bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reservoir Souring Study for De-Risking A Deep Water Subsea Green Field Development
Authors: Kamarul Zaman Nur Hazrina , Johar Zurita , A Salam Irzie Hani Bt A Salam , Sahrudin M Kamal B Sahrudin , A Raub M Razib , Foo Mei Fen 
Published: October 2022

Abstract
The paper discusses on reservoir souring study in a deep water subsea green field as a result of seawater injection. The objectives are to determine likelihood, timing of reservoir souring to happen and amount of expected produced H2S. Offshore deep water development involves considerable CAPEX investment hence reservoir souring requires to be assessed in order to make techno-commercial judgement involving formulating the field development plan, upfront identification of prevention & mitigation strategy, operating strategy and project economics.
The study started by performing data gathering involving among others field information, PVT, mineralogy, water analysis data, and production and injection profile. Subsequently, 2D reservoir modelling and 3D reservoir modelling was built. Sensitivities cases were run by varying the injection rate, nutrient loading, rock abstraction capacity, sulphate content, injection temperature and bacteria growth time. This is followed by sensitivity analyses for mitigation options using biocide injection, nitrate injection, H2S scavenging and sulphate removal in the field. Based on the results obtained, prevention and mitigation strategy has been evaluated and ranked followed by comparison with nearby analogue fields.
The modelling results of all scenarios indicate that reservoir souring will happen in the field and beyond HSE safety limit. For some scenarios, the H2S partial pressure exceeds NACE limit before end of field life, hence requiring team to re-evaluate material selection options. Water injection rate and rock abstraction capacity have the largest impact to the H2S breakthrough time. Sensitivity analyses for mitigation options have been conducted based on consideration of having options of biocide injection, nitrate injection, H2S scavenging and sulphate removal in the field. Biocide injection does not have considerable effects on H2S level. Nitrate injection only partially reduces H2S generation mainly due to high nutrient content in the reservoir and high sulphate content in the injected seawater. On the other hand, sulphate removal analyses indicate its effectiveness in preventing reservoir from becoming sour. The outcome of the study is then incorporated in the field development plan and operating strategy.
The paper highlighted comprehensive step by step approach to understand reservoir souring potential in a deep water development via 2D and 3D modelling approach. This can be included as an important procedure in field development especially involving high CAPEX development whereby critical decision making need to be made upfront. In addition, benchmarking, and learnings from nearby deep water fields help to identify best preventive and remedial option for reservoir souring.
Near-Wellbore Damage Associated with Formation Dry-Out and Fines Migration During CO2 Injection
Authors: Alchin Liam , Lymn Andre , Russell Thomas , Badalyan Alexander , Bedrikovetsky Pavel , Zeinijahromi Abbas 
Published: October 2022

Abstract
One of the key parameters for subsurface CO2 storage in well injectivity. There are multiple factors that can affect injection rate including formation dry-out, fines migration, and salt precipitation that can increase or decrease the injectivity. In this study, we experimentally investigated the cumulative effect of rock drying-out and fines migration on well injectivity for a formation in the Cooper – Eromanga Basin, South Australia.
Four core plugs with a range of clay content and permeability were chosen from the formation. Each core was fully saturated with artificially made formation water to measure initial permeability. The core samples were then subjected to a constant flow of gas (air or CO2) at reservoir pressure for up to 185,000 PVI. The effluent fluid was sampled continuously to measure the concentration of solid particles produced from the core during gas injection. The tests were followed by injection of formation water to eliminate the salt precipitation effect and then DI water to identify the maximum possible formation damage in each core sample.
Overall injectivity increased significantly during continuous injection of CO2or air into fully saturated core samples despite permeability damage due to fines migration. Fines migration was observed during gas injection, resulting in a pressure drop increase across the cores and fine release at the core outlet. 30-60% reduction of core permeabilities were observed during connate water evaporation. The damaging effect of fines migration on injection rate was negligible compared to 4-30 times pressure drop decrease due to reduction in liquid saturation.
Alleviating Directional Well Trajectory Problems via Data Analytics
Authors: Clayton Luke Michael , Lee Ming Hwa , Salmachi Alireza 
Published: October 2022

