bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of API 11D1 and API 19AC Validation Grade V0 Barrier-Qualified Gravel Pack System for Troll Phase 3 Big-Bore, High-Rate Gas Completions on the Norwegian Continental Shelf
Authors: Hammer Aaron C , Gonzalez Tom D , Dhuet Herb P , Andresen Hege , Sunde Siv Merete M , Jabrayilov Elshan , Kam Iris Sok Yee , Tviet Torstein 
Published: September 2021

Abstract
The Troll Phase 3 (TP3) wells were designed to enable high gas rates and sand free production for an expected lifetime of 40 years with a minimum pressure drop. By taking reservoir and production properties into account, open-hole gravel pack (GP) sand screens in the lower completion and big bore tubing in the upper completion were selected. To further reduce the pressure loss in the well, reduce rig time and cost, and reduce deployment risks, eliminating the intermediate completion was proposed. Traditionally, an intermediate completion is required to serve as a gas-tight barrier for running of the upper completion, mainly due to historical limitations of the GP extension (GP sleeve) not being a barrier qualified to API 19AC Validation grade V0 (referred to as V0 hereafter) after pumping sand slurry through it (post-erosion). An extensive qualification program was completed to qualify the GP system to API 11D1 and API 19AC V0 for use as a gas-tight barrier post-erosion. This allows the GP system to serve as a primary barrier while installing the upper completion and temporarily abandoning the well. The GP packer was qualified to API 11D1 V0 with the additional requirement to perform entire qualification in as-rolled casing and including a plug-in-tailpipe load case. The GP sleeve provided the most technically challenging requirements: a full-scale erosion test, immediate closure of the sleeve after pumping operation, followed by API 19AC Annex A V0 validation. Challenges were encountered trying to meet the rigorous V0 (zero bubble) acceptance criteria post-erosion. A significantly different approach was developed to achieve gas-tight performance in debris-laden environments. The new design successfully passed the post-erosion API 19AC V0 qualification to the full rating of the GP sleeve. The GP system development and qualification enabled the industry-first V0 post-erosion GP system for Equinor, which eliminates the need for an intermediate completion. This state-of-the-art gravel pack system enabled the simplified high gas rate, big-bore well design, not previously possible given well barrier considerations. The reduced pressure drop across the lower completion is expected to yield a higher gas production rate for the 40 years expected well life, contributing significant value to the TP3 project.
EM-Based 2D Corrosion Azimuthal Imaging using Physics Informed Machine Learning PIML
Authors: Ooi Guang An , Özakin Mehmet Burak , Mostafa Tarek Mahmoud , Bagci Hakan , Ahmed Shehab , Larbi Zeghlache Mohamed 
Published: September 2021

Abstract
In the wake of today's industrial revolution, many advanced technologies and techniques have been developed to address the complex challenges in well integrity evaluation. One of the most prominent innovations is the integration of physics-based data science for robust downhole measurements. This paper introduces a promising breakthrough in electromagnetism-based corrosion imaging using physics informed machine learning (PIML), tested and validated on the cross-sections of real metal casings/tubing with defects of various sizes, locations, and spacing.
Unlike existing electromagnetism-based inspection tools, where only circumferential average metal thickness is measured, this research investigates the artificial intelligence (AI)-assisted interpretation of a unique arrangement of electromagnetic (EM) sensors. This facilitates the development of a novel solution for through-tubing corrosion imaging that enhances defect detection with pixel-level accuracy. The developed framework incorporates a finite-difference time-domain (FDTD)-based EM forward solver and an artificial neural network (ANN), namely the long short-term memory recurrent neural network (LSTM-RNN). The ANN is trained using the results generated from the FDTD solver, which simulates sensor readings for different scenarios of defects.
The integration of the array EM-sensor responses and an ANN enabled generalizable and accurate measurements of metal loss percentage across various experimental defects. It also enabled the precise predictions of the defects’ aperture sizes, numbers, and locations in 360-degree coverage. Results were plotted in customized 2D heat-maps for any desired cross-section of the test casings. Further analysis of different techniques demonstrated that the LSTM-RNN could show higher precision and robustness compared to regular dense NNs, especially in the case of multiple defects. The LSTM-RNN is validated using additional data from simulated and experimental data. The results show reliable predictions even with limited training data. The model accurately predicted defects of larger and smaller sizes that were intentionally excluded from the training data to demonstrate generalizability. This highlights a major advance toward corrosion imaging behind tubing.
This novel technique paves the way for the use of similar concepts on other sensors in multiple barriers imaging. Further work includes improvement to the sensor package and ANNs by adding a third dimension to the imaging capabilities to produce 3D images of defects on casings.
A Real-Time Fiber Optical System for Wellbore Monitoring: A Johan Sverdrup Case Study
Authors: Schuberth Maximilian Georg , Bakka Håkon Sunde , Birnie Claire Emma , Dümmong Stefan , Haavik Kjetil Eik , Li Qin , Synnevåg Johan-Fredrik , Saadallah Yanis , Vinje Lars , Constable Kevin 
Published: September 2021

