bluuebunny/crossref_metadata_2025 huggingface dataset:
Complicate dynamical analysis of a discrete predator-prey model with a prey refuge
Authors: Khan A. Q. , Alsulami Ibraheem M.
Published: April 2023

In this paper, some complicated dynamic characteristics are formulated for a discrete predator-prey model with a prey refuge. After studying the local dynamical properties about fixed points, our main purpose is to investigate condition(s) for the occurrence of flip and hopf bifurcations, respectively. Further, by the bifurcation theory, we have studied flip bifurcation at boundary fixed point, and flip and hopf bifurcations at interior fixed point of the discrete model. We have also studied chaos by state feedback control strategy. Furthermore, theoretical results are numerically verified. Finally, we have also discussed the influence of prey refuge in the discrete model.
A novel Bayesian federated learning framework to address multi-dimensional heterogeneity problem
Authors: Yang Jianye , Yan Tongjiang , Ren Pengcheng
Published: April 2023

Federated learning (FL) has attracted a lot of interests as a promising machine learning approach to protect user privacy and data security. It requires the clients to send model parameters to the server rather than private datasets, thus protecting privacy to a significant extent. However, there are several types of heterogeneities (data, model, objective and systems) in FL scenario, posing distinct challenges to the canonical FL algorithm (FedAvg). In this work, we propose a novel FL framework that integrates knowledge distillation and Bayesian inference to address this multi-dimensional heterogeneity problem. On the client side, we approximate the local likelihood function using a scaled multi-dimensional Gaussian probability density function (PDF). Moreover, each client is allowed to design customized model according to the requirement through knowledge distillation. On the server side, a multi-Gaussian product mechanism is employed to construct and maximize the global likelihood function, greatly enhancing the accuracy of the aggregated model in the case of data heterogeneity. Finally, we show in extensive empirical experiments on various datasets and settings that global model and local model can achieve better performance and require fewer communication rounds to converge compared with other FL techniques.
A decision-making strategy to combat CO$ _2 $ emissions using sine trigonometric aggregation operators with cubic bipolar fuzzy input
Authors: Habib Anam , Khan Zareen A. , Jamil Nimra , Riaz Muhammad
Published: April 2023

A cubic bipolar fuzzy set (CBFS) is by far the most efficient model for handling bipolar fuzziness because it carries both single-valued (SV) and interval-valued (Ⅳ) bipolar fuzzy numbers at the same time. The sine trigonometric function possesses two consequential qualities, namely, periodicity and symmetry, both of which are helpful tools for matching decision makers' conjectures. This article aims to integrate the sine function and cubic bipolar fuzzy data. As a result, sine trigonometric operational laws (STOLs) for cubic bipolar fuzzy numbers (CBFNs) are defined in this article. Premised on these laws, a substantial range of aggregation operators (AOs) are introduced. Certain features of these operators, including monotonicity, idempotency, and boundedness, are explored as well. Using the proffered AOs, a novel multi-criteria group decision-making (MCGDM) strategy is developed. An extensive case study of carbon capture and storage (CCS) technology has been provided to show the viability of the suggested method. A numerical example is provided to manifest the feasibility of the developed approach. Finally, a comparison study is executed to discuss the efficacy of the novel MCGDM framework.
Numerical approximation of Atangana-Baleanu Caputo derivative for space-time fractional diffusion equations
Authors: Wali Mubashara , Arshad Sadia , Eldin Sayed M , Siddique Imran
Published: April 2023

In this study, we attempt to obtain the approximate solution for the time-space fractional linear and nonlinear diffusion equations. A finite difference approach is given for the solution of both linear and nonlinear fractional order diffusion problems. The Riesz fractional derivative in space is specifically approximated using the centered difference scheme. A system of Atangana-Baleanu Caputo equations that have been converted through spatial discretization is solved using a newly developed modified Simpson's 1/3 formula. A study of the proposed scheme is done to ascertain its stability and convergence. It has been shown that for mesh size h and time steps $ \delta t $ the recommended method converges at a rate of $ O(\delta t^2 + h^2) $. Based on graphic results and numerical examples, the application of the model is also examined.
Solvability and representations of the general solutions to some nonlinear difference equations of second order
Authors: Stević Stevo
Published: April 2023

We give detailed theoretical explanations for getting the closed-form formulas and representations for the general solutions to four special cases of a class of nonlinear difference equations of second order considered in the literature, present an extension of the class of difference equations which is solvable in closed form, analyze some results on the long-term behavior of the solutions to the class of equations, and give some results on convergence.
Dynamic behaviors of a Leslie-Gower model with strong Allee effect and fear effect in prey
Authors: Zhu Zhenliang , Chen Yuming , Li Zhong , Chen Fengde
Published: April 2023

