bluuebunny/crossref_metadata_2025 huggingface dataset:
Are Process Safety Standards and Practices Ready for the Energy Transition?
Authors: Scanlon M. , Woodford G
Published: September 2024

Globally, nations and organisations are setting targets to achieve net zero carbon dioxide equivalent (CO2e) emissions (NZE); for many, the target is to reach NZE by 2050. So, in just over 25 years, those nations and organisations need to rethink and deliver on how they generate, store, transmit, distribute and use energy.

Delivering a paradigm-shifted energy system that will look different from the one that exists in the early 2020s is the challenge of our time. For comparison, the first industrial revolution that introduced steam and water-power took over a century. If we look forward to 2050, both crude oil and natural gas are expected to remain a significant energy vector, although their demand is forecast to decline (IEA (2023)). There will be other energy vectors and multiple pathways, from hydrogen to renewable crudes, as well as increased electrification across the value chain. However, if we reflect on the changes that have occurred in the energy industry over the last 25 years, such as the rise of shale gas, liquefied natural gas (LNG), biofuels and electrification, these have been at a much smaller scale, more localised, and not necessarily impacting the same aspect of the energy system.

The energy transition journey towards net zero is expected to be chaotic as the energy system is disrupted with multiple opportunities being adopted and impacts occurring in parallel. One can draw analogies with how peer-accepted science undergoes a paradigm shift when the status quo of knowledge becomes challenged, with a period of chaotic uncertainty until a new status quo is established. What is certain is that during the energy transition, the energy industry will undergo significant changes, which will require the industry to rapidly adapt to both technological advancements and the challenges posed by climate change. Initially, abatement is expected to use existing technologies combined with demand-side measures. Beyond 2030, abatement will require application of innovative technologies at scale, which introduces a need for management of change (MoC). Moreover, the pace of change will need to quicken, to deliver the required annual rate of transformation towards NZE and to achieve a 1.5 °C global temperature rise above pre-industrial levels.
Developing Workforce Involvement in Sustainability: Local Community Initiative Case Studies
Authors: Lerale J. , Jovaisaite K. , BellasBourdin C. , Imran M. , Akhmadieva Z. , Burlacu E.
Published: September 2024

To support a global technology company’s sustainability objectives, an internal business group within the company has concentrated its sustainability efforts on providing impactful and long-lasting initiatives to benefit local communities. The paper provides case studies of country-specific voluntary sustainability teams of the business group that have been undertaken to benefit local communities and company priorities in Asia, Europe and the Middle East. The paper also describes how a framework was developed to guide teams of employee volunteers.

The first step in the process was to identify committed employee volunteers to lead local sustainability initiatives. The volunteers were provided with an initial framework and key directions to follow. A year after establishing the voluntary teams, new teams were provided with a comprehensive playbook which enabled the teams to deliver diverse projects faster and with higher impact.

Additionally, building diverse local teams ensured that a range of perspectives were reflected in the identification and prioritization of initiatives. To best serve the needs of the local communities, it was important to build long-term collaborations with non-governmental organizations (NGOs) relevant to the selected priorities.

The structured approach to sustainability initiatives helped the teams focus on actions that matter the most to local communities. This led to the establishment of long-lasting relationships with NGOs. Examples include supporting young individuals in foster care through skill-sharing sessions and internship opportunities within the company, supporting local community business enterprises, and providing science, technology, engineering, and mathematics (STEM) education opportunities for young people.

The engagement and enthusiasm of the employee volunteers have been maintained through observing the positive impact their efforts have made on the local communities, enabled by the clear impact-oriented guidance provided. Across several countries, this network of volunteers has onboarded almost 15% of the business group’s employees and their families to participate in sustainability actions, with over 40 initiatives completed in 2023.
Empowering Futures: Unveiling Indigenous Entrepreneurship Insights Through the Capability Lens for Social Development
Authors: Lovo Leslie
Published: September 2024

The paper aims to identify critical success factors through Amartya Sen’s Capability Approach perspective for indigenous entrepreneurship. By taking a closer look a case study of two rural initiatives in honey production and clothes sewing, it explores how improved capabilities correlate with positive social outcomes, arguing against cookie-cutter models for assessing community progress. The findings will allow to enhance strategic purpose of social investments, stakeholder engagement, and community value creation.
Screening Depleted Reservoirs and Aquifers for CO2 Geo-Sequestration, and Assessing Implications for Converting an Offshore Platform for Carbon Capture and Storage Project
Authors: Zeir A. , Aboelseoud M. A. , Mehrem M.
Published: September 2024

Re-using the depleted reservoirs for CO2 storage offers advantages over saline aquifers, as the geological characteristics required for CO2 storage have been pre-determined with high accuracy throughout the reservoir production life, plus a proof of secure containment. Additionally, re-using the production facilities and offshore platforms for the injection of CO2 would be economically and environmentally winning fact.

