bluuebunny/crossref_metadata_2025 huggingface dataset:
Offshore LNG and Gas Monetization
Authors: Alabi Femi Adeoye
Published: April 2020

An anticipated acceleration in LNG's commoditization, driven by factors such as increased natural gas demand and newfound confidence in its potential as a marine fuel and as the cleanest of the fossil fuels, having lower emissions than either coal or oil fired power generation is expected to hand it a much larger role in global energy markets. The deployment floating liquefied natural gas (FLNG) facilities, becomes increasingly important as an option to achieve this task rather than an onshore facility. Jettyless LNG transfer concept could cut total project cost by 50%.

Recent policies in Europe have encouraged the use of renewables, with gas being the obvious complementary source of energy for power generation when these intermittent sources need backup power. A supply chain is the network of LNG from the upstream to the downstream called a distribution channel have three main flows which are the product, information and the finances flow. FLNG is an emerging technology for such fast and cost effective development of technology to unlock smaller, remote or environmentally sensitive fields. LNG Monetization will be thoroughly examined. FLNG however present some novel challenges less on the technical side and more to do with the supply chain, project management, stakeholder engagement, financing, regulation and tax. Understanding regulatory, legal, financing tax issues and engaging with the relevant stakeholders well ahead of investment decisions are keys. Flexibility is also being introduced in LNG Import Terminals, which have the potential to serve as a LNG Hub where LNG is received in bulk volumes from an LNG carrier and is then distributed out through gas pipeline. This solution is applicable when the visiting LNG carrier is connected to the onshore storage without a jetty. This solution enables small-scale LNG transfers to the LNG storage on shore or to the landlocked Floating Storage and Regasification Units. The international natural gas sector was geographically divided into distinct regional markets. The US and Europe supplied mainly by pipelines and Asia supplied by LNG. For all regions, there is a striking difference between the geopolitical context of international pipeline gas business and LNG which will be detailed in this work. The FSRU is lower in cost and can be reused while the land based terminals cannot be relocated. Geopolitics is a central concern for the oil and gas sector and can be viewed as a source of both risk and opportunity as identified by EY. Collaboration in adding values to the LNG business measured by total revenue will be examined in the work.
Optimizing Floating Offshore Multi-Wind-Turbine Design: A Parametric Study on Tower Inclination and Column Spacing
Authors: Udoh Ikpoto Enefiok , Zou Jun
Published: April 2020

Multi-turbine floating offshore platforms (MUFOPs) are emerging as a viable concept for reducing levelized cost of energy in offshore wind developments. If properly designed, the cost per megawatt of electric power generated can be lower compared to single-turbine platforms. To maximize yield, minimize cost and ensure a safe design, the spacing between rotor-nacelle assemblies (RNAs), must be carefully considered. This spacing (R), is the sum of the platform column spacing (c), and tower horizontal projected length (h). Rotor diameters pose considerable challenges to the arrangement of multiple wind turbines on one platform; challenges pertaining to safe operations, feasibility of construction and transportation. Specific insights are necessary to facilitate the development of viable concepts. The parametric study presented in this paper discusses the optimization of MUFOPs using tower inclination and column spacing.

Representative configurations (adjusting tower inclination and / or column spacing) are developed with a multi-turbine semi-submersible-type platform and analyzed in time domain using coupled analysis. The configurations consist of two 5 WM reference turbines of the National Renewable Energy Laboratory (NREL), U.S.A. A non-dimensional parameter (R/c), is used to characterize the configurations. Wind, wave, and current loads are applied in analysis to assess the behavior of the system holistically. Hydrodynamic, aerodynamic, elasto-dynamic, servo-dynamic and mooring-dynamic effects are captured interactively at each time-step of analysis. An operational turbine condition is simulated in analysis using full-field turbulent wind to capture spatial variations of wind loads acting on each turbine of the system.

Characteristic responses of the nacelle, tower and platform are assessed to determine the optimal combination which avoids both inadequate and excessively conservative designs of multi-wind-turbine platforms. By analyzing the spectral densities of the responses, the potential impact of the observed responses on fatigue design is qualified. Optimal configurations from the scenarios considered, allow minimal or no wake interactions, tolerable towerbase loads and acceptable accelerations and motions of the nacelle and platform. Results indicate that optimal solutions exist at R/c ratios greater than 1.0.

An assessment of a range of tower inclinations and column spacing for optimal design of multi-wind-turbine platforms is a study that has not been documented in literature, and deserves attention considering current industry trends for floating offshore wind turbines. This paper offers significant insights on the characteristics of optimal tower and column arrangements for such platforms and provides reliable benchmarks for future designs.
Wave Data Assimilation in Support of Wave Energy Converter Power Prediction: Yakutat, Alaska Case Study
Authors: Dallman Ann , Khalil Mohammad , Raghukumar Kaus , Jones Craig , Kasper Jeremy , Flanary Christopher , Chang Grace , Roberts Jesse
Published: April 2020

Integration of renewable power sources into grids remains an active research and development area, particularly for less developed renewable energy technologies such as wave energy converters (WECs). WECs are projected to have strong early market penetration for remote communities, which serve as natural microgrids. Hence, accurate wave predictions to manage the interactions of a WEC array with microgrids is especially important. Recently developed, low-cost wave measurement buoys allow for operational assimilation of wave data at remote locations where real-time data have previously been unavailable.