We incorporate the strong Allee effect and fear effect in prey into a Leslie-Gower model. The origin is an attractor, which implies that the ecological system collapses at low densities. Qualitative analysis reveals that both effects are crucial in determining the dynamical behaviors of the model. There can be different types of bifurcations such as saddle-node bifurcation, non-degenerate Hopf bifurcation with a simple limit cycle, degenerate Hopf bifurcation with multiple limit cycles, Bogdanov-Takens bifurcation, and homoclinic bifurcation.
Stability switches, periodic oscillations and global stability in an infectious disease model with multiple time delays
Authors: Kumar Anuj , Takeuchi Yasuhiro , Srivastava Prashant K
Published: April 2023

A delay differential equation model of an infectious disease is considered and analyzed. In this model, the impact of information due to the presence of infection is considered explicitly. As information propagation is dependent on the prevalence of the disease, the delay in reporting the prevalence is an important factor. Further, the time lag in waning immunity related to protective measures (such as vaccination, self-protection, responsive behaviour etc.) is also accounted. Qualitative analysis of the equilibrium points of the model is executed and it is observed that when the basic reproduction number is less unity, the local stability of the disease free equilibrium (DFE) depends on the rate of immunity loss as well as on the time delay for the waning of immunity. If the delay in immunity loss is less than a threshold quantity, the DFE is stable, whereas, it loses its stability when the delay parameter crosses the threshold value. When, the basic reproduction number is greater than unity, the unique endemic equilibrium point is found locally stable irrespective of the delay effect under certain parametric conditions. Further, we have analyzed the model system for different scenarios of both delays (i.e., no delay, only one delay, and both delay present). Due to these delays, oscillatory nature of the population is obtained with the help of Hopf bifurcation analysis in each scenario. Moreover, at two different time delays (delay in information's propagation), the emergence of multiple stability switches is investigated for the model system which is termed as Hopf-Hopf (double) bifurcation. Also, the global stability of the endemic equilibrium point is established under some parametric conditions by constructing a suitable Lyapunov function irrespective of time lags. In order to support and explore qualitative results, exhaustive numerical experimentations are carried out which lead to important biological insights and also, these results are compared with existing results.
Bayesian estimation of parameters in viral dynamics models with antiviral effect of interferons in a cell culture
Authors: Rodríguez-Parra Miguel Ángel , Vargas-De-León Cruz , Godinez-Jaimes Flaviano , Martinez-Lázaro Celia
Published: April 2023

The goal of this work is to estimate the efficacy of interferon therapy in the inhibition of infection by the human immunodeficiency virus type 1 (HIV-1) in a cell culture. For this purpose, three viral dynamics models with the antiviral effect of interferons are presented; the dynamics of cell growth differ among the models, and a variant with Gompertz-type cell dynamics is proposed. A Bayesian statistics approach is used to estimate the cell dynamics parameters, viral dynamics and interferon efficacy. The models are fitted to sets of experimental data on cell growth, HIV-1 infection without interferon therapy and HIV-1 infection with interferon therapy, respectively. The Watanabe-Akaike information criterion (WAIC) is used to determine the model that best fits the experimental data. In addition to the estimated model parameters, the average lifespan of the infected cells and the basic reproductive number are calculated.
Hepcidin and iron metabolism in preterm infants
Authors: Ruan Sufeng , Yang Sufei , Li Jinrong , Xiong Fei , Qie Di , Lu You , Tang Zhanghui , Yang Fan
Published: April 2023

Background

Iron deficiency (ID) and ID anemia are widespread in low-income countries, particularly among preterm infants. Hepcidin is a key regulator of iron metabolism, which offers the possibility of new solutions to diagnose ID in premature infants.

Objective

To explore the relationship between iron metabolism and hepcidin in premature infants.

Materials and methods

The study involved 81 preterm infants between 28+1 and 36+6 who underwent iron status indicators and hepcidin testing at 6 months of corrected gestational age. The preterm infants were divided into two groups based on iron status indicators: ID and no ID.

Results

Serum hepcidin was lower for premature infants with ID compared to those without ID (log10hepcidin, 1.18 ± 0.44 vs 1.49 ± 0.37, p = 0.002). A single-variate linear regression model was used to explore the correlation between hepcidin and other indicators of iron metabolism. A strongly positive relationship was observed between hepcidin levels and ferritin levels (p < 0.001) in the correlation analysis.

Conclusions

Hepcidin can be used as an efficient indicator of iron storage and a promising indicator for the early diagnosis of ID in premature infants.
Adapting patient treatment of neurological diseases during the COVID-19 pandemic
Authors: Mendoza Scott
Published: April 2023

Treating neurological patients during the pandemic period has become extremely challenging. At the same time, responding properly to these challenges has been diverse around the world, with varying levels of readiness, discipline, and approach. Additionally, there are significant differences in healthcare resources and processes between nations, and even within a nation, and these have significantly influenced the treatment procedure throughout the pandemic. However, neurologists have been called to care for patients with neurological symptoms who have COVID-19, and to continue managing COVID-19-affected neurological comorbidities in patients as before. This study highlights how the treatment procedures for neurological diseases are rapidly changing due to the spread of the SARS-CoV-2 virus. It also focuses on the challenges healthcare professionals are facing while providing proper treatment to neurological patients during the pandemic situation. Lastly, it offers some useful recommendations regarding the effective management of neurological diseases during the COVID-19 pandemic period.
Anxiety, insomnia and family support in nurses, two years after the onset of the pandemic crisis
Authors: Sikaras Christos , Tsironi Maria , Zyga Sofia , Panagiotou Aspasia
Published: April 2023

Introduction

The Covid-19 pandemic continues to cause serious physical and mental problems for health professionals, particularly nurses.