This paper is based on intensive bibliographic research related to challenges and concerns of CO2 storage in depleted oil and gas reservoirs, for the selection of the optimum solution for converting the offshore platform GREEN1 in the Adriatic Sea to be re-used instead of decommissioning. It also highlights the interactions between the reservoir parameters and the design of surface facilities. The design of all the upstream components, i.e., transportation pipeline diameter, compression capacity, and maximum allowable pressure is mainly based on the rock and fluid interactions in the reservoir porous media. Storage capacity has a pivotal role in the candidate sites screening process, accompanied by an economic feasibility study. CO2 storage capacity of ‘Porto Corsini Mare’ reservoir, as a candidate site for GREEN1, is estimated based on returning the depleted reservoir to its initial pressure before production.

A methodology for comparing and selecting suitable reservoirs and aquifers for CO2 geo-storage is introduced in this paper for the purpose of identifying the optimum storage site for GREEN1 platform. The screening criterion is divided into three main categories: storage capacity, injectivity, and containment, in a shape of logic flow charts with the relevant parameters to each category, in order to help analysts and decision makers identify and compare candidate sites for CO2 storage, so that they are easily able to exclude the unsuitable reservoirs and proceed with the right candidates for further economic and risk assessment studies.
Bouncing Back- KhPD's Story of Resilience and Recovery from the 2019 Attack
Authors: Alhamraa A. M. , Wadani H. S. , Saqer N. , Qahtani F. M. , Emre K.
Published: September 2024

The Khurais Central Processing Facility (CPF), a cornerstone of Saudi Aramco's oil production infrastructure, sufferred adron attack on September 14, 2019, causing significant damage, disrupting operations and posing a serious threat to the global oil supply. This incident tested the resilience and recovery capabilities of the Khurais Producing Department (KhPD) and Saudi Aramco at large.

This paper provides an overview of the recovery efforts at Khurais, focusing on emergency response, crisis recovery strategy, integration of IR 4.0 technologies, rapid production restoration, and innovative repair techniques. This paper includes insights and practical lessons for the Oil & Gas industry on managing crisis situations and ensuring operational resilience.

The Khurais oil field, one of the largest in the world, plays a crucial role in Saudi Arabia's oil production capacity. The facility's ability to produce 1.5 millions of barrels of oil per day makes it a vital asset in the global energy landscape. The attack tested Saudi Aramco's operational resilience and crisis management capabilities.
Implementation of a Management System to Mitigate Carbon Dioxide Emissions from Light Vehicles Transportation Through Improved Driving Behavior in the State of Kuwait
Authors: Al-Hadhrami B. M.
Published: September 2024

This study investigates the effects of improved driving behaviors on greenhouse gas (GHG) emissions reduction from light vehicles in Kuwait. There has been a steady increase in Greenhouse Gases (GHG) emission to the atmosphere globally since the industrial revolution. Human activities, such as the burning of fossil fuels, transportation, and changes in land use are major contributors to the increase in concentrations of atmospheric GHGs. According to the latest estimates, Kuwait being a major oil producing country, annual increase in GHG emissions has been recorded for the past two decades, with 21.2 MT per capita emitted in 2020, increased from 21.1 compared to 2019. Implementing practical and feasible reduction strategies to the significant emission contributors is essential. This study proposes a management system targeting the transportation sector through enhanced driving behaviors in a transportation fleet, using a monitoring hardware and software, to collect data from 25 light vehicles. To assess the solution's effectiveness, we compared pre- and post-intervention periods of fuel consumption in light vehicles through monitoring and enhancing the driving behavior variables, harsh acceleration, harsh braking, over-speeding, and idling, thus reducing carbon emissions that was determined based on the US EPA conversion factor. Our results show significant improvements in several key parameters, a 15% reduction in fuel consumption resulting in 15% and 18% carbon dioxide emissions (CO2) and cost reduction, respectively. This should represent huge environmental and economic benefit associated with the measures implemented. In the post-intervention phase, where controls and interventions were implemented to enhance drivers' behaviors, there was a significant reduction in idling hours, decreasing by 8,167.38 hours with a (P < 0.003). These results clearly illustrate the need for more stringent national regulations at improving driving behaviors, which not only contribute to environmental quality improvement but also offer substantial economic advantages.
Enhancing Workforce Wellbeing: Implementing A Global Mental Health First Aid Program
Authors: Fleming B. , Smith C. , Ackerman A. , O’Keeffe J.
Published: September 2024

This paper describes how a global energy technology company developed a mental health first aid (MHFA) program to provide workplace access to a trained mental health responder at the point of need and how this initiative also helps to raise awareness of the importance of good mental health in the workplace. The program complements the company’s existing Employee Assistance Program (EAP) and mirrors the provision of physical first aid response in the workplace.