Abstract
Fiber Optic (FO) sensing capabilities for downhole monitoring include, among other techniques, Distributed Temperature Sensing (DTS) and Distributed Acoustic Sensing (DAS). The appeal of DTS and DAS data is based on its high temporal and spatial sampling, allowing for very fine localization of processes in a wellbore. Furthermore, the broad frequency spectrum that especially DAS data is acquired with, enables observations, ranging from more continuous effects like oil flow, to more distinct effects like opening and closing of valves.
Due to the high data volume of hundreds of Gb per well per hour, DAS data has traditionally been acquired acquisition-based, where data is recorded for a limited amount of time and processed at a later point in time. This limits the decision-making capability based on this data as reacting to events is only possible long after the event occurred. Equinor has addressed these decision-making shortcomings by building a real-time streaming solution for transferring, processing, and interpretation of its FO data at the Johan Sverdrup field in the North Sea.
The streaming solution for FO data consists of offshore interrogators streaming raw DAS and DTS data via a dedicated bandwidth to an onshore processing cluster. There, DAS data is transformed into FO feature data, e.g., Frequency Band Energies, which are heavily decimated versions of the raw data; allowing insight extraction, while significantly reducing data volumes. DTS and DAS FO feature data are then streamed to a custom-made, cloud-based visualization and integration platform. This cloud-based platform allows efficient inspection of large data sets, control and evaluation of applications based on these data, and sharing of FO data within the Johan Sverdrup asset.
During the last year, this FO data streaming pipeline has processed several tens of PB of FO data, monitoring a range of well operations and processes. Qualitatively, the benefits and potential of the real-time data acquisitions have been illustrated by providing a greater understanding of current well conditions and processes. Alongside the FO data pipeline, multiple prototype applications have been developed for automated monitoring of Gas Lift Valves, Safety Valve operations, Gas Lift rate estimation, and monitoring production start-up, all providing insights in real-time. For certain use cases, such as monitoring production start-up, the FO data provides a previously non-existent monitoring solution.
In this paper, we will discuss in detail the FO data pipeline architecture from-platform-to-cloud, illustrate several data examples, and discuss the way-forward for "real-time" FO data analytics.
Annular Phase Separation with AICD Completions – The Impact on Well Flow Performance and Control of Unwanted Effluents
Authors: Konopczynski Michael R , Moradi Mojtaba 
Published: September 2021

Abstract
The design and method of operation of Autonomous Inflow Control Devices are reviewed, including single-phase and multi-phase flow performance. Next, the multi-phase flow of fluids in the annular space between circular conduits is examined based on published information and flow pattern maps. This information is brought together in a thought experiment describing how AICDs and well performance will react to the segregation of fluids upstream of the flow control device, and the potential impact that the degree of restrictiveness on unwanted effluents can affect the flow performance of the reservoir and well. Finally, the impact on well flow performance is quantified by computer modelling of the reservoir inflow performance, annular flow performance, and AICD performance. The sensitivity of well productivity is assessed for multiple flow scenarios adjusting several model parameters, including type and number of AICDs per zone, GOR, water cut, flow rate, and well completion size.
Although the concept of an AICD that completely shuts off gas and/or water production sounds appealing to those wishing to eliminate the production of unwanted effluents, a full understanding of the dynamics of inflow from the reservoir and phase segregation in the wellbore is necessary to evaluate the impact of highly restrictive AICDs on well productivity. With annular separation, even small water cuts or limited amounts of free gas flowing into the wellbore can cause most of the highly restrictive AICDs in a multiple device zone to shut, greatly impacting the oil productivity of the zone and the well. Using AICDs that are not as restrictive of the unwanted effluents allows the operator to continue to produce oil at significant rates when associated with low water cuts or reduced free-gas GORs. A workflow for determining the optimum degree of restrictiveness is proposed and demonstrated.
Robotics, Digital Twins and AI: Connecting the Dot Matrix
Authors: Kydd Kris , Brennan Dervla , Kirkpatrick Neil , Wright Matthew 
Published: September 2021