This work includes the development and assessment of a wave modeling framework with real-time data assimilation capabilities for WEC power prediction. The availability of real-time wave spectral components from low-cost wave measurement buoys allows for operational data assimilation with the Ensemble Kalman filter technique, whereby measured wave conditions within the numerical wave forecast model domain are assimilated onto the combined set of internal and boundary grid points while taking into account model and observation error covariances. The updated model state and boundary conditions allow for more accurate wave characteristic predictions at the locations of interest.

Initial deployment data indicated that measured wave data from one buoy that were assimilated into the wave modeling framework resulted in improved forecast skill for a case where a traditional numerical forecast model (e.g., Simulating WAves Nearshore; SWAN) did not well represent the measured conditions. On average, the wave power forecast error was reduced from 73% to 43% using the data assimilation modeling with real-time wave observations.
Using Composite as a Long-Term Repair on Pressure Boundary Components in the Offshore Industry
Authors: Filho David Fernandes Gonçalves , Araujo Sandro Santos Pires
Published: April 2020

This work aims to demonstrate the advances in the use of composite material as a long-term repair element in high-pressure hydrocarbon pipeworks and essential system fluids in offshore units. The approach is based on the pressure exerted by classificatory bodies against the indiscriminate use of this incipient technology, reason why the risk of accidents has substantially increased in Offshore units, many of them caused by fire. Since safety is a key factor for the Oil and Gas industry, MODEC has invested in development and certification of this technology, guaranteeing that composite repair installers suit this new reality.
Brazil Pre-Salt, Santos Basin: Feasibility Study for the Application of Borehole Gravity to Improve Reservoir Monitoring
Authors: Du Zhijun , Topham Adrian , Lofts Jeremy Jez C. , Seshia Ashwin A.
Published: April 2020

Brazilian Pre-Salt reservoir characterization and monitoring is a challenge for surface geophysical methods due to the inherently minute observable signals from the reservoirs, located below the massive salt, in depth ranges > 5000 m.

The status of a program to develop a wireline deployed 3-axis gravity sensor with a target sensitivity of ~ 5 μGal is firstly introduced. This is followed by a feasibility study for the potential deployment as a time-lapse gravity survey (4D gravity monitoring) within the pre-salt. A conceptual pre-salt reservoir model for the Libra field, Santos Basin, the offshore of Brazil, is developed, built on available pre-salt knowledge provided from seismic imaging and well log data, including reservoir and production characteristics. The model is based on water substituting oil over 6 months within and through the reservoir, with adoption of an oil production rate for the field published in 2017 by the ANP. These data are used to forward model gravity to understand the potential for a detectable signal and thereby establish a baseline for a time-lapse gravity survey (4D gravity) that could be used to monitor the Libra Field.

A clear gravity response >80 μGal is observed over a six month period in the reservoir, due to water replacing oil, at the defined oil production rate. In a three-axis measurement the vertical axis is directly related to the magnitude of the fluid substitution and the two horizontal axes are sensitive to the fluid movement directions. Together, these suggest that an annual survey with a limited well stock could be effective in monitoring this type of reservoir and that a wireline deployed 3-axis gravity tool is likely to provide significant additional surveillance to constrain a reservoir production strategy through better appreciation of the direction of water movement. The follow-on step would be to model further field data and run a baseline survey to develop a novel reservoir surveillance method within the Pre-Salt.
High Pressure Testing of a Pilot Subsea Compact Flotation Unit
Authors: Zhao He , Berg Jens Kristian , Stinessen Kjell Olav , Solumsmoen Gyri Brigitte , Kolbu Jostein , Johnsen Kristin Høines , Knudsen Børre Leif , Gudbrandsen Karen Anne , Rondon Marianna , Berthelot Aurelie , Pedenaud Pierre
Published: April 2020

Produced water is the largest volume waste stream in oil and gas production and is a particular problem for late-life operation of oil fields. The huge waste volumes result in two obvious consequences and cost drivers; fast declining reservoir pressure and tremendous power used to handle it. Produced water reinjection has been used as a main strategy for both managing produced water volumes and supporting reservoir pressure. Treating produced water subsea as close as possible to the production wells has several advantages such as smaller topside footprint, minimizing the energy demand and associated emissions, reducing the well back pressure and increasing production rates. While some work has been done in the past on subsea use of deoiling hydrocyclones, robust high performance subsea produced water treatment equipment and processes have not yet been made available. The Compact Flotation Unit (CFU) is a well proven technology for topside use and has been considered promising for subsea use, but never before been tested at subsea relevant pressures. Aker Solutions with partners Aker BP, Equinor and Total and support from Research Council of Norway have successfully run a joint industry project to qualify this technology for subsea application.