Abstract
A consistent leading cause of drilling non-productive time (NPT) is the inability to steer the planned well trajectory trouble-free. Separate from downhole tool and drill bit failures, an unplanned trip to change the Bottom Hole Assembly (BHA) is required for up to one in every seven drilling runs. Root cause analyses indicate potentially a quarter of all drilling NPT has poor planning or field execution as the failure mechanism, signifying scope for improvement. This paper aims to help guide optimal selection of RSS/motor and bit, to ensure challenging wellpaths will be achieved with minimal NPT associated with BHA trips.
Directional drilling analysis typically compares dogleg severity (DLS) for planned and actual trajectory. This metric is fundamentally direction-blind; absolute tortuosity is represented whether planned or unintentional. Without full context, DLS analysis can mask many steering issues. Typically, industry software does not measure how closely the steering inputs match their anticipated responses during a run. Strategic management and identification of zones with erratic toolface control, or strong formation/BHA tendencies is critical.
The proposed ‘derived steering’ analytics method was applied to plan demanding 3D trajectories for an Extended Reach offshore campaign in Australia. Existing minimum curvature equations were repurposed to plot previous runs steering inputs and then infer efficiencies for each formation. Supervision was essential to counteract strong consistent right-hand BHA walk tendency for all the variety of wells studied. Multiple NPT events on previous campaigns had resulted from poor steering response in the shallow interbedded geology.
In view of quantifiable field-specific risks, wellplans were refined to minimize tortuosity and maximize the design safety factor. The combination of highest anticipated dogleg response rotary steerable technology and bit selection was selected for steering assurance. Modelled tendencies per lithology were shared with wellsite supervisors, and recent drilling results essentially mimicked data analytics.
Others operating in this field in the 21st century had drilled total meterage of 36,740m MD from 83 runs. Bit Gradings showed two ‘Lost in Holes’, one ‘Drill String Failure’, six trips for ‘Downhole Tool Failures’, seven for ‘Penetration Rate’, six to ‘Change BHA’, two for ‘Hole Problems’ and one for ‘Downhole Motor Failure’. The current campaign's improved directional drilling offset analysis contributed towards significant avoidance of well delivery NPT to drill 28,061m in 34 runs. No trips were required to change BHA or bit because of inability to follow the trajectory, and field teams were able to pre-empt lithology-specific challenges.
A New Sustainable Self-Healing System; Autonomous Repair for Glass Reinforced Epoxy Liner for Water Injector Tubing
Authors: Aba NorFarah Diana , Samsudin Mohd Shamsul Farid , Zakaria Muzdalifah , Mohammed Nor Azmi , Varley Russell , Zhang Jane 
Published: October 2022

Abstract
Often in the water injector (WI) system with liners, the "unseen" damage such as micro scratch is very difficult to be detected, and these micro scratches, when not detected will eventually become a major damage. Employing self-healing technology in the liner will ensure that the minor damage will be healed autonomously during operation, subsequently preventing further major damage. The in-situ healing of the damages is one of the amazing criteria offered by this technology. The integrity of the WI system is eventually assured, prolonging the service life of the materials and avoiding unnecessary expensive inspection and maintenance. In this present work, self-healing technology has been developed for the epoxy-based materials used in glass-reinforced (GRE) liner system for WI tubing. The novel self-healing additives were synthesized using a facile synthesis method and have been proven to be able to potentially replace the expensive rare-earth based catalyst, hence making the commercial step viable.
The metal-organic frameworks (MOFs) microcapsules self-healing in the epoxy-based liner system demonstrated successful autonomous healing efficiency at elevated temperatures as examined using a 3D-profilometer, with a healing efficiency of more than 80%. The system with the self-healing additives was able to recover the barrier performance of the liner, up to 98% efficiency as shown by the electrochemical impedance spectroscopy (EIS) assessment. In addition to that, within 2 hours of healing activation by temperature, the samples with the self-healing additives were able to autonomously heal, reaching more than 50% healing efficiency. Moreover, this self-healing system was able to heal a damage width of up to 700µm, for more than 80% healing efficiency. It is worth mentioning that the healing ability remained functional even though the samples had been exposed to harsh conditions for 1000 hours. The healing agent particularly contained in the microcapsules remains intact and stable throughout the stability study, hence suggesting a robust self-healing system. This finding shows the possibility of this technology to provide a sustainable production of self-healing additives for a liner in water injector's well, hence potentially improving the integrity of the materials.
Applying Data Analytics & Machine Learning Methods for Recovery Factor Prediction and Uncertainty Modelling
Authors: Kumar Munish , Swaminathan Kanna , Rusli Aizat , Thomas-Hy Abel 
Published: October 2022