Abstract
Robotics is often referred to as an enabler towards safer and more cost-effective operations within the energy industry. However, for robots to achieve their full potential they too require their own enablers. This paper intends to present a collection of lessons learnt in robotic development to date that has resulted in the necessity to develop an encompassing digital architecture.
This architecture, with an artificial intelligence component, has been designed to optimise both robot and digital twin capability, where the complete system is always working with the latest information available that reflects the ground truth. The architecture concept will be explained including why integration and standardisation are of paramount importance.
The paper will also demonstrate how business value can be generated before fully explainable, transparent, verifiable autonomy is available for robotics to be deployed on future unmanned platforms that have been designed to optimise robot operation opposed to existing human engineered environments. All these topics are important within their own right, but all are also years away from adoption on an industrial scale.
To ensure continued engagement until such a point is reached, the industry needs to focus more on the quick wins and immediate value that can be gained from robotics. The impact of COVID-19 has shown how quickly and effectively the energy industry has been able to transition to remote working. This represents a massive opportunity to prove what robotics can deliver via remote operation, minimizing vendors where possible.
The concept of "full" autonomy will be discussed with respect to value generation and barrier to entry or adoption within the energy industry. The paper will address all practical considerations that have required attention to date plus explain the next programme of work in the evolving RAS (robotics and autonomous systems) digital architecture whilst ensuring complete integration with the data pipelines that have already been built.
Implementation of a Digital Roadmap with Best-in-Class Applications
Authors: McIntosh John , Martin Renata , Alcala Pedro , Skjævesland Stian , Rigg John 
Published: September 2021

Abstract
The paper describes a project known internally as "InWell" to address multiple requirements in Repsol Drilling & Completions.
InWell is defined by a new Operating Model comprising Governance, People, Process, Functions and Technology. This paper addresses changes to the Technology element - often referred to as "Digitalization".
The paper includes a discussion about the business transformation strategy and case studies for addressing three of 18 functionalities identified in the first round of development.
The InWell development strategy followed four steps; identification of performance issues, envisioning of a future operating model, identification of functionalities required/supporting this operating model and matching to digital solutions.
Our case studies focus on three functionalities provided by three separate companies, Unification of Planning and Compliance, Real Time Data aggregation and Key Performance Indicators. Each functionality was addressed with an existing commercial application customized to meet specific requirements.
A corporate web-based Well Construction Process (WCP) was initially piloted and then extended to include all well projects. The WCP identifies the key Tasks that must be completed per project, and these are all tracked. Data from this application is used by a third-party Business Analytics application via an API.
Real time data from many sites and a wide range of sources was aggregated and standardized, Quality Controlled and stored within a private secure cloud. The data collation service is an essential building block for current third-party applications such as the operating centre and is a prerequisite for the goal of increased automation.
A suite of Operator specific Key Performance Indicators (KPIs) and data analytics services were developed for drilling and completions. Homogenized KPIs for all business units provide data for objective performance management and apples-to-apples comparison. Results are presented via custom dashboards, reports, and integrations with third party applications to meet a wide range of requirements.
During a four-month Pilot Phase the InWell Project delivered € 2.5 million in tangible savings through improvements in operational performance. In the first 12 months € 16 million in savings were attributed to InWell. By 2022 forecast savings are expected to exceed € 60 million (Figures 1 & 2). The value of Intangible benefits is thought to exceed these objective savings.
Figure 1 The Business Case for InWell – Actual & Projected Savings and Costs. Figure 2 InWell Services addressing Value Levers and quantified potential impact.
A multi-sourced digital strategy can produce quick gains, is easily adapted, and provides high value at low risk. The full benefit of digital transformation can only be realised when supported by an effective business operating model.
Disposable Fibre Optic Intervention System: Case Study of Successful Leak Detection Offshore North Sea
Authors: Feherty Craig , Garioch Andrew , Green Annabel 
Published: September 2021

Abstract
Maintaining well integrity is critical to sustaining production from mature and aging fields. Disposable fibre optic technology has been deployed in wells in the North Sea to locate known tubing leaks in the completion.
The disposable fibre optic intervention system releases a probe into the well to enable the deployment of bare fibre optic line. The fibres are released from the probe as it descends into the well. In the presented case study, the probe contained both single-mode and multi-mode fibre optic lines to enable simultaneous Distributed Temperature Sensing (DTS) and Distributed Acoustic Sensing (DAS) surveys to be performed. Once deployed in the well, pressure manipulation programs were performed to activate any tubing or casing leaks while acquiring DTS and DAS data.
As a result of the exceptional sensitivity of the bare fibres and the effective coupling of the fibre with the tubing wall the technology is shown to be highly effective in detecting leaks and confirming barrier integrity. In the presented example a leak was located along with the direction and rate of the fluid movement in the ‘B’ annulus. The simplicity of the system and highly efficient operations greatly reduced survey times in comparison to conventional intervention techniques thereby greatly reducing the cost of intervention. It can be demonstrated that the disposable fibre optic deployment system provides a game changing and cost-effective solution for both leak detection and determining liquid levels in the wells.
The disposable fibre solution is a unique deployment method which provides an alternative to conventional well surveys, reducing the complexity, time and cost to acquire valuable distributed well data. This is the first case history published for this technology in leak detection application.
Building a Low-Manned Production Installation: Considerations for Rotating Equipment, Electrical & Automation Systems, and Digitalization
Authors: LaGrange Elgonda 
Published: September 2021