Aim

To estimate the prevalence of anxiety and insomnia and to evaluate their possible association with family support received by nurses two years after the onset of the pandemic.

Materials and methods

In total, the study participants were 404 nurses (335 females and 69 males) with a mean age of 42.88 (SD = 10.9) years and a mean of 17.96 (SD = 12) years working as nurses. Nurses from five tertiary hospitals in Athens constituted the study population who completed the questionnaires State-Trait Anxiety Inventory (STAI), Athens Insomnia Scale (AIS) and Family Support Scale (FSS), in the months of November and December 2021. Regarding demographic and occupational characteristics, gender, age and years of experience as nurses were recorded.

Results

60.1% of the nurses showed abnormal scores in state anxiety, with 46.8% in trait anxiety, and 61.4% showed insomnia. Women showed higher scores on the two subscales of anxiety and the insomnia scale compared to men (p < 0.01 and p < 0.05 respectively), while they showed a lower score on the FSS without statistical significance (p > 0.05). Positive correlations (p < 0.01) were found between the State Anxiety Inventory, Trait Anxiety Inventory and AIS, while all of them showed a high negative correlation with FSS (p < 0.01). Age showed a negative correlation with Trait Anxiety Inventory (p < 0.05). As shown by the mediation analysis, the relationship between state anxiety and insomnia was mediated by trait anxiety, whereas state anxiety appeared to be dependent on family support.

Conclusions

Nurses continue to experience high levels of anxiety and insomnia and feel less supported by their families than in the first year of the pandemic. Insomnia appears to be dependent on state anxiety, with a significant indirect effect of trait anxiety, while family support seems to affect state anxiety.
End-To-End Surface and Subsurface Monitoring and Surveillance for the Onshore and Offshore CCS or CCUS Projects
Authors: Patil Pramod D. , Al-Qasim Abdulaziz S. , Al-Zayani Alia I , Kokal Sunil L.
Published: April 2023

Monitoring and surveillance (M&S) is one of the key requisites for assessing the effectiveness and success of any onshore and offshore CCS/CCUS project. It will help understand, track, monitor, and predict the injectant plume migration, flow paths, and breakthrough times. The M&S helps in quantifying sequestered injected gas and any inadvertent leakage. It provides a good understanding of the remaining oil saturation (ROS) and its distribution in the reservoir.

In this manuscript, a comprehensive monitoring and surveillance (M&S) program is developed and discussed for the onshore and offshore CCUS/CCS projects. A range of monitoring techniques are available for the CO2 geological storage in onshore and offshore reservoirs. The advanced M&S plan incorporates conventional, advanced, and emerging novel technologies for wellbore and inter-well measurements. Both deep focused (providing surveillance of the reservoir and deeper overburden) and shallow-focused (providing surveillance of the near seabed, seabed and water column). These include advanced time-lapse pulsed neutron, resistivity, diffusion logs, and bore-hole gravity measurements, cross-well geophysical measurements, water and gas tracers, geochemical, compositional and soil gas analyses, and 4D seismic and surface gravity measurements.

Results from monitoring and surveillance technologies provide a better understanding of the reservoir dynamics within the subject area. The results can be used to refine the reservoir simulation model and fine tune its parameters. This paper reviews some proven best practices and draws examples from ongoing projects and related novel technologies being deployed for onshore and offshore reservoirs. It will then look at the new horizon for M&S technologies for onshore and offshore CCS and CCUS projects.
Successful Metal Loss and Choke Health Simulation and Predictions Save Time and Cost - Case Study
Authors: Sivakumar Vinnavadi Babu C , Ahmed Rehan , Gupta Abhishek , Mahmud Yusoff , Lo Kar Men , Yusop Addy , Ali Ariff
Published: April 2023

The current practices in oil & Gas industry lack digitalization in the field of Sand Management. A recently developed simulator was identified and employed to conduct a pilot study and hence compare the metal loss and choke health data with the real field thickness sensor and choke inspection data. The objective of the Study was to carry out an analysis of the current challenges in the Sand Management portfolio of the organization and to present solutions via the software.

The challenges included: Identifying the Total Metal Loss & Deposition hotspots for entire field.Development of a robust strategy to manage production chokes.Study of corrosion effects on erosion due to sand.The obtained results to be in accordance with the actual field conditions.Provide recommendations for efficient sand management and cost savings.

A thorough Sand Management study inclusive of Total Metal Loss (Erosion + Corrosion), Depositional and Handling risks related to the Well and Facility were studied using the software's advanced sand travel logics, unique features & multi-level sensitivity analysis.