Abstract
The estimation of recoverable hydrocarbons, or field recovery factor (RF), is a critical process for Oil and Gas (O&G) companies to plan and optimise field development, manage ongoing production and identify profitable investments amongst other technical and commercial decisions. However, RF remains one of the greatest uncertainties in O&G projects.
The difficulty in RF prediction arises due to the number of variables affecting the recovery from a reservoir. These includes variables that are both uncertain and beyond the control of O&G operators, such as fluid flow in microscopic pores, as a function of fluid and rock properties, and variables which are engineering design based, such as completion methods, secondary and tertiary recovery mechanisms. In early field life, insufficient production data coupled with subsurface uncertainty makes RF prediction uncertain, and it is often the experience of the operator combined with analogue studies that is used to determine RF. However, there may be instances where operators may have insufficient data from analogue fields to properly capture the uncertainty in the RF range.
Utilising techniques of big data manipulation and machine learning (ML), two open-source, United States based data sets are (a) deconstructed to identify the key variables impacting the ultimate recovery of a field, and (b) used to create a ML model to predict the RF based on these key variables. These two datasets (the onshore Tertiary Oil Recovery System (TORIS), and the offshore Gulf of Mexico (GOM)) consist of over 1,000,000 real world data points.
Employing a low code environment, we test the predictive ability of 20 different ML algorithms by comparing predictive error. Decision tree type models (Random Forest and Category Boosting) show the best results. The paper shows comparison to a distance based (K Neighbour) model as well.
The work aims to show that not all variables influence RF equally and that any ML model should therefore be built with variables that have the greatest influence on RF yet have the lowest pairwise correlation. The influence of these input variables differs, depending on the implemented ML model.
The paper demonstrates the predictive ability of ML models is strongly dependent on the input dataset. Predicting the recovery factor of fields within the TORIS and GOM databases, the R2 values are 0.81 and 0.88 respectively. Testing the algorithm on three additional fields outside of the two datasets, and in different geological provinces showed errors of up to 10-15%.
Understanding Source, Genesis and Spatio-Temporal Distribution of CO2 off the coast of Sarawak, Offshore Malaysia : An Integrated Approach
Authors: Masoudi Rahim , Nayak Satyabrata , Panting Alexander Tarang Patrick , B M Diah M Amri , Shah Jamari M , Ismail Ts. Hijreen Bt , Hoesni M Jamaal , Razak M Shafiq , Ahmad Nur Asyikin 
Published: October 2022

Abstract
A regional CO2 concentration and risk maps have been generated for the Sarawak Basin using an integrated G&G and model-based approach. Detailed petroleum system modeling with number of scenarios encompassing critical parameter uncertainties is carried out. The extensive 3D petroleum system model carried out is critical in understanding generation, migration of hydrocarbon and CO2 as well as inter relation between the above two. This approach has significant advantage over traditional geostatistical method in extrapolation of observed data to predict CO2 concentration away from the control points. Apart from basin model detailed analysis of presence of CO2 in relation to temperature, tectonic features (faults lineaments) nature of the trap, pore pressure are carried out to identify and validate possible CO2 sources. This comprehensive study is the primary building block for generating a predictive model for CO2 distribution and possible adaptation in the prediction of other contaminants in the region.
Numerical Modeling of Hydrate Particle Deposition in Pipes With Diameter Reduction
Authors: Wang Zhiyuan , Ma Nan , Zhang Jianbo , Pei Jihao , Tong Shikun , Sun Baojiang 
Published: October 2022