Pilot testing of a subsea CFU was carried out in Equinor's large scale test facilities in Porsgrunn, using crude oil, natural gas and synthetic produced water. The pilot CFU was tested with pressures significantly above that used for conventional topside CFUs, and at various temperatures. Gas bubbles were injected by use of ejectors designed to provide the desired bubble size. Oil droplet size, flow rate and oil in water concentration were the major control variables in addition to pressure and temperature. The effect of injection of flocculant was also investigated. The main topic of interest was the oil removal efficiency of the CFU under high pressure.

The analyses of the results showed that the CFU's efficiency improved with increase of the operational pressure. This was likely to be related to the changes of physical properties of gas, oil and water as pressure increases, and the changing balance between physical phenomena in the process. The CFU also demonstrated robust performance with a large turndown ratio.

Test of flocculant at high pressure showed instant and substantial improvement in the CFU efficiency, and the effect of flocculant was not compromised by the high pressure.

The promising results suggest that CFU performs well at elevated pressure and is a viable solution for subsea produced water treatment.
Flexible Riser Fatigue Counter Powered by Digital Techniques
Authors: Engebretsen Rasmus , Nilsen-Aas Christoffer , Muren Jan , Hondebrink Luke Johan , Kajolli Besmir
Published: April 2020

This paper describes developments in the fatigue counter methodology and how digitalization is used to deliver valuable online technical service.

The fatigue counter methodology consists of using a combination of autonomous and online motion response sensors directly installed on the riser and interfacing Floating Production Storage and Offloading vessel (FPSO) structures. The measured environmental data, FPSO and riser response data are utilized in a machine learning (ML) environment to build more realistic riser response and fatigue prediction models. The results of this is significant reduction in uncertainties, enabling live riser fatigue predictions and providing a basis for life extension and improved accuracy of riser and vessel response analysis. As there is a need to run some risers at higher pressures, the optimum time periods for such high-pressure service can be found without compromising the flexible riser service life.

A recent field case is presented whereby the fatigue counter ingest, process and present data on a modern digital infrastructure. The full service was setup based on available onboard sensors including a 6 degree of freedom (DOF) vessel motion response unit (MRU), temperature and pressure transmitters and forecast model for weather. Input and output data are shared through well documented and safe application program interfaces (APIs) between the operating company and the fatigue counter 3rd party service. The operating company receives live updates of accumulated fatigue damage and remaining service life. This enables the operating company to build contextualized and high value dashboards presented on their organizational front end.

The paper illustrates the power and applicability of combining modern numerical methods with digital techniques, made possible by streaming input and output data on safe and well documented APIs.
Amorphous and Nanocrystalline Dissolvable Alloys with Artificial Intelligence for Applications in Deep-Water and Unconventionals
Authors: Chen Ting , Shenoy Ram , Wilkinson Christian , Roy Indranil
Published: April 2020

Technology developed to harness extended reach deviated (ERD) wells for deep-water and longer laterals for unconventionals demand the use of reliable "Dissolvable Alloys". Furthermore, an economic prediction mechanism to assess the degree of dissolution of deployed dissolvable hardware is highly coveted. This is one of the bottlenecks preventing the increased adoption of dissolvables in both deep-water and multistage stimulation (MSS). DAMORPHE was founded to take advantage of recent Mechanical-Materials-Electrical (MME) innovations for development and commercialization of "Game-Changing" technologies through the selective use of amorphous and nanocrystalline dissolvable alloys with Artificial Intelligence (AI). Here we discuss a couple of applications where dissolvable materials bring enhanced functionality over traditional methods and present a case for how replacing these with intelligent materials can bring further benefits to the end users.
Lost Circulation Prediction in South China Sea using Machine Learning and Big Data Technology
Authors: Hou Xinxin , Yang Jin , Yin Qishuai , Liu Hexing , Chen Haodong , Zheng Jinlong , Wang Junxiang , Cao Bohan , Zhao Xin , Hao Mingxuan , Liu Xun
Published: April 2020

Lost circulation is one of the frequent challenges encountered in the well drilling and completion process, which can not only increase well construction time and operational cost but also pose great risk to the formation. However, choosing the most useful treatments may still be a problem due to the complexity of the drilling and geological condition.

In this paper, machine-learning algorithms and big data technology are employed to mine and analyze drilling data of wells in South China Sea where lost circulation is severe. Geological characteristics, drilling fluids property parameters and operational drilling parameters are both considered. Moreover, an artificial neural network is employed to conduct supervised learning. The four metrics: accuracy, precision, f1 score and recall are used to evaluate the model. The trained artificial neural network model is employed to predict the lost circulation risks.