The program uses an employee-volunteer approach, teaching individuals to recognize and respond to signs and symptoms of mental health concerns. Implementation included creating a role description for volunteer MHFAs and documenting responsibilities for employees, managers, human resources, health, safety and environment (HSE) and company medical professionals. Requirements included criteria for volunteer eligibility and sourcing of in-country and remote online training programs to meet national as well as company requirements. Existing national MHFA training providers were mapped and a six-step MHFA training and certification process was developed. A global web and mobile app were also developed to connect employees to the trained and certified MHFAs.

The MHFA program has been fully implemented in over 20% of the company’s operational locations and partially implemented in a further 50% of locations during the first year of program activity. Over 80% of the workforce is included and covered by the program. A diverse employee cohort volunteered to be trained to provide mental health first aid response. National resources and cultural factors influenced the speed of adoption and implementation. The workforce embraced the program, and, in many cases, it was observed being pulled by end users rather than pushed out as an HSE campaign. Legal liability concerns were addressed by clearly defining the scope and MHFA responsibilities, with additional education regarding the appropriate limits of mental health first aid provision in the workplace. To support the volunteers, a global network of MHFAs was established to share ideas and experiences as well as to provide support to grow the program.

The return on investment for this type of program includes likely improvements to morale, an enhanced culture of care and overall increased HSE engagement. From an organizational perspective, the program can help contribute to reduced medical leave in the workplace over time.
Oil and Chemical Mapping & Spill Risk Assessment for Offshore Vessels
Authors: Spingardi A. , Nunzi P. , Negoi R. , Flori L.
Published: September 2024

Spill Risk Assessment and Oil and Chemical Mapping methodology presented in this paper aims at creating a comprehensive reference document for each vessel where it is applied, containing information about the spill risk for the equipment on board and the conditions that may result in a spill to the environment. In this way appropriate mitigation measures can be identified, prioritized and implemented more effectively. This assessment system combines the experience of the relevant unit and on-site technicians with a methodical risk- assessment procedure, adding value to implemented risk mitigation measures.
Double Materiality Assessment, Implications for the Oil and Gas Sector
Authors: Dhodhi Gautam
Published: September 2024

The paper aims to discuss the concept of double materiality in sustainability reporting, including conducting double materiality assessments, highlighting the associated challenges, and summarizing current approaches for oil and gas companies. The increasing relevance of the materiality concept in non-financial disclosures has been promoted by various non-financial reporting frameworks and standards published by multiple stakeholders, including regulators globally. The paper aims to review the existing research and analysis conducted on non-financial disclosures of companies, including oil and gas, to evaluate the consistency regarding adopting double materiality in their sustainability disclosures. It outlines the challenges associated with recent assessment approaches due to the novelty of double materiality and highlights mitigation strategies based on the current sustainability disclosure landscape.

Double materiality is relatively new and open to a high degree of subjectivity and interpretation. The paper aims to provide a simplistic approach to understanding the applicability and maturity of the double materiality assessment process.
A Framework for Predicting Pandemic Severity and Mortality Using Generative AI and LLMs
Authors: Tharayil Sarafudheen M. , Alnajashi Arwa , Al-Ahamri Abdullah , Shahada Marwa
Published: September 2024

This research work introduces a comprehensive framework for pandemic severity and mortality prediction. The study achieves two key objectives. Firstly, a robust model is developed for accurate mortality prediction using deep learning mechanisms, leveraging variants like Convolutional Neural Networks, Recurrent Neural Networks, and Transformers which learn complex relationships from clinical and demographic data, enabling timely risk stratification. Secondly, enhancing model explainability through large language models (LLMs) for explainability. Integrating LLMs provides natural language explanations alongside predictions. Transparency is enhanced by describing factors influencing severity and mortality, bolstered by confidence scores and uncertainty estimates. The methodology involves data preprocessing, fine-tuning LLMs, model development using deep learning algorithms, evaluation of models using performance metrics, and qualitative analysis of LLM results via user surveys. The generative AI model emerges as a valuable tool for pandemic management, adaptable beyond COVID-19. The novelty of this study lies in three aspects. Firstly, proposing and implementing a pandemic severity and mortality prediction framework using neural networks and deep learning. Secondly, introducing natural language explanations using LLMs alongside predictions, enhancing transparency, and thirdly demonstrating the effectiveness of the generative AI model across various pandemic-causing viruses, facilitated by a generic and adaptable data schema and model architecture.
Leveraging RTLS Applications for Enhanced Safety and Efficiency in Oil and Gas Organizations
Authors: Daher Elie , Schoeib Sameh
Published: September 2024

Real-Time Location Systems (RTLS) have emerged as invaluable tools for enhancing safety and efficiency in the operations of oil and gas organizations. This abstract investigates the various applications of RTLS technology within the industry, highlighting its transformative impact on safety protocols and operational efficiency.