SummaryHigh-pressure and low-temperature conditions in deepwater gas production and transportation may cause severe hydrate blockage. At present, the research on hydrate migration and deposition primarily focuses on through-diameter pipes, and there are very few related studies on pipes with diameter reduction. In this study, we used the computational fluid dynamics (CFD)-discrete element coupling method. Considering the interaction between hydrate particles, particles and the pipe wall, and particles and fluid, this study establishes a 3D pipe model under different reducing ratios, simulates the migration and deposition law, and reveals the migration and deposition mechanism of hydrate particles at the reduced diameter of pipes. The results revealed that the reduced diameter affected the flow field distribution, led to the emergence of an eddy zone, which strongly hindered migration, and quickly led to the deposition of hydrate particles. Additionally, this study also investigated the effects of gas velocity, reducing ratio, particle diameter, particle generation rate, and flow direction on the deposition efficiency of hydrate particles at the reduced diameters of pipes. Finally, the calculation formula for the eddy zone at the reduced diameter of the pipe was obtained via regression. The equivalent deposition ratio (EDR*) was proposed as a new parameter to characterize the influence of reduced diameter on hydrate particle deposition and provides a new correlation calculation method for it. The results of this study can provide a valuable reference for the efficient control and design of hydrates.
Challenges in Facilitating Online Teaching for Secondary Education during the Covid-19 Pandemic, based on a case study in Sri Lanka.
Authors: de Silva Arosha , de Silva Arosha 
Published: October 2022

Abstract

This research aims to evaluate the challenges in facilitating online teaching for secondary education during the Covid-19 pandemic based on a case study in the western province of Sri Lanka. With the pandemic, teachers had to face many challenges concerning online teaching, as they were unprepared for the remote teaching process that was to follow. For this research, teachers were able to give an account of their experiences, challengers and the sacrifices that had to be made in adapting to this new method of teaching. A mixed method of data collection and analysis was used in this research, as both quantitative and qualitative methods in combination would provide a better understanding of research problem enhancing the validity of the results. Through the findings of this research, it was revealed thatmost schools and its teachers had embraced online teaching in the midst of the many challengers during Covid-19. Thereby it is vital that measures are taken to overcome and to mitigate the effects these challenges faced in online teaching, making it possible for teachers to deliver an online education for students that is on par with other technologically advanced education system.
Does economic freedom improve FDI inflow in Sub-Saharan Africa?
Authors: Dia Ibrahima , Ondoa Henri Atangana 
Published: October 2022

Abstract

This study aims to examine the effect of economic freedom on foreign direct investment (FDI) in Sub-Saharan Africa (SSA). This study focuses on the SSA region and takes into account the effect of the five components of the Fraser Institute's economic freedom index on FDI. To this end, we employed a panel data analysis in 37 countries over the period 2000-2018 by using two-stage least squares regression (2SLS) to deal with the endogeneity issue. We measure FDI by the net annual flow of inward FDI as a percentage of GDP in SSA. We find that economic freedom, legal system and security of property rights, freedom to trade internationally, and regulation of business, labour and credit markets encourage FDI flow in SSA. However, the size of government and sound money have positive sign but it is insignificant. The results are robust when we replaced the dependent variable FDI inflow with FDI inflow per capita.
JEL classifications : P16, O43, F21, F23, O55,
Acknowledging Indigenous-specific racism within Canadian Nursing: An Integrative Review
Authors: Walizada Astera , Graham Holly , de Padua Anthony 
Published: October 2022

