bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pilot-Scale Demonstration of New Compact CO2-Capture Technology at Elevated Pressures, and Design of Large-Scale Demonstration
Authors: Isdahl O. M. , Shamshiri S. 
Published: April 2024

Abstract
Compact, and lightweight solvent-based CO2-capture technology is developed. The technology has undergone pilot-scale demonstration and extensive testing. The aim of this research is to systematically quantify the effects on the process variables associated with pressurized CO2-capture of flue gas streams or other process streams, encompassing both low and high CO2 concentrations. The objective is to verify the technology and to obtain the data necessary for the design of a large-scale demonstration plant, capable of capturing CO2 under real operational conditions. Results from four months of operation of the pilot are presented. The novelty of the technology lies in the CO2 absorption aspect of a solvent-based capture technology, utilizing static mixers and separators for contacting the gas and liquid phases. Consequently, the pilot scale absorption unit has been integrated into an existing solvent regeneration system. The solvent utilized in the demonstration is a 30 wt% monoethanolamine (MEA) solution. Pressurized capture is benchmarked against previous research conducted using the same regeneration unit but previously done with a conventional atmospheric absorption column. The research project has performed extensive testing under atmospheric conditions, yielding substantial amounts of comparable data between conventional atmospheric CO2 capture and the new technology both at atmospheric and pressurized conditions. The results show a greater than 95% CO2 capture rate both for low (2.5 vol%) and high CO2 concentrations (10 vol%). Further, the testing shows significant improvement of mass transfer of CO2 between the phases, and reduced size requirements both from a physical aspect related to dimensions of gas piping, but also with regards to the size of the absorption equipment (i.e., Mixer, separator, and piping in between those two elements). The results obtained have been sufficient to design a large-scale demonstration plant, and dimensions, size, cost, energy requirement and OPEX considerations of a full-scale system will be presented. The novelty of the technology revolves around developing a compact CO2-capture system that can be retrofitted into facilities that has existing emissions points, but most importantly, being able to enable CO2 capture on offshore installations that is not suitable for conventional technologies. The technology is likely to provide a significant cost reduction from a CAPEX perspective due to the reduced size and weight. Capturing CO2 in a compact way at pressurized conditions is likely to add great benefits. Gas turbines manufacturers are developing methods of exploiting the pressurized exhaust after the compression stage upstream expansion to facilitate high pressure CO2-capture, while preserving the energy. The presented technology can be an enabler in this market and bring down cost, size and energy consumption for gas fired power production with CCS.
Advanced Offshore Hazard Forecasting to Enable Resilient Offshore Operations
Authors: Mark-Moser M. , Romeo L. , Duran R. , Bauer J. R. , Rose K. 
Published: April 2024

Abstract
Hazards in the offshore environment can imperil successful energy operations, whether those operations are conventional, renewable, or for decarbonization. The expanding accessibility of data science and the advanced applications of machine learning (ML) models creates an opportunity to assess potential hazards and the infrastructure they impact. We present a use case demonstrating the combined application of published ML tools to U.S. federal waters of the Gulf of Mexico, an actively explored region for offshore energy that is affected by variable metocean conditions and geologic processes contributing to potential hazards. This paper demonstrates the streamlined use of ML tools to illuminate potential cascading risk events posed by seafloor hazards to pipeline infrastructure, as well as the hypothesized fate and transport of released material in the event of a pipeline rupture. We apply an ML-informed submarine landslide susceptibility tool (ML-LSM) which analyzes spatial features including slope and sediment type using a gradient-boosted decision tree (GBDT) algorithm to produce a susceptibility map in addition to the Climatological and Instantaneous Isolation and Attraction Model (CIIAM), an advanced Lagrangian model to predict material transport based on typical metocean conditions. These models were applied to the Gulf of Mexico to produce spatial results based on the features respective to the seafloor and metocean environments. The Advanced Infrastructure Integrity Model (AIIM) tool, which uses big data and ML models including GBDT and artificial neural networks, was applied to provide a preliminary forecast for pipeline integrity. Intersections of submarine landslide susceptibility, potential for infrastructure integrity loss, and material transport are highlighted amongst the results, which are presented spatially. The combination of these models utilized ML analytics to provide multiscale insights into potential future risks to energy infrastructure. Results of AIIM, in corroboration with various reports, show most existing pipelines are forecasted to be operating past their original design life. The ML-LSM map indicates locations with high landslide susceptibility. Comparing the ML-LSM and AIIM results, we are able identify potentially vulnerable structures that are at greater risk, or those in areas with lower landslide likelihood that may be potential candidates for lifespan extension or retrofitting to support alternative energy strategies. The results of the CIIAM model are integrated to indicate material fate-and-transport complications in the event of infrastructure rupture. Areas of potential bias and recommendations for model tuning are also discussed.
Site Investigation and Risk Evaluation Using the Spatial Environmental Assessment Toolkit
Authors: McWilliams S. , Roberts J. , Jones C. A. , Nelson T. R. , Chartrand C. , Olson S. 
Published: April 2024

