-soil interaction studies in the literature, and to offer a numerical tool to predict the SCR-soil interaction in different clay types. The objective is to investigate the fundamental mechanism of SCR-soil interactions using advanced finite element (FE) analyses. The FE analysis is conducted in Abaqus using the coupled Euler-Lagrangian (CEL) technique to capture the local large deformation surrounding a riser. A strain-softening soil model for deepwater soft clays subject to cyclic degradation is developed based on cyclic direct simple shear (DSS) tests to avoid cycle-by-cycle simulations. The stress-displacement relations are proposed in the FE analysis to avoid the size effect associated with strain-softening soils. The FE analysis results are compared to the test data from the independently conducted model tests and the established results from the literature. Good agreements among different studies are observed.
Applying Artificial Intelligence to Optimize Oil and Gas Production
Authors: Kandziora Christoph 
Published: April 2019

Abstract
The Internet of Things (IoT) — combined with advances in sensor technology, data analytics, and artificial intelligence (AI) — has paved the way for significant efficiency and productivity gains in the oil and gas industry. One application, in particular, has been proven to benefit from these technologies: electrical submersible pumps (ESPs). It's well understood across the E&P industry that nearly all wells must eventually incorporate some form of artificial lift to continue production, and ESPs drive about half of that. Although ESPs are designed to operate in harsh conditions, such as corrosive liquids, extreme temperatures, and under intense pressures, they can fail. Costs for repair or replacement are high but are usually dwarfed by the cost of lost production. In some cases, especially offshore, that cost can run into millions of dollars per day, including idle operational resources and output losses. This paper explores a unique AI-based application that enables operators to preempt costly ESP failures, while optimizing production at the same time. To illustrate, a use case will be shared. As a proof-of-concept and later a pilot project in an onshore oilfield, 30 ESPs driven by pumps ranging in power from as low as 200 kW to as high as 500 kW were deployed and monitored using an AI-supported predictive maintenance model. The positive results are applicable to offshore applications. In one case, the probability of an ESP failure was determined 12 days before an actual failure of the ESP occurred.
Innovative Digital Inspection Methods
Authors: Anderson Stephen , Barvik Sigve , Rabitoy Chad 
Published: April 2019

Abstract
While there is a lot of talk about Big Data Analytics, Internet of Things (IoT), Artificial Intelligence (AI), Real Time Monitoring (RTM), Digital Twin and other methodologies, all of them require, not only data, but accurate, reliable data. This paper describes a new and innovative inspection methodology that combines 3D laser scanning and precise 3D Geometric Dimensioning & Tolerancing (GD&T) metrology data with advanced Non-Destructive Testing (NDT) results. This data is then combined in digital 3D space to give an accurate representation of current equipment condition and mechanical integrity of critical offshore assets. Such inspection and testing can be conducted during manufacturing as a quality check, creating digital baseline records, or on deck during operations, saving significant downtime and costs.
By including metrology and phased array, the described inspection methodology can provide precise digital data and specialized 3D reports that will satisfy not only compliance and regulatory efforts in a more objective manner, but also assist original equipment manufacturers (OEMs), drilling contractors and operators by supplying conclusive and accurate data of equipment condition. This data, based on in-situ NDT and Geometric Dimensioning & Tolerancing measurement information, will support Digital Twin data and operational and maintenance decisions that will preserve the integrity, safety, and availability of the assets.
This innovative inspection solution can form part of a Condition-Based Maintenance (CBM) program where operators can move from time-based programs and use the digital data to determine future equipment performance, work scope, and schedules while maintaining a complete and updated digital condition record throughout the lifecycle of the equipment. The program may predict and prevent problems at early stages, provide strategies that will simplify maintenance activities, and potentially identify manufacturing flaws. More importantly, it can create historical digital data that will change the way the drilling industry operates and satisfy what regulatory agencies have been seeking since the implementation of the new well control rule.
Effects of Uniform and Mega Pitting Corrosion on Residual Strength of Degraded Offshore Mooring Chain
Authors: Farrow Gary H. , Potts Andrew E. , Dimopoulos Simon , Kilner Andrew A. 
Published: April 2019