Abstract

Background
Historically, nurses and the nursing discipline have participated in perpetuating colonial harms and assimilative policies towards the Indigenous peoples of Canada. Thus, the nursing profession has been complacent and at times complicit in their actions that have resulted in Indigenous-specific racism. The purpose of the paper is to highlight how Canadian nursing practice is contributing to ongoing colonial policies and how this perpetuates the current Indigenous health disparities, and to offer suggestions to be integrated into nursing practice.
Method
Whittemore and Knafl's integrative review methodology was used for this review. Sixteen sources fitting predetermined criteria found on the databases CINAHL, Medline, ProQuest Nursing & Allied Health Premium, Google Scholar, and Google were assessed and analyzed.
Results
There are multiple ways nursing is currently involved in colonial harms and contributing to Indigenous-specific racism in healthcare. The suggested interventions to address these harms are identified and grouped into themes. They are Indigenous-specific racism in nursing academia, Indigenous-specific racism in nursing practice, and organizational and systemic recommendations.
Conclusion
Despite progress and efforts made by nursing, the current health care system continues to reflect the legacy of colonialism for Indigenous peoples. Therefore, the nursing discipline needs to re-examine current nursing practice and begin a systemic approach to dismantle Indigenous-specific racism.
Time Series Modeling of Road Traffic Crashes in Himalayan States of India
Authors: Yadav Bibek , Hossain Moazzem 
Published: October 2022

Abstract

Road Traffic Accidents in India are increasing at a high rate due to the large percentage of slow-moving vehicles and the absence of proper traffic management systems. In hilly regions, the road accident scenario is further gloomy due to narrow roads, steep slopes, hairpin bends, and a valley or river on one side of the roads. Various elements contribute to accidents in a hilly location, and it's important to understand how these factors interact. Road crash time forecasting was done for accidents that took over three years. Auto-regressive Integrated Moving Averages (ARIMA) models were applied to the collected data, and an Eighty-four (84) month forecast was based made based on the fitted models. Based on the results of this study, the rate of road accidents is expected to decrease in Nagaland and Meghalaya, while increases in Sikkim and Manipur are constant for at least the next seven years. It was found that the incidence of road accidents in Nagaland, Manipur, Meghalaya, Sikkim, and Jammu &Kashmir can be fitted ARIMA (0,1,1) (1,1,0) [12], ARIMA (0,1,1) (0,1,0) [12], ARIMA (0,1,1) (0,1,0) [12], ARIMA (0,1,1) (0,1,0) [12] and (0,1,1) (0,1,0) [12] respectively. Remedial measures are suggested to implement improved policies and close monitoring of road traffic systems. This study provides information that could be useful for determining road accident rates in those states and would be used for providing important information to extend awareness concerning road safety.
All-optical organic photochemical integrated nanophotonic memory: lossless, continuously-tunable, non-volatile
Authors: Bilodeau Simon , Doris Eli , Wisch Jesse , Gui Manting , Rand Barry , Shastri Bhavin , Prucnal Paul 
Published: October 2022

Abstract
Controlling changes in the optical properties of photonic devices allows photonic integrated circuits (PICs) to perform useful functions, leading to a breadth of applications in communications, computing, and sensing. Many mechanisms to change optical properties exist, but few allow doing so in a reversible, non-volatile manner. This leads to power inefficiency in reconfigurable circuits and requires external memory elements. In this work, we propose and experimentally demonstrate reversible, non-volatile phase actuation of a silicon nitride PIC with thermally-stable photochromic organic molecules. The use of a high-core-index platform allows, for the first time, the photochemical actuation of a planar-resonator-based photonic memory unit, which enables high performance and permits integrated spectroscopic analysis. We show novel properties of this all-optical memory for a silicon photonics platform, including complete transparency in the optical C-band, as well as first-order photokinetics of the photoconversion that lead to bidirectional scalable switching rates and continuous tuning. Such features are critical for memories in analog applications, such as quantum, microwave, and neuromorphic photonics, where low loss and precision are paramount.