To train and test the proposed model, drilling operation parameters, geological parameters and drilling property parameters are collected for lost circulation events for 50 drilled wells over past two years in South China Sea. The trained model is excellent with the most important evaluation metrics, attaining an accuracy up to 92%, with f1 score, recall and precision up to 89% similarly. This suggests that the model have a good generalization ability and can be applied to other fields. Data analysis through an artificial neural network is carried out to develop a lost circulation prediction system model. This methodology can predict six lost circulation risks, each is defined according to drilling mud loss rate.

This is one of the first attempts to predict lost circulation using data-analytics and artificial intelligence. The proposed intelligent lost circulation prediction method can assist the drilling engineer to choose the optimal drilling parameters prior to drilling and avoid lost circulation events.
Quantum Dots: Low-Dosage Hydrate Inhibitors for Deep Water Flow Assurance
Authors: Deka Barasha , Sharma Rohit , Mahto Vikas , Polara Subhash
Published: April 2020

Flow assurance problem of gas hydrate formation in subsea transportation system of crude oil is addressed in this research work. The paper depicts the synthesis and evaluation of propylene glycol quantum dots as low-dosage hydrate inhibitor (LDHI) for preventing / delaying gas hydrate formation during transportation of crude oils in subsea pipelines. The thermodynamic hydrate inhibitor, propylene glycol, has been developed as anti-agglomerant, which is a type of low-dosage hydrate inhibitor, by converting it into its quantum dots. The developed quantum dots (QDs), which are a few nanometer sized particles are a new addition to oilfield chemicals. They are highly effective in increasing induction time of gas hydrate formation and hydrate agglomeration time for multiphase flow of crude oil with water cut up to 90%. Hydrate formation induction and agglomeration time study are performed on a fabricated setup based on visual method of hydrate study on crude oil –water system including tetrahydrofuran, forming a model hydrate system. The developed quantum dots are characterized to obtain their optical and other properties. The research work showed the effectiveness of propylene glycol QDs as LDHI, which may be applicable in deep water production systems to avoid flow assurance problem in transportation pipelines.
Modeling Current-Energy-Converter Devices in the Tanana River, Alaska
Authors: James Scott C. , Olson Sterling S. , McWilliams Sam , Jones Craig A. , Roberts Jesse D.
Published: April 2020

The effect a marine hydrokinetic device, or array of devices, has on the environment is a key component of design, permitting, and viability of a project. To accurately understand physical processes and their potential relationship to environmental stressors at a current-energy converter (CEC) site, a numerical model was developed using SNL-Delft3D-CEC-FM to facilitate an understanding of the potential changes to the system .

Conceptual flowchart of the modeling methodology.

Using turbine and river data provided by the Alaska Hydrokinetic Energy Research Center, a steady-state flow model was constructed for varying river discharge levels. The wakes of University of Alaska at Fairbanks New Energy Systems vertical-axis, 5-kW turbine as well as commensurate changes to the steady-state flow field were simulated. Finally, an example optimization study was undertaken for turbines arranged in various arrays to demonstrate the effects of lateral and downstream interference, wake recovery, and overall momentum removal on the flow conditions and power generation.

Considering a distribution of flow conditions over a 10-year period for the Tanana River at Nenana, variations in number of CEC devices and array layout provided insights into power production and environmental effects. Specific quantities of interest included changes in velocity and bed shear stress, which each showed changes in proportion to the number of devices in the array. Using SNL-Delft3D- CEC-FM with calibrated turbulence constants allowed for a design that maximized CEC array power while remaining within constraints of minimally altered environmental conditions. That is, array layouts could be selected to optimize power generation while minimizing flow-field changes.

This work highlights the importance of investigating array performance at each site under consideration. These findings are helpful in optimizing turbine arrangements in the Tanana River at Nenana that maximize power production and minimizes undesirable/unintended changes to the river's natural flow (flow depth, velocity, and bottom shear).
High-Voltage Subsea Connectors: Enabling Innovative Subsea Power Distribution Solutions
Authors: Plant Chris
Published: April 2020

This paper focuses on the development of the world's first high-voltage (HV) 45kV, wet-mate connector system1 qualified in accordance with the Subsea Electrical Power Standardization (SEPS) SP-1001 Penetrators and Connectors cross-operator standard. The connector is rated for water depths up to 3,000 meters and is a key enabler of numerous offshore applications, including subsea electrical power grids; independently retrievable, high-power step-down transformers for long step-out subsea gas compression; cost-effective installation of deepwater pipelines with direct electrical heating (DEH); and simplified repair of deepwater high-voltage umbilical power cores (among others). The high voltage and current rating of the connector provides the opportunity for commonality between the primary and secondary of a subsea transformer. This reduces the cost of mating tools, protective caps and test equipment, thus improving the economics of utilizing wet-mate connectors, which can often be cost-prohibitive.