Abstract
The first phase of the Chain FEARS (Finite Element Analysis of Residual Strength) Joint Industry Project (JIP) aimed to develop guidance for the determination of a rational discard criteria for mooring chains subject to severe pitting corrosion which, based on current code requirements, would otherwise require immediate removal and replacement.
Critical to the development of rational discard criteria is the ability to accurately estimate the residual strength of a corrosion and wear degraded chain, and to have as a benchmark for loss in strength, an accurate estimate of the chain in its as-new condition. A Finite Element Analyses (FEA) residual capacity assessment method was first developed and correlated against available break strength test data of corrosion degraded links [1], and the Predicted Break Load (PBL) of as-new links was established as a benchmark for loss of strength [2].
The validated FEA method for the determination of chain residual capacity was employed as a basis to establish an understanding of the effects of corroded chain and to determine the underlying relationship between loss of chain capacity and both uniform and mega pitting corrosion levels. The investigation sought through the conduct a series of FEA assessments employing a parametric model of idealized degraded chain links to derive the theoretical relationship beteen the residual capacity for varying levels of uniform corrosion, and the residual capacity for varying size, locations and shapes of mega pit corrosion degradation.
This paper presents the findings of the investigation into the effects of uniform and mega pitting corrosion on degraded chain residual capacity and the correlation of the relationship with physical break test data, the findings of which forms the basis for development of a rational guideline for chain discard criteria whereby degraded mooring chain can be assessed in respect of the need for replacement.
Machine Learning Models to Predict Gas Hydrate Plugging Risks Using Flowloop and Field Data
Authors: Qin Hao , Srivastava Vishal , Wang Hua , Zerpa Luis E. , Koh Carolyn A. 
Published: April 2019

Abstract
Recently the concept of "no external gas hydrate control measures" has been proposed, whereby gas hydrate formation can occur in oil and gas subsea pipelines during steady state and transient operations, with the operational window defined by predictive analytic tools. Flow assurance engineers routinely use computer programs, including transient multiphase flow simulators coupled to a gas hydrate kinetics model to simulate gas hydrate formation and transportability. Given the complexity in multiphase flow modeling, modern machine learning technologies, especially artificial intelligence, could be applied to solve high-level, non-linear problems, such as evaluating gas hydrate risk based on measurable process parameters.
In this work, several machine learning techniques, such as regression, classification, feature learning with an algorithm/framework like support vector machine (SVM) and neural networks (NN), are applied to analyze the data sets on: 1) hydrate tests conducted at pilot-scale flowloop facilities (4,500 data points), as well as 2) transient operation field data. The classification/regression model based on flowloop test data uses several independent input variables (features), such as water cut, gas-oil ratio, hydrate particle cohesive force, fluid velocity, oil viscosity, specific gravity, interfacial tension, and time in the hydrate stable zone, to output the hydrate fraction and probability of hydrate plugging in the pipeline. The semi-supervised learning model was applied based on the field data use as input, including water cut, shut-down time (where applicable), and gas-oil ratio to determine the level of hydrate resistance to flow during restart or dead oil displacement after production shut-down.
The flowloop based machine learning model exhibited good prediction accuracies in test and validation processes, and was used to assess the hydrate risks in an actual field. The field data based machine learning model demonstrated the ability to construct field risk maps.
The machine learning technique could be potentially applied in hydrate management to evaluate hydrate risks in subsea oil/gas pipelines. As a complement to more complex transient multiphase flow simulations, this machine learning approach can aid in the development of advanced hydrate management strategies.
Extreme Sub-surface Currents Observed in the Northern Brazil - Suriname Region
Authors: Schiller Rafael V , Smith Rosemary B 
Published: April 2019