The main Outputs from the study were: Metal Loss Hotspots & their values for all the facility pipelines were identified, calibrated and Validated.The study provided road maps to answer the uncertainties related to the incoming Particle Size Distribution (PSD), incoming and surface Sand Concentration through work-flows and sensitivity analysis.A Choke Management workflow was displayed which not only simulates the current condition of the choke but can also predicts future failures and help in optimizing choke for longevity.Component Life & Minimum Allowable wall thickness calculations. At the end of this phase, the results were presented & validated by the Petronas Technical team.

As a result of the above study, the benefits of the software's accurate predictions were: Cost & Time Saving: the frequency of sand sensor data collection can be increased. Also, since the hotspots have already been pin-pointed by the simulator, there is no need to conduct the metal loss sensor survey for the entire pipeline, it can be focused to the hotspots only.Carbon Footprint Reduction: Higher frequency would result in lower human intervention.The metal Loss and health data can be visualized on a real-time basis hence a more pro-active approach can be applied to tackle the integrity issues.

Substantial increase in revenue and reduction in expenditure can be done by predicting and mitigating the sand related risks. This Simulator can cover the entire cradle to grave period of a field & this new outlook of sand management would be highly beneficial to industry.
Enabling Ecosystem Based Management: New Ways to Conduct Deep Sea Minerals Exploration
Authors: Smit Hans , Meyer Laurie , Flynn Adrian , van Eck Gary , Cecino Giorgia
Published: April 2023

The Cook Islands (CI) possesses within its Exclusive Economic Zone (EEZ) a massive field of polymetallic nodules representing one of the world's largest undeveloped cobalt deposits, along with large quantities of other metals critical to achieving global energy transition targets. In February of 2022 the Seabed Minerals Authority (SBMA) of the CI granted licenses to three companies to conduct nodule exploration programs. This paper describes the process adopted by Moana Minerals, one of the license holders, to define new ways of conducting exploration which are focused on addressing the greatest challenge to Deep Sea Mining (DSM) development – that of securing the social license to advance to eventual mining of the resources.

While it is generally true for any DSM project, obtaining license to operate within the EEZ of a sovereign nation requires even more focus on socio-economic and cultural concerns. Hence Moana Minerals invested even before exploration license award in the completion of an Environmental and Social Impact Assessment (ESIA) scoping study. This exercise helped to define the key questions and concerns, the range of stakeholders in the ESIA process, and began to construct the Ecosystem Based Model which is the heart of our ESIA program. We describe our employment of the increasingly adopted best practice of Ecosystem Based Management (EBM), which considers the entire ecosystem and its services, and the complex associated interactions for a "whole of system" approach. We discuss how this model is used to help communicate relationships between potential stressors associated with seabed mining and ecosystem responses, as well as how it is used to identify thresholds and guide development and adaptation of ecosystem management approaches. Given the challenges of the remoteness of the Cook Islands, limited exploration assets in the region, and ongoing supply chain delays and limitations, our early analysis of how best to execute an EBM-based program concluded that a dedicated research vessel properly outfitted with a full suite of scientific gear would be key to success. We describe our program to economically develop such an exploration system through repurposing an offshore support vessel, with an aim towards maximum suitability for Cook Islands-based exploration and other deep sea exploration work in the region as well as other potential high value regional applications. Finally, we discuss operations to date using this critical exploration-enabling asset.
Upheaval Buckling of Unbonded Flexible Pipes: An Alternative Approach
Authors: Murray Sean , Casanovas Clara , Tan Zhimin , Trousdale Euan , Liu Jian , Patrocinio Juliana , Zhu Linfa , Lopes de Castro Mario Augusto
Published: April 2023

Due to their non-linear bending response, low bending stiffness and potentially high axial expansion coefficients, buried unbonded flexible pipes can be susceptible to Upheaval Buckling (UHB). The traditional industry approach is to prevent UHB by providing sufficient download to limit upwards movement of the pipe to very small levels (normally within the mobilisation distance of the soil). Since unbonded flexible pipes offer little resistance to bending, the required download to prevent UHB of unbonded flexible pipes can be significant resulting in prohibitive rock-dump requirements. However, by design, unbonded flexible pipes can accommodate large bending deformations without compromising the cross-sectional integrity of the pipe. The objective of this paper is to propose an approach which takes advantage of the pipes capability to accommodate large deformations and to minimize download requirements.

This paper presents a comprehensive literature review of the state-of-the-art methods currently adopted in industry for the assessment of UHB of buried unbonded flexible pipelines. An alternative approach which permits significant upwards movement of the flexible pipe, taking advantage of the pipes ability to accommodate such movements, is also presented. A comparison of the potential failure modes, mechanisms and consequences associated with these approaches are studied and acceptance criteria are proposed. Parametric finite element analysis studies are performed to compare the flexible pipe behaviour and download requirements using the traditional approach and the proposed alternative approach.