The paper discusses the growing need for a clear industry standard that covers the development and qualification of HV wet-mate electrical connectors. It also explores the inherent challenges of subsea electrical connectors, including long-term reliability, subsea module integration activities, and long-term effects of sea-water immersion on insulating materials. These were identified through a policy of continuous stakeholder engagement and a thorough review of 40 years of low- and medium-voltage connector design.

To illustrate the benefits that HV wet-mate connectors can provide, multiple use cases are discussed, including long step-out subsea compression; deepwater pipeline DEH; and HV umbilical repair.
Certification Pathway for 3D Printed Parts - Unlocking the Barriers to Accelerate the Adoption of Additive Manufacturing in Offshore Industry
Authors: Kandukuri Sastry Yagnanna , Le Gallo Brice
Published: April 2020

Offshore industry assets are capital intensive and downtime can have severe financial consequences. Additive manufacturing (AM) based supply chains can potentially offer offshore industry stakeholders a strong value and a competitive advantage, from lower costs and lead times to greater flexibility and agility. However, the current adoption level of AM for the offshore industry is very limited, despite the consensus that such technology could have potential applications for spare parts, repair and even new builds. While adoption of additive manufacturing could be a source of positive change, inadequate understanding of requirements regarding approval, qualification and certification processes required by regulatory authorities could hinder the progress of AM adoption in the offshore industry.

Currently, there are only a handful of additive manufacturing standards available for early adopters of AM technology. Hence, costly and time-consuming nonstandard testing to ensure the integrity of the 3D printed parts is deterring the wider applications of additive manufacturing in the offshore sector, underscoring the need to develop optimal practice guidelines and standards from design to part build to operation.

This paper aims to highlight several key challenges that hinder the adoption of AM in the offshore sector and to propose various solutions that can help to overcome these. Due to its novel approach, the risk-based certification pathway discussed in this paper will help the offshore industry and its supply chain ecosystem to build trust and confidence in the adoption of this emerging technology, which otherwise might not be possible.
The Assessment of Microbial Surfactants as Asphaltenes Dispersants: Sophorolipids vs Dodecylbenzenesulfonic Acid
Authors: Aguiar Janaina I. S. , Rogers Jonathan , Mahmoudkhani Amir
Published: April 2020

Asphaltenes are a major problem for oil industry. Their variability in size, structure and polarity presents a challenge to develop formulations that are effective against precipitation and deposition for all types of asphaltenes. Also, changes in production systems, such as the rate of water break through, can also impact the efficiency of dispersants. In this paper sophorolipids, a class of microbial surfactants, that are renewable and biodegradable with low aquatic toxicity, are tested as asphaltene dispersants. In order to achieve the objectives of this study, asphaltenes were extracted from a heavy oil and their solubility and stability were evaluated at different concentrations of n-heptane and water. The behavior under n-heptane concentration sweep was found to be in line with previous experimental works and water did not change that behavior. The sophorolipids were able to inhibit ~100 % of the polar asphaltenes precipitation at low concentrations. Under similar conditions dodecylobenzesulfonic acid, which was used as a benchmark for comparison, did not perform at concentrations up to 1000 ppm either with or without water. The high performance of biosurfactants is attributed to their enhanced dispersing properties for organics such as wax and asphaltenes.
Comparison of Seismic Responses of a Fixed Offshore Structure for Ground Motion Records Considered Near Fault Effect and Fling Effect Generated Using Three Methods
Authors: Duman Servan , Vasala Haritha , Sari Ali
Published: April 2020

Offshore platforms, fixed or floaters, are a well-established design concept for oil explorations. It is fundamental to design these structures such that they can resist moderate to severe earthquakes without causing any severe damage to the occupants and to maintain the integrity of the structure. Hence, it is important to examine the behavior of these offshore structures for all kinds of earthquake scenarios to determine the risk levels that may occur in the structure. This paper intents to compare the seismic responses for a fixed offshore structure by employing ground motion records generated using three different methods.

The design spectrum determines the seismic hazard of a region. Therefore, it is necessary to use acceleration records compatible with the design spectrum in seismic analyses. In this paper, Scaling, Spectral matching and Stochastic methods were used for comparison. Peerscaled tool was used for scaling in the time domain. RspMatch was used for the Spectral Matching. New acceleration records were generated by QuakeSim. A series of non-linear time histories using acceleration records of scaled ground motions were carried out to compare the damage levels and responses of a fixed offshore structure.

