bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automotivation: What we Can Learn from Cars
Authors: Mounir Abou-Assaad Amine , Steven Holmes John 
Published: April 2020

Abstract
"If you have always done it that way, it is probably wrong."
Charles Kettering
Our history as an Oil & Gas industry is rife with technological firsts and innovative technologies. From the turn of the 20th century, the innovations in technology in this sector have been a driver for technology in multiple industries, from medical to aviation. Over time, the industry became reluctant to innovate in many areas since the technologies in the field were sufficient. The result has been that the Oil & Gas Industry is now falling behind other industries at introducing innovations and breaking the traditional ways of applying technology to products [13]. This is not to say that there are not some amazing new products and engineering feats coming out of different corners of our industry; or that there are not great minds still at work inventing and innovating to make our industry safer and more efficient. While most of the industry relies on custom products making each rig unique, the next big improvement in reliability and total cost of ownership will be standardized configured products.
This paper will explore case studies from other industries including the transportation industry and specifically automotive. This study will describe how those learnings can be applied to Oil & Gas (O&G) and provide specific cases in O&G new product development (NPD) that have implemented these learnings. The automotive industry has contributed methods of improved quality, just-in-time inventory, true vendor partnering and component standardization, to mention a few, to industry at large. Many of the learnings apply directly to the development of equipment for drilling rigs; but, due to the differences between a high-volume low mix market and a low-volume high mix market, some of the learnings may not apply. Through up and down cycles automotive manufacturers continue to be leaders in innovation both in their products, and the processes that bring us their products.
The paper will also take a deep dive look at the technological specifics that we as an industry can look at to enable the streamlining of our products from the design phases to manufacturing, through testing and validation and finally commissioning. The paper will examine engineering solutions that the industry can adopt and integrate into various designs. How OEM’s can leverage the competences of their very capable and willing vendors will also be examined. Specific examples of how these learnings can apply in Oil & Gas will be drawn from a recent Blow Out Preventer control system design. As technology and needs evolve, so must our approach to solving our challenges.
Condition Monitoring Without Machine or Field Data: Transforming Maintenance System Information to Measure Equipment Degradation
Authors: Pereira Paul Christopher 
Published: April 2020

Abstract
The objective of this study was to accurately measure the degradation of equipment indirectly (without the use of sensor or machine data). This was done in a semi-autonomous manner by leveraging the bulk data in the organization's maintenance system and its underlying metadata relationships. This study included a novel combination of two traditional techniques for asset management: The P-F curve from Condition Based Maintenance (CBM), and the "Crow – United States Army Material Systems Analysis Activity (Crow-AMSAA)". The P-F curve is a widely accepted tool to represent the degradation and eventual failure of assets. It is used to approximate the lead time to a specific failure occurring, where "P" represents the point where a failure can first be detected, and "F" represents the point where the actual functional failure occurs. Traditionally this curve is derived in a CBM system using knowledge-based or data-driven approaches that depend heavily on field sensor data. This study instead uses a statistical based method (Crow-AMSAA) to approximate the curve based on properties of maintenance record data and the intensity of data generation within the maintenance system. As theorized in previous studies, we can indeed observe changes in maintenance record properties prior to rig stoppage events (equipment failures) and approximate the P-F curve. The underlying input variable from the maintenance system was shown to be the Mean Time Between Corrective Maintenance (MTBCM), which is derived from qualitative and quantitative properties of maintenance records (work orders or jobs). When this value is visually modelled over a period of time based on the Crow-AMSAA method, a visual representation of the P-F curve can be easily identified. It was also shown as possible to determine a threshold value for taking action prior to failure. To represent this, the Crow-AMSAA output graphics were augmented with additional metadata and features that underly the maintence records. With these proper visual aids and regression techniques implemented, it is possible to identify threshold values in units of MTBCM, as well as days (unit of time), for specific assets. This allows for actions to be implemented prior to imminent failures caused by degradation growth.
Design and Analysis of Stakeholder Oriented Critical Paths for Offshore Decommissioning Projects in the United Kingdom and Australian Landscape Using Mixed Methods
Authors: Tung Aaron 
Published: April 2020