With a focus on safety, RTLS facilitates real-time monitoring and tracking of personnel and assets, thereby mitigating potential hazards and enhancing emergency response capabilities. Through the precise location data provided by RTLS, organizations can swiftly identify personnel in distress or evacuate personnel from hazardous areas, minimizing the risk of accidents and injuries. Additionally, RTLS enables proactive safety measures by providing insights into worker behavior and identifying patterns that could indicate potential safety risks.

Moreover, RTLS plays a pivotal role in optimizing operational efficiency within oil and gas organizations. By accurately tracking the movement of assets, equipment, and personnel, RTLS enables organizations to streamline logistics, minimize downtime, and optimize resource allocation. Real-time data provided by RTLS systems allows for better coordination of operations, reducing bottlenecks and improving overall productivity. Furthermore, RTLS facilitates predictive maintenance by monitoring the condition and usage of equipment, thereby reducing the likelihood of unexpected failures and maximizing asset uptime.

In conclusion, the adoption of RTLS applications represents a paradigm shift in safety and efficiency enhancement strategies within the oil and gas industry. By leveraging RTLS technology, organizations can proactively address safety concerns, optimize operational processes, and ultimately achieve higher levels of safety and efficiency. Embracing RTLS not only mitigates risks and enhances productivity but also underscores the industry's commitment to embracing innovative solutions for sustainable growth and operational excellence.
Developing Strategic Assessment on Methane Emission Management in PERTAMINA
Authors: Perdhani R. , Yuanda T. R. , Suripno S. , Permadi J. , Darmawan R.
Published: September 2024

Methane emissions from oil and gas operations present an urgent climate risk and a critical process safety event. Therefore, PERTAMINA has identified and screened considerable methane emissions sources from its assets. However, methane mitigation on the sources will cause potential gaps regarding the credible methane emission data. To address those gaps and to acknowledge the OGMP 2.0 reporting requirements, PERTAMINA is conducting strategic assessments combining methane emission quantification methodologies comparison and methane emissions measurement activities. Preparing for strategic methane mitigation opportunities, PERTAMINA has joined OGMP 2.0. Nonetheless, there are challenges in developing robust methane emission management to meet the Gold Standard reporting standard. To tackle the challenges, the strategic assessments are performed by PERTAMINA. First, the performance of current emissions quantification methodologies was compared with the desired performance of OGMP 2.0 to be able to assess the gap and develop the methane emission management roadmap. Afterward, the methane emissions detection and quantification campaigns have been performed to recognize and characterize methane emissions from PERTAMINA's oil and gas value chain. The gap assessment consists of OGMP 2.0 frameworks acknowledgement, OGMP 2.0 requirements and existing quantification methodologies alignment, and current methodologies improvement. The alignment of OGMP 2.0's methane emission source and category was conducted to identify any potential issue and to address any key finding. Furthermore, technical improvements were made to comply with certain levels of OGMP 2.0 reporting. Based on the gap assessment results, the current methane emission situation is assessed to be able to develop the roadmap from a credible baseline, and reduction target is established to understand the OGMP 2.0 level that will be achieved. Meanwhile, the methane emission detection and quantification pilot project has been carried out since 2023 at selected business subsidiaries. The bottom-up measurement one is the most frequently used technology during the study period. The novelty of these strategic assessments is in the ability to initiate robust and comprehensive methane emission management in PERTAMINA, to provide understanding on how to comply to OGMP 2.0's Gold Standard reporting requirements, and to share similar objectives with the Indonesian Government's methane reduction plan and ambition in the Global Methane Pledge.
Structural Understanding Underlying the Safety Culture Ladder
Authors: Hudson T. G. L. , Hudson P. A. R. , Hudson P. T. W.
Published: September 2024

OBJECTIVES/SCOPE

The paper discusses the underlying structures driving the management of risk in different safety cultures as described by the Hudson Safety Culture Ladder. The paper links different causal models employed by organisations to the stages in the ladder and uses a case study to illustrate the fundamental concepts.

METHODS PROCEDURES, PROCESS

The management of risk within organisations is driven by the underlying causal models that the organisations management uses to make sense of how the world works. The paper considers management actions and activities in the light of this. Taking these insights, the paper then maps the concepts onto the safety culture ladder descriptions as contained in the Hearts and Minds Understanding Your Culture framework.

The paper then extends the concepts into novel dimensions to demonstrate the applicability of the findings and methods.

RESULTS, OBSERVATIONS, CONCLUSIONS

The Hudson Safety Culture Ladder describes four levels of safety culture. Each of these cultures are shown to be the observation of different structural approaches to the risks that the culture is exposed to. These approaches are linked to the breadth and complexity of the risk spaces the organisations operate in.

This means that organisations can tailor their cultures to the operational reality they operate in. This enables efficient allocation of resources.