Spectral matching method was observed to cause higher displacements than scaling method. The occurrence of inelastic events, such as buckling was observed to be high when the acceleration records considered the near-fault effect. And, permanent deformation was observed when acceleration records considered the fling effect. Ground motion records generated by different methods if adopted while performing seismic assessments of offshore structures will reduce the risk level for the structure.
Physics Based Machine Learning for Annular Blowout Preventer Health Monitoring
Authors: Mallek Moadh , Wassar Taoufik , Franchek Matthew A.
Published: April 2020

Physics-based models are efficient solutions capable of predicting the dynamic performance of engineering systems. Owing to the rapid data growth in sensor technologies, enormous datasets are readily available creating a unique opportunity to seamlessly fuse analytical physics based models with system data. This integration has produced a physics-based machine learning (PBML) knowledge base that overcomes the costly limitations of deep learning solutions and associated false discoveries of machine learning (ML) methods.

Presented in this paper is a University of Houston invented PBML approach to monitor the condition and performance applied to an annular preventer. A PBML model that describes the relationship between annular closing pressure and its cylinder displacement is derived. The model coefficients are adapted via system identification methods using real time collected data. The resulting coefficients are clustered to classify annular health from early age to middle age to aged cycles using the K-means method. Life cycle test of multiple annular preventers is performed using a full-scale testing facility. The results show that annular elastomer degradation can be detected and quantified using the proposed real-time adaptive physics based model solution given sensing information.
Pilot Study of Integration of Wildlife Impact Analysis into Spatial Environmental Assessment Tool for Marine Hydrokinetic Energy
Authors: Coates Shannon , Lockhart Gwen , Courbis Sarah , Raghukumar Kaustubha , McWilliams Samuel , Jones Craig
Published: April 2020

This study aimed to produce a pilot spatial model, building upon the existing quantitative Spatial Environmental Assessment Tool (SEAT), to evaluate risks associated with marine hydrokinetic energy (MHK) development within the Pacific Marine Energy Center South Energy Test Site, located off Newport, Oregon. The goal is to establish an approach for integrating natural resource sensitivities with changes in physical conditions caused by wave energy converter arrays to inform planning and impact assessment. To generate the model inputs, a benthic substrate proxy within the project area was defined as a "sensitive resource" input (Receptor), using the Risk (Rτ) output points from the SEAT model to identify areas that could be impacted by the operation of a MHK device (Threshold). Risks were further investigated by overlaying federally designated Habitat of Potential Concern, Essential Fish Habitat, and critical habitat to identify sensitive benthic resources (Secondary Constraint) within the project area. The last iteration of the model focused on using nearshore habitats for threatened coho salmon (Oncorhynchus kisutch) outmigrating from rivers to demonstrate how a higher taxon could be incorporated into the pilot model by assigning risk based on proximity to the shoreline. This approach allows the analyst to weight the sensitivity of natural resources and place secondary constraints and ocean conditions into the assessment for an integrated picture and can accommodate multiple taxa, seasons, habitats, and locations. Overall, the results of the four models were dependent on the weighting and scale of the data. The outcomes of this study are meant to demonstrate ability to integrate models and are not based on particularly defensible criteria. More rigorous literature review and risk assessment process would be necessary to demonstrate the project specific risk of impacts from MHK devices. This type of modeling can inform resource management and planning, and ultimately assist in identifying priority impact issues and mitigation needs throughout project siting and development, which will reduce risk and cost to developers.
Legged Robots for Autonomous Inspection and Monitoring of Offshore Assets
Authors: Ramezani Milad , Brandao Martim , Casseau Benoit , Havoutis Ioannis , Fallon Maurice
Published: April 2020

Inspection and monitoring of assets are repetitive and expensive tasks and have higher risk when facilities are located offshore. Robotics holds the promise of improving the efficiency and safety of such platforms by allowing inspection and continuous remote monitoring of difficult-to-access facilities.

Legged robots, such as quadrupedal robots, are promising machines to achieve this goal: they have high maneuverability both indoors and outdoors, they are designed for accessing and navigating facilities that are built for humans (e.g. stairs, step-over piping, narrow passageways) and can carry a variety of sensors targeted at inspection and monitoring tasks.

In this paper we introduce our approach for autonomous inspection of oil & gas platforms using legged robots. Our approach is being developed as part of the ORCA Hub (Offshore Robotics for Certification of Assets), a UK robotics research hub. We envision a highly autonomous robotic system that conducts inspections with minimal intervention by human operators. The robot can navigate through facilities, accomplishing crucial tasks such as 3D mapping, monitoring of thermal build-up using thermal cameras, pressure sensing and also using color cameras to detect people and to carry out general visual inspection. We demonstrate and evaluate the system's perception, locomotion and inspection capabilities on a training facility that realistically simulates an oil rig at the Fire Service College, Moreton-in-Marsh, UK and an industrial area in the Offshore Renewable Energy Catapult Facility, Blyth, UK. We show the result of both autonomous and real-time teleoperated missions, and analyze the accuracy and efficiency of the system.
Impact of Solvent Treatments for Asphaltenes on Wax Deposition and an Efficient Alternative with Green Surfactants
Authors: Aguiar Janaina I. S. , Pontifes Antonio A. , Nerris Anthony , Rogers Jonathan , Mahmoudkhani Amir
Published: April 2020