Abstract
Presently, marine energy (ME) deployments are absorbing unsustainable costs and timelines associated with planning and permitting to get projects in the water (up to 25% of total project cost, which is more than double comparable offshore energy projects at approximately 10% of total project costs; Kramer et al. 2020; Peplinski et al. 2021). To overcome this challenge, the Spatial Environmental Assessment Toolkit (SEAT) is in development to provide the highest-quality site characterization and a priori understanding of the potential environmental impacts using numerical modeling tools and available site data to reduce uncertainty. Reduced uncertainty equates to a reduction in resources required for planning and environmental permitting and a more streamlined path to realized commercial-scale projects.
In this work, numerical modeling and mapping tools are linked together within SEAT to assess ecosystem impacts due to marine energy installations and evaluate optimal ME array layouts based on meaningful site and ME device physics. Of utmost importance is the ability of ME developers, regulators, and stakeholders to develop ME array layouts that maximize energy production, support environmental benefits and Powering the Blue Economy applications (e.g., coastal resiliency, desalination), and minimize potential undesirable environmental effects.
The SEAT is an open-source graphical user interface (GUI) that aggregates numerical model results and spatial receptor data to evaluate the potential risk of change and subsequent impact on the environment being developed for ME. The numerical models can represent the presence of wave, tidal, or river energy converters in their respective environments and evaluate device and array generated site changes in hydrodynamics (e.g., wave fields, water currents), sediment and larval dynamics (e.g., benthic, spawning habitats), and propagation of new acoustic signals (e.g., hearing thresholds).
The toolkit of linked models and site-specific receptors will ultimately allow developers to determine optimal designs for MRE deployments that maximize power performance and benefits from changes that promote project resiliency while minimizing the potential for unwanted environmental effects. The SEAT is an integrated communication tool with which regulatory agencies, stakeholders, and industry developers can effectively evaluate the complex information required for the permitting process thereby reducing the time and costs associated with the process.
Managing Uncertainties in Offshore Wind Foundation Concept Design: A Comprehensive Approach
Authors: Orihuela T. H. , Kadivar M. , Subramanian S. , Sullivan P. R. 
Published: April 2024

Abstract
This paper addresses the complexities and challenges faced in the early stages of offshore wind turbine foundation design. The focus is on understanding and managing the uncertainties inherent in Wind Turbine Generator (WTG) parameters, MetOcean data, geotechnical and geophysical characteristics, and clustering strategies. It explores the critical role of WTG parameters, including loading effects and natural frequencies, and their impact on foundation design. The paper also delves into the significance of accurate MetOcean data in determining environmental loads and examines the stages of geotechnical and geophysical assessments that provide valuable insights for concept design. A key aspect of the study is the clustering strategy, which optimizes the design process by minimizing the number of distinct foundation designs required, especially in large wind farms with diverse environmental conditions. This comprehensive approach addresses the varying levels of uncertainty in data and design parameters, offering solutions to balance accuracy with available information. The paper aims to guide practitioners in navigating the complexities of offshore wind foundation design, promoting efficient, cost-effective, and reliable solutions.
Using Integrated Computational Materials Engineering for Oil and Gas Applications
Authors: Whelan G. 
Published: April 2024

Abstract
Integrated Computational Materials Engineering (ICME) is an approach to materials design, optimization, and insertion as well as solving challenges on implementation and selection of existing materials using a combination of physics-based modeling and machine learning methods. In the present work QuesTek will demonstrate how ICME can be used to improve mechanical properties, corrosion properties, and processability of common structural materials used in oil country tubular goods (OCTG).
This work uses QuesTek's ICMD® software platform including thermodynamics- and kinetics-based databases and modeling as well as physics-based analytical modeling and simulation approaches to predict process-structure-property relationships in structural alloys. Using these predictive modeling tools, the composition and processing are optimized to achieve improved performance.
QuesTek will demonstrate results of composition and heat treatment optimization on mechanical and corrosion properties. Specifically, stress-corrosion cracking susceptibility and strength of alloys was explored and the sensitivity within specification ranges was examined. The results showed that these methods can be used to tighten specification ranges and adjust heat treatments to improve robustness of material performance for a given application.
Integrated computational materials engineering (ICME) is a relatively new approach to materials engineering which leverages the many advancements in both physics-based modeling and computational speed over the last couple of decades. The materials genome initiative has pushed for the utilization of ICME to improve novel materials design and development as well as improving alloy optimization, qualification, and troubleshooting of materials challenges for insertion of existing materials into new applications. This methodology has been growing in use in many industries (e.g., aerospace, space, defense, biomedical, automotive, nuclear, etc.) but its use in the Petroleum industry is still relatively limited. This work outlines how this approach could be adopted for practical oil and gas applications, and what the benefits would be.
Integrity Management for Lifetime Extension of Offshore Structures
Authors: Hauge M. , Jensen Ø. 
Published: April 2024