AbstractOffshore waters from Northern Brazil to Suriname are subject to extreme curents driven by the North Brazil Current (NBC) and NBC Rings which represent a significant metocean hazard for the O&G Industry. Although extreme surface currents are well known, there is still a gap in the understanding of extreme sub-surface currents in that region. The objective of this paper is to further elucidate the characteristics of significant sub-surface currents and provide metocean guidance to the O&G Industry based on three separate long-term mooring campaigns in the region. Our investigation demonstrates that extreme sub-surface current events exist offshore Northern Brazil, French Guyana and Suriname. The events were mainly characterized by northwestward peak currents from 0.82m/s to 1.22m/s within 150m-300m below the surface. They were more frequent offshore Northern Brazil and French Guyana where events were observed within 2-3 months of each other. Offshore Suriname, only one event was reported in 14 months. Sub-surface current events took place during times when the surface circulation was relatively weak and during times when surface currents were strong and affected by the NBC / NBC Ring circulation. Offshore Northern Brazil and French Guyana, it is suggested that significant sub-surface currents could take place around the time when a NBC Ring is sheeding and the surface circulation is unstable. Extreme sub-surface currents could be decoupled from the surface circulation and that poses an additional challenge in terms of predicting when extreme sub-surface currents could take place. The findings of our study provide a new regional picture of extreme sub-surface currents from Northern Brazil to Suriname and highlight that those events must be accounted for by offshore O&G developments in that region.
Deepwater Well Control: New Training Reflects Critical Challenges and Human Errors
Authors: Ferreira Ivaldo Mesquita , Ferreira Ig Oliveira , Lima Heitor Rodrigues , Santos Otto Alcantara 
Published: April 2019

Abstract
This paper presents how important IOGP recommendations for well-control training were implemented in the courses provided by a Brazilian well control school using its proprietary drilling simulator. The courses now shed more light upon the crew member/designer’s needs to be successful in maintaining the integrity of the safety barriers including non-technical skills.
The simulator incorporates features that improve the understanding of specific issues related to deepwater and ultradeepwater well control, such as the importance of early kick detection due to narrow drilling window, the advantages of performing dynamic leakoff tests and dynamic volumetric well control methods that reduce the maximum peak pressure and maximum gas flow rate at the choke, the importance of avoiding gas in the riser by properly removing the trapped gas below the BOP, among others.
Barrier Fluidless, Sealless Seawater Canned Motor Pumps
Authors: Stover David L. , Travaini Luca 
Published: April 2019

Abstract
The oil and gas industry continues to push toward subsea pumping technologies that minimize required support systems and increase system reliability. Canned motor technology has been applied successfully in other applications to achieve similar objectives including driving a subsea twin-screw pump. Applied subsea, canned motors eliminate the need for any barrier fluids within the motor, the myriad of systems and complexities necessary to store and replenish these fluids, and the mechanical shaft seals required to prevent the leaking and/or contamination of these fluids within the motors.
As a direct adaptation of proven applications, seeFigure 1, subsea water treatment is ideal for canned motor technology. Therefore, a development has been initiated and will be completed in 2020 to demonstrate the first truly barrier fluidless, sealless subsea pump solution.
This purpose of the paper is to identify the novel elements of this technology, review the system configuration, and describe the process and challenges of this ongoing design and qualification initiative.
Process Improvement Based on a Gap Assessment of NASA and O&G Risk Management Processes
Authors: Mayfield James Allen 
Published: April 2019