This paper presents case studies which demonstrate that significant savings in the volume of rock-dump can be safely made when permitting large deformations when compared to the traditional UHB prevention approach.
Slug Forecasting and Production Optimization Using Deep Learning
Authors: Dabholkar Dinesh , Rawat Devina , Manikani Sunil , Abraham Doney
Published: April 2023

Subsea fields characterized by multiphase reservoir, deep wells, and pipeline-riser setups, are prone to slugging. Sustained slugs arriving at surface facilities, cause several operational challenges leading to reduced production or field shutdown. Reliable forecasting of slugging behavior is crucial in mitigating slugging and optimizing field behavior. The goal of this work was to assess potential of deep learning models for slugging forecasting and production optimization. Historical data from several field transmitters which record signatures specific to slugging events was collected and studied. Domain experts classified normal flow, unstable flow, and slug flow conditions in the field based on those data. Several deep learning-based models were trained on the supervised data to generalize correlations for slug identification and forecasting. Experiments were conducted on the labelled data to identify best suitable prediction model. A state-of-the-art temporal fusion transformer model was selected for time series forecasting based on experiments.

The real-time and historical data possess noisy signals and skewed distribution depending upon frequency of slug events. The deep learning model was found to overcome these challenges and successfully learn the complex interaction in time between various field variables and correlate with slugging patterns. Not only was the model able to classify between slug and no-slug events, but it was further able to forecast slugging critical variables such as slug frequency, amplitude, slug volume, etc. The selected model outperformed traditional statistical models such as Non-Parametric Time Series (NPTS) and other deep neural network models such as DeepAR, and Simple Feed Forward. The model was able to match the flow behavior during slugging events with continuously improved performance after multiple training exercises on additional data. This novel solution can be used for active monitoring of slugging conditions in field, generating alerts and provide forecasting on slug critical information.

Visibility in the future will enable understanding of slugging behavior and empower the operators to take proactive mitigation measures based on predicted slugging signatures. This will improve the operational efficiency and hence minimize the negative impact of slugging on productivity, asset integrity and the environment.
Offshore Connectivity as Leverage of Mobility Technologies
Authors: Fasone Gianny Stavros Rodrigues , Gusmão Vinicius Guedes , Da Silva Neta Lídia Moura Matos
Published: April 2023

Innovation and new technologies come hand by hand in the Oil and Gas industry adding value and improving processes and safety at the same time reducing costs. This paper presents how the improvement of wireless connectivity in offshore platforms has been supporting critical mission activities, deployment of IIoT devices and field workers mobility.

Wireless networks were expanded in industrial environments enabling a wide variety of new services. Meanwhile, the most impacted operational processes were selected where disruptive technologies could generate more value, such as maintenance and inspection processes. After this, we evolved each insight through the Technology Readiness Level steps; beginning with the Proofs of Concept for decision making until we could scale it up and measure its benefits. Explosion-proof devices were used to provide mobile connectivity to robots and IIoT devices. Augmented reality glasses running remote and guided assistance software, increased collaboration, adding more expertise and knowledge to operational activities at Campos basis.
Comparison between Coupled and Uncoupled Dynamic Analysis of Offshore Wind Turbine Generators (WTG) Support Structures
Authors: Gupta Anupam , Desai Ankit , McDonald Geoff , Sarada Shashikant
Published: April 2023

As offshore wind generation activities continue to expand in the United States, there is a growing need for more efficient, optimized, and reliable analysis of the foundation structures that support Wind Turbine Generators (WTGs). This paper aims to provide a comparison of coupled and uncoupled analysis methodologies for the design of offshore WTG foundation structures under complex dynamic loading from turbine operation and sea states. The focus is on an integrated turbine, turbine tower, and foundation model, which is essential for understanding the behavior of the entire system under various loading conditions. The goal of this paper is to provide insight into the strengths and limitations of two different analysis approaches, coupled and uncoupled, with the aim of helping engineers and designers make more informed decisions when it comes to the design and construction of offshore WTG foundation structures.

In this research, an integrated substructure, turbine, and tower model was developed to support the offshore wind turbine. Both coupled and uncoupled dynamic analysis methods were applied to the analysis models. The dynamic turbine loads were calculated using wind turbine information from the National Renewable Energy Laboratory (NREL). Modal analyses were performed to determine the mode shapes and natural frequencies as well as dynamic time history analysis to determine hydrodynamic forces on the support structure. The forces and displacements at the interface joint were then compared to evaluate the difference in behavior between the uncoupled and coupled solutions.

This study aims to fill a gap in the current literature by comparing coupled and uncoupled analysis methodologies specific to the integrated model of WTG foundation structure. The paper presents a side-by-side comparison of the coupled and uncoupled analysis using SACS analysis software by Bentley and the OpenFAST program by NREL. SACS is one of the most widely used software packages for the design and analysis of offshore structures in the United States.