Abstract
Each oil and gas region have their own unique decommissioning regulations, risks, and stakeholder landscapes. For example, in the United Kingdom, commercial fishermen takes up 75% of all statutory consultees for the Decommissioning Programme (OPRED, 2019). Whereas in the Australian landscape, remote areas such as the North-West Shelf are dominated by recreational fishermen organizations (Shaw, Seares, & Newman, 2018).
One way to gain an in-depth understanding of stakeholder landscapes of the different decommissioning regions is through the development and analysis of stakeholder oriented critical paths. In this paper, the development and analysis of stakeholder oriented critical paths for the United Kingdom and Australia will be discussed to show how variation in regulatory, technical, and stakeholder environment can influence decommissioning decisions and impact decommissioning projects.
The critical paths were designed using mixed-methods – a combination of case studies and semi-structured interviews in order to take into account the interdisciplinary nature of decommissioning. One critical path design was developed for the United Kingdom and the other one for Australia. Each of the critical path design consists of two versions – a simplified and a detailed version.
Analysis of the critical paths yielded that the work breakdown structure of decommissioning remains the same across different regions. However, the difference in technical challenges, regulations, and stakeholder landscape have an effect on the philosophy, strategies, cost, and schedule of the decommissioning project. It is therefore important for operators to thoroughly understand the decommissioning landscape that they are in prior to planning decommissioning projects.
Concept Design of Floating Substation for a 200 MW Wind Farm for the Northeast U.S.
Authors: Shelley Steffen Allan , Boo Sung Youn , Kim Daejun , Luyties William H. 
Published: April 2020

Abstract
Floating offshore wind turbine technology, much of it developed domestically, is rapidly advancing and is in the early implementation phase, while floating substation technology is still at an early development stage. This study presents novel floating wind power substation platform designs for deepwater wind farm applications. Two types of floating substations configurations are considered to compare technical and cost performance: a semi-type "X-WindStation" and a TLP-type "TX-WindStation". The floating substation platforms are considered for a 200 MW wind farm located in 100 m (328 ft) water depth off the Northeast coast of the United States. The floating substation supports a two-deck electrical power facility that provides sufficient electrical power equipment layout area and includes temporary quarters.
Both floating substation platforms are evaluated for global performance and mooring systems (catenary for semi-type and tendon for TLP-type) with the site design metocean conditions for the extreme and survival storm seas. The results are assessed in accordance with industry standards ABS and API, and offshore engineering practices.
Capital expenditure (CAPEX) of both substation platforms for a 200 MW farm is estimated by including the electrical substation, platform hull, mooring lines, anchors, integration, installation and commissioning costs. Installed CAPEX costs of the platforms show that the semi-type substation platform cost is lower than the TLP-type cost for the case where each tendon has a dedicated anchor, whereas the cost for the TLP-type with two tendons sharing an anchor is highly comparable to, if not less than, the semi-type platform.
Predicting Hydrate Plugging Risk in Oil Dominated Systems using a Transient Hydrate Film Growth Prediction Tool
Authors: Qin Hao , Qu Anqi , Wang Yan , Zerpa Luis , Koh Carolyn , Bodnar Scot , Daly Sean , Palermo Thierry , Mateen Khalid 
Published: April 2020

Abstract
The formation of gas hydrates is considered a major flow assurance issue resulting from high pressure and low temperature conditions during petroleum production in deep water developments (Sloan and Koh 2007). Gas hydrates are solid crystalline compounds, which can be formed when the pressure and temperature reaches the thermodynamically stable hydrate zone. Hydrates can plug deepwater flowlines, which may lead to the rupture of flowlines and spill or leakage of oil and gas (Sloan 2010). As a result, production and economic losses may exist during operation.
illustrates the oil-dominated pipeline plugging mechanism caused by hydrates in an oil dominated pipeline. The process is fairly complex, with phenomena such as: (1) water entrainment or dispersion of water droplets in the continuous oil phase due to fluid shear and surface-active components in the oil; (2) hydrate formation, with hydrate growth at the water-oil/water-gas interface under a certain degree of thermal driving force; (3) hydrate agglomeration and deposition; (4) particle jamming and hydrate plugging. Among these mechanisms, film growth, deposition (bedding) can be categorized into hydrate deposition.
Traditionally, thermodynamic approaches are used to prevent the formation of hydrates in flowlines, including the injection of thermodynamic hydrate inhibitors (THIs), such as methanol or glycols. THIs work by shifting the hydrate phase equilibrium conditions to a lower temperature and higher pressure, which makes the condition unfavorable for hydrates to form (Sloan and Koh, 2007). However, for THIs, large amounts of chemicals are needed, which will introduce high OPEX and CAPEX (Creek, et al. 2011). Hydrate risk management methods have gained popularity, as they will largely reduce the cost. The latter more recent concept suggests that by injecting low dosage hydrate inhibitors (LDHIs), including kinetic hydrate inhibitors (KHIs) and anti-agglomerants (AAs), the risk of flowline blockage can be controlled, even though the flowline may enter the hydrate stability zone. To support this concept, a comprehensive simulation tool is critical to predict the different hydrate plugging mechanisms mentioned above.
Performance of an Acoustic Sensing Array in an Energetic Tidal Channel
Authors: Raghukumar Kaustubha , Chang Grace , Spada Frank Wayne , Jones Craig Alexander 
Published: April 2020