Abstract
Nearly all oil and gas operators and engineering companies in the offshore sector today are engaged in programs to advance concepts for low-manned and/or normally unattended production installations (NUIs). When it comes to the design of these facilities, topsides rotating equipment and electrical, instrumentation, control, and telecommunications (EICT) packages represent key areas of interest for decision-makers, owing to the significant impact they can have on required manning levels. Over the past decade, the author's company has worked closely with major Operators in the U.S. and the North Sea to look at how existing technologies can be applied in these areas to safely facilitate de-manning of both brownfields and greenfields. This paper provides insight into these efforts. It also presents projected manpower and cost savings from de-manning, using data derived from both studies and real-world projects.
In-Situ Sensing of Underwater Gas Releases
Authors: Laddha Chetan , Ortiz-Soto Lorna , Baksmaty Leslie , Dominguez-Olivo Juan 
Published: September 2021

Abstract
The O&G industry has been producing hydrocarbons from subsea reservoirs for several decades. However, there is a technological gap in the ability to reliably detect and quantify dissolved gases within the water column. This technological gap has in turn led to a scientific gap in our ability to determine the subsurface origin of subsea fluid emissions. Gas releases are commonly found in the marine environment primarily because of naturally occurring seeps and occasionally due to Oil and Gas production activities. There is a need to be able to identify the gas composition and accurately characterize its source (i.e., ongoing microbial activity or thermogenic derived hydrocarbons). However, building a reliable solution which allows this differentiation between thermal and microbial sources in the underwater environment as well as the inference of their subsurface origin requires a multi-disciplinary subsurface workflow coupled comprehensive high-fidelity measurements at the seabed. As one of the front-end building blocks of any robust multi-disciplinary workflow, there is a need for development of an in-situ sensing and sampling capability which allows real-time assessment and geological characterization of the underwater emissions across the upstream industry, from exploration to abandonment. Such a capability would also be complementary to the geohazard and subsurface assessment practices e.g., by reducing lost rig time during interventions by allowing quick characterization of emissions that arise from natural seeps or LOPC (Loss of Primary Containment) events.
This paper describes the maturation of a compact underwater in-situ sensing technology deployed from autonomous or tethered underwater vehicles and which enables measurements of gas constituents and their respective isotopes at the seabed.
A Road Map for Renewable Energy Integration with Subsea Processing Systems
Authors: Pimentel Juliano , Slater Robin , Grant Andrew , Vesterkjær Rune , Normann Truls , Kothari Rajeev , Sandberg Johan 
Published: September 2021

Abstract
This paper proposes a road map for the integration of renewable energy supply to power subsea processing systems. To replace the traditional power supply, like fossil fuel-based generators or grid power, a wind turbine generator (WTG) operating on a islanded mode has been introduced and discussed. A review of the state of the art of WTGs is performed, primarily focused on power and controls aspects, with identification of the main technological gaps left to achieve wind-powered subsea processing. To fully assess the renewable energy integration and current gaps, a study case is proposed which addresses a subsea compression train powered by offshore wind. A thorough analysis is conducted, with meteorological conditions based on the NCS (Norwegian Continental Shelf), where gas line packing is proposed as an innovative means of energy storage. Finally, an economic analysis as well as a CO2 emission estimate is presented to demonstrate the benefits of the proposed road map. Some further discussions and conclusions are presented as well as some propositions for future works.
The Commercial Case for Hydrogen as a Route to Market for Offshore Wind in the North Sea
Authors: lliffe Molly 
Published: September 2021

Abstract
The UK was the first major industrialised nation to commit to a Net Zero target by 2050, and Scotland has an even more ambitious target to reach Net Zero by 2045. To realise these targets, hydrogen will play a leading role in the decarbonisation of multiple sectors including industry, transport, heat and power.
Offshore wind can be a core component of our future energy infrastructure, and the scale of its potential role in hydrogen production has recently drawn wider attention from policy makers, developers and potential users across a range of sectors.
Hydrogen as a route to market for offshore wind therefore presents a transformative opportunity for the North Sea oil and gas sector and the associated UK supply chain. Existing skills and infrastructure in this region can be leveraged to achieve a leading position in this emerging clean fuel source.
This opportunity is particularly relevant for sites in the North Sea which are further from shore with good wind resource, where power transmission costs and/or losses would be prohibitive. Additionally, hydrogen offers an interesting route to market for projects unable to obtain firm grid connection, for sites in regions with high grid charges, or where sufficient government revenue support for conventional power generation is not available for all good quality sites.