The findings from these case studies on monopile and jacket foundation types offer a deeper understanding of the distinctions and similarities between coupled and uncoupled analysis of the integrated structure model. This paper presents the conclusions from the study and summarize the key observations to assist engineers in creating simulation models and analyzing WTG foundation structures. These observations will aid in comprehending the complexities of the dynamic behavior of the WTG foundation structure under combined environmental and turbine loading.
Optimization of Well Completion Strategy for Double Displacement Process (DDP) and Water Alternating Gas (WAG) Injection in a Dipping Stratified Reservoir
Authors: Ngo Vuong Thanh , James Lesley A
Published: April 2023

This study assesses how zone-by-zone completion strategy which including top-down & bottom-up mechanisms affect the performance of the double displacement process (DDP) and water alternating gas (WAG) up-dip and down-dip. It further seeks to develop an optimal zone-by-zone completion strategy to overcome the gas override problem and increase oil recovery in a dipping stratified reservoir. The impact of connection transmissibility on completion strategies in a dipping stratified reservoir is also investigated.

The research was conducted on a stratified block model reservoir with dimension 4000 m × 1000 m × 80 m and is divided into four main reservoir zones in Z direction. Zones are separated from each other by a thin shale bed with thickness of 0.2 m. The communication between reservoir zones and shale beds have level of 0, 0.1, 0.01 relating to completely sealing shale, leaky shale and completely open shale. Well completion strategies simulated included all zones injecting and producing, top-down and bottom-up. The simulation begins with waterflooding to obtain 95% water cut, then the performance of DDP, WAG up-dip, and WAG down-dip with the various completion strategies were simulated.

The results prove that zone-by-zone completion strategy is a successful way to overcome gas override and improve vertical conformance with WAG injection in a stratified reservoir to maximize oil recovery from the offshore field in East Canada. With zone-by-zone completion strategy, the recovery factor of WAG up-dip increased 0.8% more than the all-zone injecting and producing scheme. The results also identified bottom-up was effective completion strategy for WAG up-dip in stratified reservoirs without zonal communication and top-down was a successful completion strategy for communicating stratified reservoirs with 0.01 level of connection transmissibility with WAG up-dip and without zonal communication with WAG down-dip. DDP and WAG are considered as potentially effective enhanced oil recovery methods for offshore reservoir. However, most of studies be conducted on laboratory and reservoir simulation scale, and focus on operation parameters such as WAG ratio, WAG cycle, slug size. Our understanding is that this is the first study on the effect of top-down and bottom-up completion strategies to the performance of DDP and WAG in pilot stage on a dipping stratified reservoir block model.
ROV Teleoperation based on Sensory Augmentation and Digital Twins
Authors: Xia Pengxiang , McSweeney Kevin P. , Song Zhuoyuan , Du Eric
Published: April 2023

ROV operations are mainly performed via a traditional control kiosk and limited data feedback methods, such as the use of joysticks and camera view displays equipped on a surface vessel. This traditional setup requires significant personnel on board (POB) time and imposes high requirements for personnel training. This paper proposes a virtual reality (VR) based haptic-visual ROV teleoperation system that can substantially simplify ROV teleoperation and enhance the remote operator's situational awareness.

This study leverages the recent development in Mixed Reality (MR) technologies, sensory augmentation, sensing technologies, and closed-loop control, to visualize and render complex underwater environmental data in an intuitive and immersive way. The raw sensor data will be processed with physics engine systems and rendered as a high-fidelity digital twin model in game engines. Certain features will be visualized and displayed via the VR headset, whereas others will be manifested as haptic and tactile cues via our haptic feedback systems. We applied a simulation approach to test the developed system.

With our developed system, a high-fidelity subsea environment is reconstructed based on the sensor data collected from an ROV including the bathymetric, hydrodynamic, visual, and vehicle navigational measurements. Specifically, the vehicle is equipped with a navigation sensor system for real-time state estimation, an acoustic Doppler current profiler for far-field flow measurement, and a bio-inspired artificial literal-line hydrodynamic sensor system for near-field small-scale hydrodynamics. Optimized game engine rendering algorithms then visualize key environmental features as augmented user interface elements in a VR headset, such as color-coded vectors, to indicate the environmental impact on the performance and function of the ROV. In addition, augmenting environmental feedback such as hydrodynamic forces are translated into patterned haptic stimuli via a haptic suit for indicating drift-inducing flows in the near field. A pilot case study was performed to verify the feasibility and effectiveness of the system design in a series of simulated ROV operation tasks.