Asphaltenes and waxes can precipitate and deposit in reservoirs, wells and equipment increasing production and operation costs. Previous studies showed the co-precipitation of these heavy organic compounds under field conditions and that the chemical treatment for one fraction can affect the deposition mechanism of the other fraction. These facts led to a key question: Can solvents that are normally used for asphaltenes remediations affect wax deposition? In this paper, we dealt with the impacts of aromatic solvents addition to a waxy crude and studied characteristics of wax deposits obtained from Cold Finger testing at different ratios of solvent/oil. The results showed that depending on solvent concentration the Wax Appearance Temperature (WAT), composition of paraffins and deposition rate have significantly changed. It was also shown that a biodegradable and low toxicity biosurfactant demonstrated a remarkable efficiency as wax dispersant to control and reduce organics deposition.
Fit for Purpose LWD Shear Sonic Logging in Surface Hole Sections: Ensuring Quality Data for Drilling Risk Mitigation
Authors: Blyth Matthew Peter , Sakiyama Naoki , Yamamoto Hiroaki , Fahim Ud Din Syed Muhammad
Published: April 2020

The largest risks in deepwater well construction often occur in the shallow, surface hole sections where seismic uncertainty is high. This seismic uncertainty translates into increased error when estimating the position and extent of shallow hazards such as gas charged sediments, high pressure zones, wellbore stability concerns, faults, etc. Should these hazards be encountered unexpectedly, or without adequate preparation, then the associated operational costs and risks to safety can be extremely high. It is therefore critical that these risks are managed appropriately to ensure drilling success. Minimizing the uncertainty in the surface seismic requires adequate knowledge of both the compressional and shear velocities of these shallow sediments. Being able to turn this information into real-time drilling solutions to mitigate risk requires the acquisition of these measurements using logging while drilling (LWD) sonic tools in a wide variety formation types, often in large, and potentially washed out, surface holes and in a wide variety of mud types. This paper will discuss the physics of acquiring quadrupole shear measurements in large boreholes and slow formations. The limits of measurement will be explored, using both modeled data and real well examples, in a variety of formations, with different mud types, and in different borehole sizes. The effect on measurement quality as a result of the interplay among these three key parameters is revealed. The results show that, although the acquisition of reliable shear data in these conditions is challenging, it is not impossible, provided that the LWD tool is correctly designed, the physics are understood, and suitable processing applied. The latest generation of LWD sonic tools can therefore offer unique solutions to managing drilling risk.

As LWD sonic tools have become more advanced, they have become more routine in use and are now commonly used in multiple hole sections from surface to total depth. Utilizing the compressional and shear measurements from these tools as inputs into analysis to address concerns such as wellbore stability or seismic remigration requires a thorough understanding of the physics of the measurement, the effects of the borehole conditions and the limits of their capability. The challenges inherent in acquiring compressional velocity in large holes and slow formations are well documented, but the effect of these formations on measurements of LWD quadrupole shear has been much less discussed. The newly conducted intensive modeling study and field data analysis of the LWD quadrupole modes reveal that the effect of the drilling mud properties (slowness and density) is also important as well as the formation properties and the borehole size for deriving robust shear slowness.
Offshore Hydrogen Production in the North Sea Enables Far Offshore Wind Development
Authors: Peters Rene , Vaessen Jacqueline , Meer Rene van der
Published: April 2020

The North Sea area is in transition. While oil and gas production is in decline, the deployment of offshore wind turbines in large scale wind parks to produce offshore renewable energy is accelerating. The accelerated deployment of renewable wind increasingly far offshore creates challenges to transport large amounts of energy to shore. Traditional energy transport from offshore wind by means of HVAC power cables becomes uneconomic beyond 100 km from shore and energy losses are unacceptably high. Moving to HVDC cables reduces the power losses, but increases the cost of power conversion offshore. An alternative that currently is being considered is energy transport via molecules, in the form of hydrogen. The hydrogen is produced from seawater after desalinization by means of water electrolysis. The current pipeline infrastructure in the North Sea can be reused to transport the hydrogen at high pressure and low cost to shore. As large industry sectors are considering decarbonization by means of hydrogen, in particular for hydrotreatment, desulfurization and ammonia production, the so called ‘green’ hydrogen can directly be used onshore without reconversion to power.

Half of the assets in the North Sea are approaching end of life and decommissioning in the coming decade, which means they become available for re-purposing. Most offshore trunk lines also operate under their maximum capacity. Prior and ongoing research projects are aimed at identifying win-win combinations from this situation: to re-use platforms for hydrogen production (P2G), pipelines for hydrogen transport and perhaps wells for hydrogen or CO2 storage such that the variable nature of wind power can be exploited more efficiently.