Abstract
What can the aerospace safety and systems engineering community teach the commercial Oil and Gas (O&G) industry about streamlining risk management processes when NASA is not known for its streamlined practices and how much improvement can be realized by the O&G industry, if any? Addressed in this paper are these basic questions. This assessment identifies improvements to risk management requirements for an O&G company. The methods of performing the assessment and developing recommendations for improvements are provided. These recommendations clearly show the benefit of incorporating these processes for O&G communities.
Through the mishap investigation reports due to lost Space Shuttles and other similar incidents, NASA has developed mature processes associated with risk management. In a similar manner, the O&G industry has had to develop its own processes through mishaps they likewise have encountered. A detailed and holistic examination was conducted of a major O&G company’s risk management procedure requirements, starting with risk planning, then risk assessment, risk response, monitoring and control of the risk, risk learnings and closure, and finally, risk governance. Upon completing the assessment, recommendations for improvement to the company’s risk management procedure requirements were made.
NASA’s risk management process and Systems Engineering handbook were used to examine the O&G company’s risk management procedure. Each requirement within the procedure was placed into a spreadsheet and examined for appropriateness, with roles and responsibilities mapped to each of the requirements. Areas of benefit were identified and examined for feasibility, with recommendations for improvement presented to the company’s risk management personnel.
The paper presents the findings of the assessment, and recommends improvements based on this assessment. Experts within both the O&G and aerospace industries, with extensive experience in mishap investigations, reviewed the results of the assessment and the recommended improvements. Feasibility of implementation was determined by examining the recommendations from a cost, resource and technical perspective.
SLWR Innovative Design Methodology Supporting Concept Engineering Through to Project Cost Optimisation
Authors: Diakonova Elena , Bonnet Gilles , Brouard Yann 
Published: April 2019

Abstract
Steel Lazy Wave Risers are one of the most efficient and compliant riser systems for deep-water projects.
From a design perspective, designers have to deal with parameters such as the configuration itself, interaction with the FPSO, environmental loads, installation vessel capabilities and commercial issues like installation and procurement costs.
This paper presents how to assess the need for Steel Lazy Wave Risers (as opposed to conventional Steel Catenary Risers) and how to develop a state of the art design by using an innovative methodology based on the efficiency of an optimisation through modern technology computation.
The objective of the optimisation is to propose a riser configuration that allows the best compromise between all parameters, while remaining fit for purpose and cost-efficient. A methodology was developed using a Python script as an interface between Orcaflex software and the user-defined parameters to best respect the project specific weighted criteria.
It will also highlight how the methodology can be applied for fast track conceptual studies, enabling the end user to account for optimised design at the start-up of a field development. All the constraints and objectives will be considered with possible challenges and solutions to be presented.
The final design of a lazy waver riser is a compromise between all constraints.
This paper provides comprehensive information relative to all the stages of steel lazy wave riser design, from the initial draft configuration to the most optimised and cost-efficient one. A few optimisation possibilities achieved thanks to this process will be developed and illustrated through examples. The concept can be applied to early stage engineering or during the course of a project.
Main Factors Impacting Oil Projects Return: A Sensitivity Analysis
Authors: Lucchesi Rodrigo Dambros 
Published: April 2019

AbstractPerforming robust economic valuation is critical to ensure success on oil development projects. In a dynamic market with ever changing variables, risks and uncertainties must be well analyzed and mitigated to prevent less than expected economic returns in mega-projects such as an offshore deep-water oil field development. This study aims to evaluate what are the most important factors that should be considered when assessing risks in a project economic valuation, using Brazil’s Production Sharing Contract (PSC) fiscal system as an example. A sensitivity analysis was performed in a standard offshore oil production project using the discounted cash flow method. First, a base scenario was calculated, and then, four key assumptions were chosen to be tested – oil prices, capital expenses (capex), operational expenses (opex) and recoverable reserves - and changes of + and - 20% in each, one at a time, were applied to the base scenario, and their impact on the internal rate of return and government take were measured. Findings indicate that, at least in the Brazilian PSC case, oil price is the most influential parameter in the project profitability, presenting an almost perfect positive correlation with the rate of return. Oil price is also the most difficult assumption to project and the one that is completely out of companies’ control, which poses them a significant challenge, to be able to keep its projects economical under volatile prices. Main investment decision gates happen years before first oil is produced, so the level of uncertainty on this parameter is very high. This study reinforces the concept that a good oil price forecast is paramount in projects valuation. Additionally, companies should always make investment decisions based on multiple oil price scenarios to determine the project’s financial risk.