ROVs are widely used in subsea exploration and intervention tasks, playing a critical role in offshore inspection, installation, and maintenance activities. The innovative ROV teleoperation feedback and control system will lower the barrier for ROV pilot jobs.
Cyclic Strength of Soils at Atlantic Shores Offshore Wind Farm
Authors: Peralta Proserpine , Vembu Kalaiarasi , Dow Fraser Jack , Adhikari Sudarshan , Trandafir Aurelian , Long Xiaoyan , Hargrave Deanne
Published: April 2023

The cyclic soil behavior of North Sea clays and silica sands have been well-documented (Andersen 2004, 2009, etc), and have been used globally to develop soil models and design foundations for structures subjected to cyclic wave loading. The recent development of offshore wind farms within the Atlantic Offshore Continental Shelf (OCS) in the U.S. have prompted the large-scale design of fixed-bottom foundations of offshore wind structures, which are designed to be highly dynamic. In contrast to North Sea soils, very few data have been published regarding the strength behavior of typical Atlantic OCS soils. This has prompted the need to review industry-accepted soil models and cyclic design procedures based on empirical data and model testing from the North Sea and whether these may be applicable to Atlantic OCS soils. This paper presents cyclic soil data from a series of triaxial and direct simple shear tests on clay, silt, and sand samples from the Atlantic Shores Offshore Wind Lease Area in offshore New Jersey. A comparison of the soil behavior is made to published North Sea soils data and recommendations are provided on soil parameters for application to foundation design procedures for offshore wind structures within the Atlantic OCS.
Decarbonization Strategies to Reduce GHG Emissions on the All Electric FPSO
Authors: Correia Rosana de Freitas , do Vale Osvaldo Roberto , Barros Igor Malamace de Azevedo , Braun Felipe Eduardo , Pivatto Bruno Coccaro , Cavaliere Carlos Andre Carreiro , Soares Fabricio Benites , Ferreira Daniel , Costa Marcia Gusmão Teixeira , Takemoto Alexandre Yudi Mille , Barbosa Rodrigo Suzart Alca , Ribeiro Leonardo da Silva
Published: April 2023

This paper presents a set of technologies and optimizations implemented in the All Electric FPSO, the largest PETROBRAS’ design, that was conceived to operate in Atapu and Sépia fields and will become into P-84 and P-85 FPSOs, respectively. This design was done to increase the Pre-Salt production, add more value to its reserves and minimize greenhouse gas (GHG) emissions. All Electric concept considers all rotating process equipment to be driven by electrical motors. Based on this concept, the process plant configuration and the number of equipment trains were defined to comply with the flow capacities. The adoption of this new concept was possible due to proactive advocacy of PETROBRAS and other oil and gas companies for the revision of an environmental regulation that limited its use (CONAMA 382/2006). Moreover, other decarbonization solutions were selected and incorporated on the project based on MACC methodology and PETROBRAS's low carbon strategy. Considering the typical emissions of a FPSO, the technologies and optimizations were deployed on the main sources: power generation, flaring, venting and fugitives. Some reduction emission initiatives were implemented for the first time in a FPSO of large capacity, such as: all-electric plant concept, deeper seawater intake system, cargo tanks gas blanketing and recovery system and variable speed control on water injection pumps. Moreover, known technologies such as flare gas recovery system, closed drainage gas recovery system, cogeneration, low fugitive emission valves, and CCUS-EOR etc. were also used on All Electric FPSO design. As a result, the GHG emission intensity achieved was estimated about up to 30% less than previous FPSO designs. Another accomplishment was the zero routine flaring and venting, based on World Bank initiative, which PETROBRAS is committed. Finally, all these initiatives are significant to the company achieve its goals, maximizing value and producing oil and gas with reduction of GHG emissions. The All Electric FPSO design is an example of how an energy efficiency approach could achieve a reduction in GHG emissions. The lessons learned during the development of this design contribute to broaden the knowledge for oil and gas industry decarbonization.
Applications of Additive Manufacturing in Subsea Production Systems
Authors: Della Roverys Coseglio Mario Sergio , Velazquez Rafael , Chiquito Paulo , Ahmad Nameer Syed , Nietz Martin , Milne Gary
Published: April 2023

While additive manufacturing (AM) of metallic materials (commonly known as metal 3D printing) has greatly advanced in the aerospace and medical industries in recent years, the oil & gas sector still lags in adopting the technology. One aspect that plays a key role in this scenario, especially for subsea components, is the robust set of requirements. Despite recent progress made via joint industrial projects (JIP) to establish an internationally acceptable framework for AM applications, there are still issues that need to be addressed to fully take advantage of what the technology has to offer. One of the challenges is selecting the most appropriate parts. The objective of this work, therefore, is to analyze the portfolio of an oil & gas company to identify opportunities and select one metallic subsea component that is more suitable to be manufactured using laser-based powder bed fusion (LPBF), an AM technology with a high degree of maturity and widespread industrial use. Through a program designed to identify best uses of AM and to accelerate its application, a multidisciplinary team of engineers, product managers and designers teamed up with AM experts to conduct high-level assessment and detailed evaluation of the portfolio to identify the best candidates considering both technical and economic criteria. The main contribution of this study is the generation of data that can lead to a better understanding of the applicability of AM in the oil and gas industry, particularly in subsea applications. The results obtained can also guide future developments aimed at integrating AM into the oil & gas production chain.
Time Series Data Analysis with Recurrent Neural Network for Early Kick Detection
Authors: Wang Junzhe , Ozbayoglu Evren , Baldino Silvio , Liu Yaxin , Zheng Danzhu
Published: April 2023