A simple narrow risk space only requires a culture to be Reactive, using an Unstructured approach to failures to fix problems as they arise.

A broader complicated risk space requires a culture to be Calculative, taking a Structured approach to ensure that learnings from failures are applied across the entire organisation

Complex risk spaces require a Proactive culture that is not only Structured, but also sensitive to the operational context.

A highly dynamic complex risk space requires a Generative culture that is Structured, Operationally Context sensitive, and Internally Context sensitive.

The paper uses these concepts in a case study with a world class aviation engine MRO to help illustrate.

Please explain how this paper will present novel (new) or additive information to the existing body of literature that can be of benefit to a practicing engineer.

The safety culture of an organisation is not a monolith, but should be considered in the context of the risk spaces it operates in. The concepts in this paper can help fine tune cultural understanding and improvement activities.
Integrated, Remote, Digital – Confined Space Monitoring in IR4
Authors: Daher Elie , Schoeib Sameh
Published: September 2024

Confined space work is one of the most hazardous jobs in a turnaround. In recent years, confined space monitoring has been revolutionized. Safety watch personnel positioned outside the confined spaces have been replaced by qualified technicians who remotely monitor multiple confined spaces. These technicians can directly communicate with the confined space workers and have clear A/V communications with them.

While the current remote monitoring system is a step in the right direction, there are certain safety challenges that persist. One such challenge, for example, is that you can currently only monitor workers through A/V cameras. While workers may look fine physically, in emergencies like gas leaks, tracking internal vitals like heart rate and breathing rate can alert the command center to a potential medical emergency. The affected worker can be taken out of the confined space for appropriate treatment and rest preventing an incident within the Confined Space.

Another challenge with the current Confined Space Monitoring systems is that they are monitored by technicians who are monitoring multiple confined spaces at the same time. No matter how experienced and well trained the technicians are, they are still human and might miss something. This is where AI comes in. Enhancing the current confined space monitoring solutions with AI technology like Computer Vision enables improved PPE compliance, fall alerts etc enhancing safety of the workers within confined spaces.

Lastly, one other challenge of the current confined space monitoring systems is that they require a command center which relies on the power and network connectivity available at the plant it is situated in. This results in certain limitations where there are space constraints and/ or connectivity issues. For these situations, the new confined space monitoring solution has a ‘light’ version which does not require a full command center set up. The ‘light’ version can be installed on a laptop and managed by a technician from anywhere on or off the site. This reduces its footprint and can work independently on battery power.

This paper looks in detail at the technical advances of the new digital confined spaces monitoring technology and how it maximizes worker safety and efficiency.
A Comprehensive Life Cycle Assessment of Hydraulic Fracturing
Authors: Khan Abdul Muqtadir , Anderson Christine , Prabhu Rasika , Beletskaya Anna , Kuan Pearl , Danican Samuel , Mostowfi Farshid
Published: September 2024

The oil and gas industry has been taking steps to achieve sustainable growth. Most E&P companies have declared their commitment to a carbon-neutral future. The first step in realizing this goal is to identify high-intensity operations, such as unconventional hydraulic fracturing and reduce those emissions. Therefore, the primary objective of this work is to quantify the main sources of emissions in the hydraulic fracturing value chain and identify technologies that could drastically reduce those emissions.

The main purpose of this work is to identify nearly all sources of emissions and the scale of their impact. Once the main emission sources are identified in the entire unconventional fracturing chain, we then focus on technologies that enable significant emission reduction. We employed qualitative and quantitative analysis to assess the emissions impact of diesel engines, material transportation, and water utilization. Our observations yielded a high-level view of emission intensity across the value chain of hydraulic fracturing. Wellsite execution related fuel consumption during pumping was the highest contributor to emissions at 36%, followed closely by the flaring for fracture cleanup at 29%. Total transportation contributed 24% to the total emissions. While the emissions of the fracturing fleets are often very visible due to their large footprint and duration, surprisingly, the nonroutine flaring and transportation are also impactful. In fact, nonroutine flaring could have much higher impact depending on how fast the cleanup process could take place, which may not be easy to predict.

It is reported that using natural gas in internal combustion engines reduced the CO2 emissions. However, the methane leak from engines would offset the CO2 savings and render the benefits marginal. We also observed that the reuse of produced water to be a feasible way to reduce the well stimulation footprint on water resources, which could be enabled by improved water treatment techniques at scale, advances in hydraulic fracturing fluid composition, and appropriate infrastructure. We quantified the upstream emissions (embodied carbon) of commonly used chemicals. Our calculations show that the embodied carbon of commonly used chemicals in unconventional fracturing is rather small. Our conclusions emphasize the importance of adopting ecofriendly technologies to address the challenges posed by hydraulic fracturing. They can impact up to 35% of emissions reduction.