The objective of the PosHYdon project, the first offshore hydrogen production plant is not only to build up experience with the production of H2 in an offshore environment, but it will also be a test center for innovative Power to Gas (P2G) technologies and integrated systems. The aim of the facility is to accommodate at least 1 MW of electrolyzer capacity, including its water treatment unit and auxiliary units. The objective of the project is to gain experience with the operation of a hydrogen production unit offshore, and the admixing of hydrogen in an multiphase flow pipeline carrying oil and gas towards a process separation and treatment hub located nearby. The pilot seeks to gain more detailed information on cost of installation and operation of an electrolyser unit in an offshore environment.
The Limits of Reduced Order Current Energy Converter Modeling
Authors: Olson Sterling S. , Topper Mathew B. R. , Chartrand Chris C. , James Scott C. , McWilliams Sam , Jones Craig A. , Roberts Jesse D.
Published: April 2020

Reduced-order models for mesoscale current energy converter (CEC) modeling allow for tractable computation times for investigations of array configurations on power performance and environmental effects to support design optimization. The CEC representation in these models take the form of actuator discs in codes such as SNL-Delft3D-CEC-FM treating the rotating CEC blades as momentum sinks. In the first-of-its-kind, whole-plant optimization software, DTOcean, the hydrodynamic modelling of CECs is reduced one step further by superimposing wake models based on normalized CFD simulations onto a set of pre-computed velocity fields, to provide power estimates. DTOcean is a new tool and the amount of verification and validation evidence gathered is presently limited. To gain additional confidence and industry buy-in to the software penetration, this study investigated a primary component of levelized cost of electricity (LCOE) calculation, annual energy production (AEP), through an analytic calculation of power using the results of an identical simulation in SNL-Delt3D-CEC-FM. Three configurations of an 8-turbine array are studied with DTOcean where two rows of 4-turbines are spaced (unstaggered) 5-, 10-, and 20-Diameters apart and the AEP was calculated; The energy calculation in SNL-Delft3D-CEC-FM were more computationally expensive for the mesoscale domain making the optimization of solely an arrays power production using the wake superposition method implemented DTOcean attractive. The codes however are complementary as SNL-Delft3D-CEC-FM simultaneously investigates environmental effects of varying array configurations while DTOcean considers all aspects of array costs through its lifetime to optimize LCOE from a whole-plant perspective.
Managing Hydrate Formation in Subsea Production
Authors: May Eric F. , Metaxas Peter J. , Lim Vincent W. S. , Jeong Kwanghee , Norris Bruce W. , Kuteyi Temiloluwa O. , Stanwix Paul L. , Johns Michael L. , Aman Zachary M.
Published: April 2020

Quantitative prediction of gas hydrate formation risk is critical for the successful implementation of risk-based approaches to hydrate management in subsea production. Here we use a high pressure, stirred, automated lag-time apparatus and a high pressure acoustic levitator to experimentally obtain smooth probability distributions describing stochastic hydrate formation. Robust, repeatable hydrate nucleation and growth rate probability distributions as a function of induction time and subcooling are measured for various gases, shear rates and inhibitor dosages in systems with interfacial areas ranging from (0.1 to 60) cm2. The results reveal that new engineering models can be used to reliably predict hydrate formation probability. Importantly these new models have solid theoretical foundations which enables them to be generalized with confidence to industrial systems.
Hidden Value in Maintenance System Data: Using Machine Learning to Correlate and Predict the Risk of Asset Failures
Authors: Pereira Paul Christopher
Published: April 2020

The prediction of equipment failures typically falls along two paths: statistical analysis of past failures, or using sensor data to monitor the condition of equipment in the field. This study instead takes a novel approach by implementing machine learning on the data within maintenance systems (which are typically used to monitor and track maintenance activities/workflows). This implementation serves to map the correlations between maintenance data and failures, to predict failures by only monitoring an organization's maintenance system.

This involved identifying maintenance system variables or attributes that normally represent specific steps in the maintenance process, but could potentially provide indirect information on the reliability of assets or the risk of future failure (e.g. work orders created/completed, work order types, original equipment manufacturer recalls/upgrades, inventory rotation rates, procedure changes, turnaround events, etc.). Machine learning is then used to determine correlations between failures and system variables (which results in an optimized model). The resulting model can then be implemented on current data to predict future failures.

Although largely designed around workflow management, the underlying metadata from an organization's maintenance system can indeed be transformed to provide valuable insights and quantify risk. Machine Learning is able to predict failures with a meaningful degree of accuracy. Even if the transparency of model logic is insufficient to take specific actions to mitigate failures, it is enough to dynamically assign a level of risk to individual assets, and even predict risk for future time periods. When interpreting the optimized machine learning model with methods such as feature impact charts, it is also possible to identify the strongest correlations between failures and different Computerized Maintenance Management System (CMMS) derived variables (variables that were designed and transformed from actual historical data for the purpose of model building). Insights gained from this additional analysis, such as the true impact that preventive maintenance delays have on risk, offer great potential for understanding the behavior of equipment and maintenance organizations.