In support of environmental monitoring technologies to evaluate the acoustic impact of marine energy operations, a cost-effective compact array of acoustic sensors has been developed that characterizes, classifies, and provides accurate location information for anthropogenic and natural sounds in real time. The NoiseSpotter consists of a three-dimensional bottom-mounted array of three acoustic vector sensors cabled to a surface buoy for real-time telemetry. Each sensor measures acoustic pressure and three-dimensional particle velocity associated with the propagation of an acoustic wave.
The NoiseSpotter was deployed in an energetic tidal channel with a tidal oscillation that can approach 3 m. Performance characteristics in the presence of the resulting flow noise is quantified, and a flow noise suppression system is quantitatively shown to significantly improve performance, with flow noise suppression close to 15 dB. Performance is significantly improved when the sensors are housed in a flow noise removal shield, which provides acoustic transparency while reducing non-acoustic signal contamination. Long term durability of this flow-noise suppression shield is demonstrated using biofouling experiments. The real-time telemetry of data digests is demonstrated to allow rapid decision-making in response to measured sound intensity levels.
Digital Twin for Operations - Present Applications and Future Digital Thread
Authors: Podskarbi Mat , Knezevic David J 
Published: April 2020

Abstract
We present a structural digital twin system based on component-based parametric reduced order modeling using Reduced Basis Finite Element Analysis (RB-FEA) framework. This enables fast, detailed, and holistic modeling of large-scale structures, such as floating and fixed production and drilling platforms, and crucially, the digital twin's parametric nature and fast solve time enables the system to be connected seamlessly with inspection and sensor data. We demonstrate RB-FEA based structural digital twins, and capabilities for connecting them to sensor data and data science methods to increase predictive power and engineering insight. We show how the digital twin is a key enabler for a Digital Thread – a data-driven architecture that links together information generated from across the product lifecycle.
Inspection data, such as thickness measurements, can be directly mapped into the structural digital twin. Sensor data, such as motion and strain can be transformed into loading data, e.g. to estimate sea-states and calculate stress and fatigue accumulation based on actual conditions, or to "tune" model parameters to match data-based measurements, such as mode shapes and frequencies. This enables continuous tracking of the asset and assessment of its current state, based on quantitative and detailed structural analysis, at any time. Ultimately the structural digital twin provides an interpretation layer for integration of monitoring and inspection data, leading to a fully automated digital thread.
We present a framework, based on a cloud-based simulation platform and Python-based scripting, to automate the workflows listed above. Digital twin provides a single source of truth about asset condition and allows data driven communication and decision taking between multiple stakeholders – operators, contractors, regulators, etc.
We will show examples of real-world applications of RB-FEA digital twin for FPSO and Jacket platforms and development work for digital thread with emphasis on data driven value creation along the entire life cycle of the asset.
The Reduced Basis FEA based structural digital twin is a key enabler of data driven digital thread in addition to sensor frameworks and data science systems. RB-FEA provides fast, parametric, and physics-based analysis providing a transparent interpretation layer for data obtained from other systems. It provides a key element allowing knowledge management along asset lifecycle – from concept to decommissioning.
High fidelity, physics based global simulations, such as RB-FEA digital twins, are a key enabler for effective digital transformation of industrial operations. They enable real-time insights into asset performance that are otherwise unattainable, providing tools for Asset Integrity Management, Risk Based Inspection, Automation and Optimization of Operations as well as enabling full digital thread enhancing Safety and CAPEX and OPEX.
A Journey of Floating Production Systems in Brazil
Authors: Padua Macio Mattoso , Goulart Maiza Pimenta , Mastrangelo Carlos Ferraz , Loureiro Rodrigo Reis , Castro Gustavo A Villela , João Leonardo Vilain , Maddalena Marco Antonio 
Published: April 2020