Abstract
Offshore structures are designed for safe operation until the end of a pre-defined design life. However, the value of a life extension beyond the original plan can be very large. Continued production from existing facilities has potentially lower cost and reduced carbon emissions compared to replacement of facilities. This is indeed the case for oil and gas production where additional near-field resources can be unlocked by tie-ins to existing facilities, but also for offshore wind projects where the energy production will be maintained over a longer time. Longer life will therefore increase the energy output and make the renewable energy more competitive.
Integrity management for structures subjected to fatigue loading, and corrosion attacks, has traditionally been based on ‘safe life’ design principles. This design philosophy require that the integrity shall be maintained over a certain time interval under normal operational follow-up and without condition monitoring or integrity assessment during operation. The design life can be updated if more precise design data can be introduced, e.g. environmental loading conditions based on real data from operation. If the experienced loading is lower than assumed in design, the life can be somewhat extended. Lifetime extension beyond this will require a measure of the current condition of the structure as basis for an integrity assessment. This approach is termed ‘condition-based’ integrity management where we initially assume that the structure has infinite life if the condition can be monitored, and integrity maintained. The condition monitoring can either be continuous measurements or discrete inspections where the inspection interval is managed as part of the integrity assessment.
As offshore structures are large, inspection, maintenance and repair are challenging tasks. The technology development required to support life extension and late life integrity management is therefore divided into three tasks: Improved inspection and condition monitoring technologiesImproved determination of the representativity of inspection results to assess overall integrity (including uninspected locations)Improved accuracy of fatigue calculations, both in terms of S-N and crack growth analysis.
A major obstacle for improvement is the large variation in the current standards and recommendations for fatigue assessment. To ensure safe assessments that can be verified by independent parties, a common platform is needed. This platform should include aligned principles for all relevant technical aspects of the assessment. For fatigue assessment this includes variable amplitude loading, sequence effects, balance between initiation phase and propagation phase as well as environmental effects. For corrosion assessment the corrosion propagation model and the related environmental effects must be well defined.
Bonga FPSO – The Key Levers in Ensuring Reliable Performance of Critical Rotating Equipment
Authors: Akinyemi Oluwaseun , Odebeatu Chike , Nwajiuba Chigozie , Agugua Godbey , Atebe Orobome 
Published: April 2024

Abstract
This paper is a critical review of the application of the apposite brownfield total equipment care (TEC) principles and concepts largely contributory to the higher rotating equipment reliability and availability figures in the Bonga Deepwater operation. The approach defines how the performance of an ageing fleet of rotating machinery susceptible to myriads of production challenges including changing production fluids chemistry, reservoir pressure decline, equipment obsolescence and reliability reduction of ancillary equipment, supply chain disruptions effect of COVID – 19 and its aftermath and others has been unlocked in a cost-effective manner to support the bottom-line business aspirations and achieve 1 billion barrels milestone. This paper is one of a series of Bonga themed papers proposed for OTC 2024.
The Bonga field journey to One Billion Barrels started with the launch of the Bonga Business Improvement Plan (BBIP) in 2016 with keen focus on improving on four (4) critical systems per year through End-to-End system reliability improvement, Asset register update, Reliability centered maintenance, Critical Sparing reviews, Surveillance refresh and Preventive Maintenance Optimization. Key strategies deployed are: Embedding Proactive Technical Monitoring (PTM) to aid in early identification and mitigation of threats prior to becoming big issues, by leveraging on technology tools such as Exception Based Surveillance (EBS), SmartConnect, Plant Information, Solar InSight, and System-1 amongst others, Deepening Failure Investigations by deploying Causal Reasoning methodology across business (including HSSE type events) to understand root causes and systemic issues, and driving Maintenance Efficiency, capacity & capability building through strong collaboration with major rotating equipment manufacturers during planning and execution of major overhauls, utilizing onsite workshop and corporate workshop onshore for major maintenance activities not limited to valve overhauls, electric motor repairs, and pumps, and improved execution strategies resulting in optimized maintenance costs.
With our Proactive Threat Management approach, daily surveillance, strong collaboration with equipment OEMs during planning of major equipment overhauls, improved execution strategies and execution efficiencies, Bonga FPSO have been able to achieve significant improvement in plant availability of &gt;95%, reliability &gt;96%, and significant reduction in greenhouse gases (GHG) emissions through reduction of flares and fuel emissions, which has overall contributed to the 1 billion barrels export milestone achieved.
This paper presents the benefit of digitalization, robust Asset Management processes and competence development as key enablers to improved plant and equipment Reliability, Availability & Utilization in any production facility.
Enhancing Value Generation from Reservoir Brine via an AI-Driven Lithium Recovery Optimization Methodology - A Volve Field Reservoir Benchmark Analysis
Authors: Katterbauer Klemens , Patil Pramod , Al Shehri Abdallah , Yousef Ali 
Published: April 2024