This study contributes a high-level, yet accurate, perspective on emissions of the hydraulic fracturing process. We highlight the high-emitting steps in the process and identify technology gaps that could reduce the emission footprint of the industry. This research underscores the urgency of adopting responsible practices in hydraulic fracturing for a harmonious coexistence with global sustainability objectives.
Data Structures and Integrations for Environmental Reporting and Analytics
Authors: Hill Travis
Published: September 2024

Data structure and integrations are vital components to a successful implementation of environmental software used for tracking, reporting, and data analytics. Defining the expected data outputs at the beginning of a software implementation results in an efficient and effective reporting process, which meets stakeholders’ expectations, and is the foundation for advanced analytics. A robust evaluation of the expected reporting, whether it is required for regulatory, voluntary, or internal reporting, will set the requirements for source system data. If the data in the identified source systems is not available or reliable, the outputs of the environmental system should be adjusted, or the project should be postponed until the source system data is readily available.

This paper explains how the project team and stakeholders defined the requirements, data fields, calculation methodologies, necessary reports, and document approvals. Documentation is necessary to effectively communicate the requirements and expectations for developers, while also allowing appropriate stakeholders to agree on the project deliverables. Without proper documentation and approvals, the project outputs are likely to miss the intended outputs and require rework.

During the project planning phase, the implementation teams created workflows or diagrams tracing components for each desired output back to source systems. The diagrams identified data points such as source system fields, frequency of updates, unit of measure, unique identifies, Global Positioning System (GPS) coordinates, or run-time information. The data point definitions show the availability of the data from the source system and frequency of updates of source system data to influence integration design.
Digital Reporting Solution Delivers a New HSE Observation & Intervention Every Minute!
Authors: Pamnani Amit , Bhushan Bharat , Albanna Mohammed Abdulsalam , Dey Dhiman
Published: September 2024

ADNOC Offshore has developed a robust HSE Observation & Intervention program, leveraging digital solutions to enhance reporting culture and safety performance. This initiative has led to a significant decline in incident and injury rates, reinforcing our commitment to 100% HSE.

ADNOC Offshore collects HSE observation data from HSE Observation & Intervention Mobile application through which all our employees and contractors reports safe or unsafe acts or conditions by selecting various dropdown options and attaching photos when and where possible and applicable. However, the observation description captured in these reports is often incomplete, inconsistent, and unstructured, making it difficult to analyze and derive insights. Due to varied level of literacy and educational background the description typed in English may not be grammatically correct or even misspelled. The company wants to use machine learning to improve the data quality, risk rank, identify patterns and trends, and enhance the decision-making process for HSE management. The aim is to do real-time intervention at the time of reporting an event based on AI tool, further analysis for these unsafe acts & conditions and prevent those from becoming incidents. Due to the large volume of data, it was very challenging to analyze and identify trends and common hazards.
Transforming Safety and Operational Excellence: ADNOC's Implementation of an Integrated Work Management System
Authors: Saleem Juzar
Published: September 2024

In the ever-evolving landscape of the global oil and gas industry, ensuring safety, maximizing efficiency, and achieving operational excellence are paramount objectives. The Abu Dhabi National Oil Company (ADNOC), a global leader in energy production, has taken a groundbreaking step towards realizing these goals through the implementation of its innovative Work Management System (WMS). This comprehensive digital solution represents a paradigm shift in how work is conceptualized, managed, controlled, and executed across ADNOC's vast and diverse operations, effectively setting new benchmarks for the entire industry.

The scale and scope of the WMS implementation are truly remarkable, making it one of the largest and most ambitious projects of its kind in the oil and gas sector. With over 50000 trained and active users, the system processes more than 2 million permits annually and manages in excess of 1.2 million certificates and risk assessments. These figures alone underscore the transformative impact of this initiative on ADNOC's operations.

This comprehensive overview delves deep into the intricacies of ADNOC's Work Management System, meticulously detailing its key components, chronicling the implementation journey, and analyzing the profound impact it has had on the organization's safety culture, operational efficiency, and overall performance. This thorough exploration aims to provide a detailed understanding of how ADNOC has managed to create a safer, more efficient, and high-performing operational environment through the strategic implementation of the WMS.
Estimating Probability Distribution for the Random Time Variable in the Continuous Compounding Formula: Implication to Time Value of Money in Investment Decisions
Authors: Hesse Christian Akrong , Boyetey Dominic Buer , Nyarko Eunice Stella , Ashiagbor Albert Ayi
Published: September 2024

