bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accelerating Wellbore Domain Interpretations Using Generative AI and Knowledge Graphs
Authors: Rekik Karim , Zhou Zengpeng , Ouzineb Sohaib , Zened Olfa , Amour Myriam 
Published: November 2024

Abstract
The petroleum industry relies heavily on accurate wellbore domain interpretation for effective resource management and extraction. Traditionally, this process involves numerous complex and time-consuming steps, such as data normalization, unit harmonization, and depth matching, often requiring extensive expertise. This paper presents an AI-powered solution designed to automate the creation of wellbore interpretation workflows, significantly enhancing efficiency and accuracy.
Our solution integrates generative AI, large language models (LLM), and graph-based methods to streamline the workflow creation process. The methodology involves three key steps: knowledge gathering from extensive documentation, automatic workflow generation through natural language interactions with a chatbot, and execution of quality-checked workflows. By leveraging a comprehensive knowledge base built from training manuals, API references, and historical interpretation data, our system can intelligently suggest optimal workflows in response to user queries.
Tests conducted using data from the Groningen field demonstrate the effectiveness of this approach. The time required to create a lithology computation workflow was reduced from the typical 15-30 minutes to just 10 seconds using our AI-powered workflow advisor. This represents a time reduction factor of up to 180 for junior petrophysicists. The knowledge graph employed in this process showed a 93% accuracy in building workflows, ensuring reliability and precision.
This innovative solution not only saves time but also minimizes errors, enabling non-experts to perform accurate data interpretation. The AI-powered workflow advisor represents a significant advancement in the automation of wellbore interpretation tasks, demonstrating the potential of machine learning to revolutionize the petroleum industry. By automating tedious and complex processes, our solution contributes to faster, more reliable wellbore analysis, ultimately improving decision-making and operational efficiency.
Maximizing Drilling Performance with Real-Time Digital Twins, Automated Advisory and Cutting-Edge Digital Platform
Authors: AitAli R. , Arevalo P. , Grymalyuk S. , Bourechak T. , Belgacem H. , Chergui H. , Sellam A. , Zarra A. F. , Sardella C. , Tahri A. , Merah F. , Fattouch A. , Pietragallo L. , Venerio C. , Tricasi V. , Salinas A. 
Published: November 2024

Abstract
The integration of real-time digital twins with offset wells performance analysis is critical for optimizing drilling operations and reducing non-productive time (NPT) and invisible lost time (ILT). This paper presents a digital platform that combines innovative product solutions, communication protocols, and preventive measures to mitigate costly downhole issues and enhance drilling efficiencies. The digital twin of the wellbore uses physics-based models to continuously monitor torque and drag indicators, transient pressure regimes, and drilled cuttings bed concentration, enabling early identification of hole condition issues through automated alarms and mitigation advice.
The drilling automation application optimizes drilling parameters by combining rate of penetration (ROP) and vibration data (VSS) to produce parameters that ensure tool integrity and reduce maintenance costs. A cloud-based platform integrates real-time software and has over 85 solution-based applications to monitor operations, provide advanced analytics, and proactive workflows using hazard detection algorithms.
This paper presents case studies demonstrating the benefits of integrating digital twins with offset wells performance analysis. Results show significant improvements in drilling performance, including a 17% reduction in weight-to-weight (W2W) time, 22% increase in ROP, and 31% reduction in overall well drilling time compared to P10 and 37% compared to P50. The integration of digital twins and intelligent detection of trend deviations during drilling operations contributes to a robust drilling optimization and hazard prevention workflow, improving the accuracy of resulting models and performance trends. The combination of these well monitoring mechanisms contributes to the overall reduction of well construction time and cost.
Construction Barge Performance Management - Artificial Intelligence Based Software
Authors: Siddiqui Shahid Ahmed 
Published: November 2024

Abstract
In the case of Offshore Construction through barges and construction works in general, whatever is the contracting strategy, one thing is common to all, which is human performance, this drives efficiency and makes the basis of all the development of Cost.
There is a significant potential to enhance human efficiency. The project "CONSTRUCTION BARGE PERFORMANCE MANAGEMENT - ARTIFICIAL INTELLIGENCE BASED SOFTWARE" is development and implementation of AI/ML based software that analyzes components of human efficiency to identify training needs and establish targets for low performers to elevate their efficiency, thereby improving overall workforce efficiency and output. Huge data related to work requirements and workforce attributes is utilized by the software to suggest rational deployment of every worker at the most appropriate work location.
In complex offshore construction, the gap between average and high productivity among workers is often due to lack of an effective work front. The software is designed to streamline work fronts, optimizing sequencing to shorten critical paths, attain effective work front and then balance the workforce with effective work front so derived. It analyzes non-productive time (NPT), suggests improvements and automates and eventually makes management autonomous. This approach aims to elevate productivity, pushing human efficiency and output to new heights.
One of the major tools of this software is the point-based system to evaluate performance and skills. It generates points based on the skills and performance of the workforce to determine compensation. This system develops multi-skilled workers. The system identifies training needs and suggests appropriate courses. It also helps in identifying candidates for promotion by evaluating their performance and multiple skills, suggesting additional training or qualifications required for the next step in their career. Once the system is operated for one to two years it will have enough data to ensure fair compensation, identify training needs, fair promotions, improved behavioral based safety and effective counseling of workforce. Another important module of the software is deft handling of behavioral based safety data which aims to improve BBS and workers’ wellbeing. IoT cameras/sensors integrated with the system will be used in reducing HSE incidents and tracking and improving workers’ well-being.
Significance of Multiple CO2 Plume Management and Pressure Interactions during Geological CO2 Storage Operation based on the Canadian Aquistore CCS Project
Authors: Shokri Alireza Rangriz , Kamali Marziyeh , Movahedzadeh Zeinab , Narayanasamy Ranjith , Nickel Erik , Chalaturnyk Rick 
Published: November 2024