Fast and accurate kick detection during drilling operations is critical to ensure drilling safety and reduce non-productive time. Over the years, the industry has taken various approaches to address this problem. However, due to the complexity of the influx process, the problem of slow detection speed and high false detection rate still exists. While many recent works of literature have attempted to solve the influx detection problem with machine learning algorithms, only a few of them have considered the time series information in real-time drilling data. Since there may be lags of unknown duration between different drilling parameters, a properly designed time series analysis model may be able to capture their relationships and make reasonable predictions. Recurrent Neural Network with long short-term memory (RNN-LSTM) architecture is a deep learning algorithm capable of making predictions based on historical time series data. Previous studies have shown that the RNN-LSTM algorithms can be applied to real-time drilling data to reasonably predict the trends of a segment of drilling data such as the total mud pit volume. In this paper, several sensitive influx indicators are separately predicted by completely independent RNN-LSTM models based on different sets of real-time drilling parameters. These models run as ensemble learning models to continuously predict influx indicators. Then, the prediction results will be quantified, and the probability of kicks will be calculated based on the different weights for each indicator. The proposed model is tested on field data in parallel with some common kick detection models and the performance is analyzed. It is concluded that the proposed model can perform accurate influx detection and outperform some common methods in the industry in terms of detection speed.
Importance of Flexible Structure Modeling of a Floating Wind Platform
Authors: Shi Yu , Yang Zhiyong , Bian Xiaoqiang
Published: April 2023

Recently, the ultra large wind turbines push floating wind platform’s size to a gigantic scale. The most recent 15MW wind turbine brings a lot of challenges to the floating structure design. Rigid body assumptions of the floating body and wind turbine tower may not be valid for such a large scale. Flexible body modeling of these large floating wind platforms allows the consideration of flexibility of the structures and results in a more accurate prediction of the design loads and the structure behavior. In this case study, we used a generic floating 15MW wind turbine model similar to UMaine 15MW wind turbine semisubmersible and a patented PyraWind™ 15MW wind turbine platform for a comparative study. For each of the two platforms, an OrcaFlex model with flexible body assumption is compared with an OrcaFlex model with rigid body assumption. The global performance and design loads of the two models are compared in detail. For different hull structures, due to the differences in the rigidity of the supporting structure, there is a difference in the tower behavior with or without flexible body modeling. This paper lays the groundwork for future research on flexible body modeling in the design of floating offshore wind turbines (FOWT).
Case Study: Effective and Economical Approach to Prevent Scale Formation Using Scale Inhibitor Squeeze into Reservoir
Authors: Lim Ann Jie , De Cruz Abigail Lian , Koyyalamudi Lakshmi Narayana , Ismail Mohd Syahezat , Khairudin Azri , Mohd Nawi Mohd Shakir , Isrofeil Izyan Haziqah , Zulkafli Luqman Hakim , M Adib M Syamil , Mohamed Arsyamimi
Published: April 2023

Producing wells in Field T, Malaysia offshore have faced significant production impairment due to deposition of calcite and barite scale in the tubing and reservoir. A proactive approach is strategized to inhibit the scale formation along the inner wall of production tubing and reservoir through a scale inhibitor squeeze (SISQ) treatment with a lifespan of 2 years. The main objective of this approach is to eliminate the need of frequent stimulation jobs to maintain the production.

Several attempts of scale inhibitor pumping in the past had been applied in the operator's production fields with different scale inhibitor (SI) formulations. However, some of the SISQ jobs were unsuccessful meanwhile some did not meet the treatment life targeted. A Root Cause Failure Analysis (RCFA) was conducted and the best practices and recommendations from the previous scale treatments were incorporated into this scale inhibitor squeeze treatment while the lessons learnt were implemented to prevent reoccurrence of unwanted events.

In the past, most of the failed acidizing and SISQ jobs were caused by misdiagnosis of the root cause of production drop in wells, causing wrong selection of candidates right from the beginning. Another cause is the reaction between the chemical and existing scale in the tubing wall that resulted in the disintegration of the deposits, which subsequently block the flow of the well. There were also instances where coreflooding tests were not conducted due to unavailability of core samples. From the past failure contributors, the best practice proposed is to initiate any scale inhibition program by determining the correct root cause of production drop and to proceed with remedying the existing scale buildup. Examples of the solutions are through scale clean out, acidizing or workover before implementing a prevention solution such as SISQ. During the chemical selection stage, scale inhibitors should be selected based on a series of lab tests to study the performance of scale inhibitors, potential of damage formation, scale inhibitor retention core flood analysis, scale inhibitor thermal stability and fluids compatibility.

Both wells B15 and D04 SS on which the SISQ jobs were conducted after acidizing job, have until now sustained their production. The MIC is well above 5 ppm target although approaching the end of 2-year treatment life. The Multifinger Imaging Tool (MIT) run downhole after one and a half years also indicated insignificant scale buildup on tubing wall. Permanent downhole gauge flowing pressure is also stable indicating no severe skin buildup. The produced water ions data, however, is insufficient to provide a view on the upward or downward trend of the scaling ions. In future replications, produced water ions sampling frequency should be increased.