This paper treats the time “t” variable in the continuous compounding formula of the time value of money as a random variable and derives a probability distribution for it. It formulates a mathematical model that shows the probability associated with the time of recouping the present value of the investment at a specified time and estimates the time at which a given asset changes, holding other factors constant. The study finds that there is an indirect relationship between the investment holding period and the probability of obtaining an investment return on the future value of an asset. It also finds that there is a maximum threshold of time that maintains the present value of an asset after which the probability decreases. This paper differs from previous studies by modeling time as a random variable.
Recent development of a laser interferometer for Taiji space gravitational wave detection
Authors: Luo Ziren , Liu He Shan , Wang Juan , Tao Wei , Qi Ke Qi , Wang Shao Xin , Gao Rui Hong , Li Pan , Dong Peng , Sha Wei , Hu Wen Rui
Published: September 2024

In this study, we developed and constructed the first-generation ultrastable optical bench (OB) for the Taiji program. The OB uses optical bonding technology, and for the first time, noise testing and calibration were performed. A comprehensive analysis was carried out on the various noise sources impacting the interferometer system; these sources included laser frequency noise, laser power noise, thermal drift noise, and angular jitter noise. When the environmental conditions fell short of our stringent requirements, an advanced post-data processing technique was employed to effectively reduce both the thermal drift noise and angular coupling noise. The results revealed that the noise level of the interferometer system reached 1.1 pm/Hz1/2 at 1 Hz, 5 pm/Hz1/2 at 0.1 Hz, and 8 pm/Hz1/2 at 0.01 Hz; these levels met the requirements of the Taiji pathfinder mission. Furthermore, a future research proposal was provided, with the aim to meet the full frequency range requirements of the Taiji program.
Development and validation of prediction model for prolonged mechanical ventilation after total thoracoscopic valve replacement: a retrospective cohort study
Authors: Lin Zhiqin , Xu Zheng , Chen Liangwan , Dai Xiaofu
Published: September 2024

Background
Total thoracoscopic valve replacement (TTVR) is a minimally invasive alternative to traditional open-heart surgery. However, some patients undergoing TTVR experience prolonged mechanical ventilation (PMV). Predicting PMV risk is crucial for optimizing perioperative management and improving outcomes.
Methods
We conducted a retrospective cohort study of 2,319 adult patients who underwent TTVR at a tertiary care center between January 2017 and May 2024. PMV was defined as mechanical ventilation exceeding 72 hours post-surgery. A Fine-Gray competing risks regression model was developed and validated to identify predictors of PMV.
Results
Significant predictors of PMV included cardiopulmonary bypass time, ejection fraction, New York Heart Association grading, serum albumin, atelectasis, pulmonary infection, pulmonary edema, age, need for postoperative dialysis, hemoglobin levels, and PaO2/FiO2. The model demonstrated good discriminative ability, with areas under the receiver operating characteristic curves of 0.747 in the training set and 0.833 in the validation set. Calibration curves showed strong agreement between predicted and observed PMV probabilities. Decision curve analysis indicated clinical utility across a range of threshold probabilities.
Conclusions
Our predictive model for PMV following TTVR demonstrates strong performance and clinical utility. It helps identify high-risk patients and tailor perioperative management to reduce PMV risk and improve outcomes. Further validation in diverse settings is recommended.
Accurate estimation of suspended sediment concentration integrated remote sensing information and a novel stacking machine learning model
Authors: Fang Xiaotian , Zhang Jiahua , Yu Xiang , Zhang Shichao , Kong Delong , Wang Xiaopeng , Ali Shawkat , Ullah Hidayat , Xu Nuo
Published: September 2024

Suspended sediment concentration (SSC) in rivers significantly impacts the preservation of the ecological environment and the exploitation of water resources. The advancement of remote sensing technique offers a robust approach for monitoring SSC. However, the complexity of watersheds and the surrounding environment present a new challenge for accurate estimation of SSC. To address this limitation, this study proposes a new stacking model considering Multilayer Perceptron and Light Gradient Boosting Machine with Elastic Net algorithm (MLEN), and integrates remote sensing information for precise estimating SSC. The Tree-structured Parzen Estimator method was adopted to optimize hyperparameters, the MLEN model was trained by reconstructed datasets combining surface reflectance from high-quality Landsat remotely-sensed images over 30 years, with environmental factors including precipitation, temperature, wind, and surface pressure from ERA5 dataset, as well as discharge and SSC data from USGS five hydrographic stations of the Middle Rio Grande River Basin in the United States. Those stations were selected with over 30 years of available data and nearby gauged stream widths of at least 90 meters to ensure local characteristics and reliable satellite sampling. Moreover, the contribution of features on estimating SSC was also discussed in detail. The results show that compared with the individual models, the MLEN model achieved best accuracy in estimating SSC. Furthermore, the MLEN model also outperformed the other five machine learning algorithms (R2 = 0.80, RMSE = 0.44, and MAPE = 0.30). It indicates the MLEN model can effectively predict SSC in complex, long-term, and time-varying watersheds with readily available hydrographic data.
Rack1 Contributes to the Upregulation of Embryonic Genes in a Model of Cardiac Hypertrophy
Authors: Ceci Marcello , Bonvissuto Davide , Papetti Flavia , Silvestri Federica , Sette Claudio , Catalani Elisabetta , Cervia Davide , Gornati Rosalba , Romano Nicla
Published: September 2024