Abstract
Carbon capture and storage is a viable short-to-medium term strategy to reduce emissions and support a low-carbon economy. However, geological storage of CO2 in Giga-tonne scales requires many injection wells, leading to complex integration of multiple CO2 plumes. Based on a decade of CO2 storage operation at the Canadian Aquistore CCS project, this paper explores the potential CO2 plume commingling and subsequent pressure buildup during clustering of large-scale geological CO2 storage operations.
To assess the significance of multi-well CO2 injection on storage capacity and injectivity, we constructed a static regional model that characterizes the storage and sealing formations. To understand the potential repositories, traps, and sealing mechanisms, the regional model considered 23 wells in the region to build a robust structural framework, utilizing the geological information, interpreted 3D horizons, well tops, and reservoir properties populated based on 3D seismic porosity volumes. A section of the regional model was selected to match the Aquistore injection history and to evaluate the impact of multiple injection wells and CO2 plumes within the area of interest.
The dynamic reservoir model was calibrated to the injection data up to year 2020. The history matched simulation model was then used to predict the injection history for the next three years, until 2023. The simulation forecast was compared against actual field data in the same timeframe to assure the simulation model is capable to predict the CO2 storage operation. Different CO2 injection scenarios were employed for dynamic reservoir simulations for the next 20 years with varying injection rates. The injection pressure was constrained to a value below 95% of fracturing pressure determined from an earlier mini-frac test. We monitored the commingling of the CO2 plumes from different wells under a range of reservoir and operational uncertainties. To address the regulatory concerns, the degree of pressure interference between each adjacent CO2 injectors was used to observe the influence of each CO2 injection well before and after the integration of individual CO2 plumes. Lastly, enhanced operational and adaptive pressure management strategies for the CO2 injection wells were discussed to mitigate the potential subsurface risks, maintaining the injection rates and storage capacities within safe limits.
Utilizing eight years of actual field data from the Aquistore CO2 injection site is an asset to better understand the CO2 plume evolution and the associated regional pressure buildup in saline aquifers. The modeling results provide valuable insights into the safe and long-term management of multiple CO2 plumes, and showcase the importance of clustering of large-scale geological CO2 storage projects for operators and regulators.
The Integrity Evaluation of Geological Body for CCUS Technology Based on Microseismic Monitoring Technology
Authors: Xu Jianguo , Zhou Yuchi , Pan Ruosheng , Huang Tianjie , Liu Bo , Gao Qiang , Liu Yutong 
Published: November 2024

Abstract
The integrity of geological bodies is a fundamental condition for the long-term and highly efficient storage of CO2. Geological body integrity of CO2 injection areas is indirectly judged by such conventional methods as primarily assessing contamination degree of water and gas in shallow layers, as well as changes in carbon flux in soil and the atmosphere. Direct identification methods for leakage pathways of inter-layers and faults are relatively limited. This paper puts forward a evaluation method for geological body integrity of Carbon Dioxide Capture, Utilization, and Storage (CCUS) based on microseismic monitoring technology.
This technique utilizes downhole geophones to collect data of target intervals, and employs perforation signals of adjacent wells for polarization analysis of P-waves. Then we correct the direction of the downhole geophones with three-components, optimize the velocity model. Subsequently, microseismic signals generated during the CO2 flooding process are located by adopting the method of multi-wave joint orientation technology. By analyzing the sequences and spread conditions of microseismic events, the spread distribution of CO2 flooding front is grasped, and the channeling condition of inter-layers is determined. This technology has been applied in the CO2 flooding test areas in Jilin Oilfield, which is the largest CCUS demonstration area in PetroChina. It is designed with 12-stage geophones, with a longitudinal monitoring range covering the top and bottom boundaries of the oil reservoir. The lateral monitoring range is approximately 1500m, and the monitoring period is 60 days, covering two complete water-gas alternating injection cycles, each cycle lasting 30 days.
By statistically analyzing the time sequence and magnitude attributes of microseismic events, a total of 539 effective microseismic events have been acquired, with magnitudes ranging from -3.13 to -0.906. In the vertical direction, the locations of microseismic events are concentrated in producing reservoir areas, with no continuous microseismic events occurring across the cover layer, indicating good integrity performance of the formation.
The successful application of this technology effectively evaluates the geological integrity of CCUS systems, which is of significant importance in guiding the subsequent location selection for CCUS/CCS technologies. Additionally, it provides effective data support for understanding the flow patterns of CO2 injected into the formation, and also the basis for the mapping of subsequent development plans.
A Breakthrough Sulfur Dust & Granulate Cleaning by UAE Made Robot
Authors: Alkhoujah K. , Al Ali A. , Al Ghassani M. , Al Marzooqi S. , Al Ameri M. , Al Muharrami F. , Karki H. 
Published: November 2024