Abstract
This paper describes the history, challenges, solutions and evolution of the Floating Production Units in Brazil. The first floating unit was on stream in 1977 at Campos Basin in Brazil. It produced from a single well with a drilling riser and dry-X-tmas tree to a MODU converted into a floating production unit and exporting to a spread-moored shuttle-tanker by a floating hose. Now, more than 40 years later, over 2,400 meters of water depth at Santos Basin are moored several floating production and storage units (FPSOs). It houses over 40 thousand metric tons of complex topsides exploiting ultra-deep wells from the pre-salt prospects. Along the evolution of the FPSOs, one major stepping-stone was the implementation of lessons learned as a feedback to create a strong foundation. This paper will depict field demands and solutions adopted to deal with the differing climates and environments as well as other particularities to develop FPSOs in Brazil. To face the technological challenges to efficiently and safely produce from ultra-deep water complex pre-salt reservoirs required the consolidated use of the expertise and experience from past projects.
Initially Petrobras was well known worldwide as a Semi-Submersible company, with a unique proficiency to develop converted Semi-submersibles and other new constructions. This expertise is still present to this day, but the company has since pioneered and consolidated the use of FPSOs worldwide, leading the industry in this concept.
Petrobras led the industry effort to approve FPSO international standards, local regulations with agencies and regulatory bodies by the end of ‘80s to early ‘90s. This paper will focus on the evolution of this industry, highlighting the achievements, and address the new developments and opportunities for the future.
State-of-the-Art Development of Offshore Water Deaeration Processes Utilizing High-Purity Nitrogen for Chemical Free Oxygen Removal
Authors: Isdahl Ole Morten , Seltveit Tor Olav 
Published: April 2020

Abstract
Conventional deaeration of seawater for water injection use expensive chemical scavengers and heavy vacuum towers, which occupy valuable space on offshore installations. The scope of this study is to investigate, compare, and further advance the development of two state-of-the-art deaeration technologies which solve the aforementioned issues. The first method, compressorless deaeration with the use of stripping gas is a newly developed modification of an already efficient, light, compact, and worldwide implemented technology. This technology uses pure nitrogen in a regeneration loop, together with static mixers which allow oxygen mass-transfer from seawater into the gas phase. The second method utilize the same proven nitrogen regeneration loop in combination with novel membrane deaeration technology.
Advanced dynamic process simulations, combined with field data, mechanical design and process calculations are utilized to quantify process parameters and design requirements for the two technologies. The results are presented and used for discussing advantages, disadvantages, possibilities and further development needs of both the stripping gas- and membrane technology.
Results show that it is possible to further increase the robustness of the stripping gas-technology by eliminating the compressor. A clever ejector system with turn-down capabilities ensures the technology's advantage of positive operating pressure and utilizes energy from the seawater flow to compress the nitrogen. Power calculations, turn-down possibilities and oxygen removal efficiency at various operating conditions are presented. A suggested design for membrane deaeration is also presented, along with calculations and comparisons to the stripping gas technology, especially regarding flow rate capacity and the economies of scale. The main advantage of the proposed membrane technique compared to existing membrane concepts is the high-purity nitrogen regeneration loop, which offers improved mass-transfer capabilities across the membrane.
The novelty of this work the feasibility of successfully operating a compressor-less, efficient, compact deaeration system on positive pressure. Additionally, the stripping gas technology requires no chemical scavengers in order to obtain an oxygen concentration lower than 10 ppb. The membrane deaeration process can also achieve low oxygen concentrations without chemical scavengers and it is further found that the technology might be economically viable compared to stripping gas for low flow rates.
Virtual Sensors for Mooring Line Tension Monitoring
Authors: Jaiswal Vivek , Brown Aaron Austin , Yu Mengxi 
Published: April 2020

Mooring line tension monitoring is required for permanently moored floating offshore platforms by some regional regulators and classification societies. This requirement is typically satisfied by installing physical sensors that directly measure the line tension. Experience shows these sensors have relatively short life compared to the platform operational life and consequently they need to be changed several times thereby increasing the operational expenses. It is also possible that changing the sensors in the field may not be feasible due to access and safety issues or it may be prohibitively expensive, which could lead to the platform operating without meeting the regulations.
This paper presents a machine learning based model, which we call ‘virtual sensor’, for predicting the mooring line tensions based on the platform’s heading, horizontal position and six-degrees-of-freedom (6-dof) rigid body motions. The model’s development and testing are demonstrated with the help of data generated through numerical simulations of a permanently moored semi-submersible. When deployed in field, the inputs to the virtual sensor would be obtained from the global position system (GPS) and accelerometers. Both the GPS and accelerometer are cheaper to install and maintain, reliable and easy to replace.
The neural network model is pre-trained using a dataset of 5000 static simulations and further fine-tuned with 48 dynamic simulation cases. Model performance on four mooring lines are presented in the study. The accuracy of the model was assessed by determining the percentage of predictions with errors within ±5% of the simulated mooring line tensions. Three of the mooring lines achieved accuracy greater than 90% and one mooring line achieved 77% accuracy. The relevant limitations of the study and future work are discussed in the paper.