Receptors for activated C kinase (RACKs) have been shown to coordinate PKC-mediated hypertrophic signaling in the mouse. However, rare information is available on its participation in embryonic gene expression. This study investigated the involvement of RACK1 in the expression of embryonic genes in a zebrafish (ZF) ex vivo heart’s culture model by using Phenylephrine (PE) or a growth factors cocktail (GFs) as pro-hypertrophic/regeneration stimuli. Blebbistatin (BL) inhibitory action treatment was also studied for its involvement in blocking some of PE’s signal transduction actions. qRT-PCR and immunoblot analyses confirmed the upregulation of RACK1 in the PE- and GFs-treated groups. BL administration counteracted PE-induced hypertrophy and downregulated RACK1’s expression. Immunohistochemical analyses of the heart showed the co-localization of RACK1 and embryonic genes, namely, Gata4, Wt1, and Nfat2, under stimulation treatment, whereas resulted less expressed in the BL treatment. Cultured ZF heart cells activated via GFs treatment the enhanced expression of RACK1. Overexpression of RACK1 induced by transfection of recombinant RACK1 cDNA in ZF heart cells, enhances the expression of embryonic genes, especially after a week of GFs treatment. In summary, these results support the involvement of RACK1 in the induction of embryonic genes during cardiac hypertrophy/GFs stimulation in a fish heart model, which can be used as a mammal's alternative study model.
Oakland Score to identify low-risk patients with lower gastrointestinal bleeding performs well among emergency department patients
Authors: DiLena Daniel D. , Bouvet Sean C. , Somers Madeline J. , Merchant Maqdooda A. , Levin Theodore R. , Rauchwerger Adina S. , Sax Dana R.
Published: September 2024

Background: The Oakland Score predicts risk of 30-day adverse events among hospitalized patients with lower gastrointestinal bleeding (LGIB) possibly identifying patients who may be safe for discharge. The Oakland Score has not been studied among emergency department (ED) patients with LGIB. The Oakland Score composite outcome includes re-bleeding, defined as additional blood transfusion requirements and/or a further decrease in hematocrit (Hct) >/= 20% after 24 hours in clinical stability; red blood cell transfusion; therapeutic intervention to control bleeding, including surgery, mesenteric embolization, or endoscopic hemostasis; in-hospital death, all cause; and re-admission with further LGIB within 28 days. Prediction variables include age, sex, previous LGIB admission, systolic blood pressure, heart rate, and hemoglobin concentration, and scores range from 0 to 35 points, with higher scores indicating greater risk.
Methods: Retrospective cohort study of adult (≥18 years old) patients with a primary ED diagnosis of LGIB across 21 EDs from March 1st, 2018, through March 21st, 2020. We excluded patients who were more likely to have upper gastrointestinal bleeding (esophago-gastroduodenoscopy without LGIB evaluation), patients who left against medical advice or prior to ED provider evaluation, ED patients without active health plan membership, and patients with incomplete Oakland Score variables. We assessed predictive accuracy by reporting the area under the receiver operator curve (AUROC) and sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios at multiple clinically relevant thresholds.
Results: We identified 8,283 patients with LGIB, 52% were female, mean age was 68, 49% were non-white, and 27% had an adverse event. The AUROC for predicting an adverse event was 0.85 (95% CI: 0.84 to 0.86). There were 1,358 patients with an Oakland Score of </=8; 4.9% had an adverse event, and sensitivity of the Oakland Score at this threshold was 97% (95% CI 0.96 to 0.98).
Conclusion: The Oakland Score had high predictive accuracy among ED patients with LGIB. Prospective evaluation is needed to understand if the risk score could augment ED decision-making and improve outcomes and resource utilization.
Harnessing Industry 4.0 Technologies for Human Resource Development in Iraqi Higher Education: Challenges and Opportunities
Authors: Jubouri Hassan Abed Ali Alwan
Published: September 2024

This research delves into the transformative potential of Industry 4.0 technologies, such as artificial intelligence (AI), the Internet of Things (IoT), big data analytics, and robotics, in advancing human resource development within Iraqi higher education. Anchored in the principles of digital transformation and organizational change management, this study illustrates how AI can personalize learning experiences and streamline administrative tasks, thus enhancing efficiency and effectiveness. IoT supports the real-time monitoring and upkeep of educational infrastructure, while big data analytics offer critical insights into student performance and institutional operations. Additionally, robotics enrich practical training and research opportunities. By integrating these theoretical frameworks, the study examines the comprehensive impact of Industry 4.0 technologies on developing human resources in the educational sector.