Abstract
In the pursuit of more sustainable resource use, lithium has emerged as a useful resource for a range of uses, including batteries. Due to these difficulties, there is a growing need for improved field operations that preserve output levels while also making the operations more sustainable. The Fourth Industrial Revolution are greatly impacting the oil and gas sector, and as the need for lithium to be used for batteries and energy technologies grows, hydrocarbon reserves are becoming a more desirable source of these precious minerals. Lithium has been found in considerable amounts in the generated brines of a number of reservoirs worldwide. In this study, we provide a novel artificial intelligence (AI) optimization strategy for optimizing lithium recovery from reservoir operations while preserving reservoir oil production goals. A deep learning LSTM algorithm is integrated into the AI framework to estimate water injection amounts based on oil, brine, and lithium recovery. After that, a global optimization framework using the deep learning model is integrated to optimize the water injection levels in order to maximize lithium recovery while preserving reservoir oil production levels. For the purpose of recovering lithium from reservoir brine in an oil and gas reservoir, we have presented a novel AI optimization framework. The framework allows hydrocarbon recovery rates to be maintained while optimizing lithium recovery. The framework, which highlights the potential for a large improvement in lithium recovery rates from an enhanced injection procedure, was successfully demonstrated on the Volve field. This paradigm has the potential to yield substantial benefits for optimizing the use of reservoir brine, which might lead to improved sustainability in reservoir operations.
Going Deeper: Inspecting Subsea Live Assets by Means of an Advanced AUV Solution
Authors: Nevoso C. , Cavallini F. , Massari G. , Bernini T. , Watanabe T. , Britto A. 
Published: April 2024

Abstract
Data has always been the key: more data, at higher frequency, with better quality and, possibly, always cheaper. Data, if properly handled, means knowledge and knowledge allows better performance and with less risk. In this context, offshore IMR is not different compared to other business segments, with the addition that, in 2023, it appears to be somehow obsolete the need to mobilize a diesel propelled vessel with circa 60 people onboard with the purpose of taking some pictures and videos of subsea facilities. In order to respond to this challenge, several players in the market have launched their development programs, with the objective of developing and qualifying a new generation of subsea vehicles, or better drones, capable to match the industry needs in terms of cost efficiency and environmental footprint as well.
Focusing on pipeline inspections, AUVs are the preferred choice for long range activities while optimizing the need for support vessels in constant control of the subsea operations. However, the complexity of the subsea domain resides in the non-linear objects such as subsea XTs, manifolds, etc., i.e. all those subsea assets requiring detailed inspections at frequent interval mainly to assess the status of valves, cathodic protection, flanges and connections in general. Doing this with a standard AUV is fairly impossible, therefore a new generation of advanced AUV solutions is required, capable of DP and hovering modes, thus adding the flexibility to stop-by at given location and perform a detailed assessment of the target point, including search and localization of possible hydrocarbon leaks. This functionality implies a rethinking of the subsea vehicle which -as anticipated- is then commonly redefined by the offshore industry as "subsea drone".
After extensive qualification programs such subsea drones are currently being introduced by different suppliers and service providers to the market, promising substantial achievements in terms of inspection effectiveness. The focus of this paper shall then be in sharing the direct experience made by Saipem while bringing FlatFish to deepwater, in what it is believed to be a unique subsea campaign setting a number of industry firsts: autonomous deepwater inspections of flowlines, XTs, structures and risers.
Such deepwater operations, carried out offshore Brazil at the beginning of 2023, have been an essential achievement in the subsea drone development and qualification plan, unlocking the next stage of FlatFish continuous development while marking a milestone for the offshore energy industry. Saipem intends to share, from its privileged viewpoint, the main outcomes and lessons learnt from such deepwater pilot operations.