Abstract
This paper will present a successful enhancement within ADNOC Sour Gas. Shah Gas development field (SGDF) consists of three main areas which are well pads and gas gathering, gas processing plant and Sulfur station. One of the major challenges at the Sulfur station is the management of Sulfur dust and granules around the granulators area. A dedicated working force is required to conduct cleaning activities to ensure smooth operations and avoid unanticipated operation interruption. Around 40 cleaners are required for cleaning activities for a period of 3-hours on daily basis in each shift. This paper will present the details and capabilities of the robot and its specification and the results of operating it at ADNOC Sour Gas Sulfur Station. Additionally, this paper will review some of the existing solutions and practices for Sulfur dust management in other Sulfur producing facilities around the world, such as Canada, Kazakhstan, and Saudi Arabia, and compare their effectiveness and efficiency with the proposed robot system.
Subsea Well Troubleshooting through flow Assurance Dynamic Simulation
Authors: Gioja G. , Montini M. , Tiozzo A. 
Published: November 2024

Abstract
During the commissioning of a gas well integrated into a cluster system, substantial quantities of liquids accumulated within the flowline, resulting from various operational anomalies. This accumulation presented a significant technical challenge during the well restart phase, primarily due to the volumetric surge of liquids in the Slug Catcher and the limitations of topside process liquid management systems. The complexity of this issue necessitated a thorough investigation and the development of a robust solution to displace the accumulated liquids and ensure an effective well restart.
To address this challenge, a series of comprehensive studies and analyses were undertaken. The core of this troubleshooting effort was the deployment of a model in a sophisticated flow assurance simulation tool. A multiphase dynamic simulator (MDS) was employed to simulate the liquid displacement process and evaluate the restart behavior of the well under different operational scenarios. This approach facilitated the identification of critical operational parameters and constraints, enabling the development of an effective and reliable operational procedure.
The subsequent sections of this paper detail the methodology employed, the insights gained from the simulation studies, and the formulation of the operational procedures designed to mitigate the issues associated with liquid accumulation during well restart. This study highlights the critical role of advanced simulation tools in addressing complex flow assurance challenges in hydrocarbon production systems.
An Efficient and Integrated Biomass to Sustainable Low-Carbon Bio-Ethylene Process
Authors: Raizada Abhishek , Sarin Yogendra 
Published: November 2024

Abstract
Various types of biomass such as agriculture waste/residues and sustainably sourced woody biomass can be utilized to produce circular, low carbon biofuels such as SAF/gasoline/methanol and Diesel for decarbonization of transport, as well as biobased chemicals like Ethylene Oxide (EO), Polyethylene and others. The entire process for conversion of biomass to biofuels and renewable chemicals presents a highly efficient, integrated and a low carbon sustainable alternative to fossil fuels as a solution urgently needed to combat climate change and for meeting the Net Zero Goals by 2050. The integrated process backed by trade secrets and extensive IP involves i) conversion of biomass into bioethanol intermediate via Petron's highly efficient and commercially demonstrated Cellulosic Ethanol G2.0 technology, and ii) dehydration (water removal) of bioethanol into high purity bio-ethylene. The ethylene produced is then purified upto the required grades depending on the downstream applications.
The biomass feedstock undergoes efficient pretreatment and is converted into constituent sugars via action of enzymes followed by fermentation into beer (alcohol) with high efficiency and yields. The beer is then purified to produce the required quality of ethanol which can be directly fed into Petron's proprietary Ethanol to Ethylene (EtE) process. The non-converted process residues are used as renewable fuel for green energy production. The bioethanol is dehydrated over a proprietary catalyst to produce high quality ethylene used for plastics, chemical and biofuel production. The water produced in the reaction is fully recycled back into the process requiring minimum freshwater and effluent generation.
This paper presents a low cost, efficient and integrated biorefinery concept for non-food biomass crops and waste biomass conversion into low carbon bio ethylene - the foundation of the global chemical industry for biofuels, plastics and bio-based chemicals production.
These biorefineries efficiently utilize either separately or a combination of low grade biomass crops (such as non-edible corn) and/or Cellulosic Biomass waste as feedstocks to produce multiple products such as High Protein Animal Nutrition Feed and Corn Oil (in case of non-edible biomass corn feedstock)ONLY the waste starch and fiber residues converted into low carbon EthanolBiogenic CO2 produced during ethanol fermentation is of high purity and can be used for multiple applicationsThe bioethanol once produced becomes a platform for production of BIOETHYLENE - the heart of the chemical industry – which can be converted further into biofuels such as Sustainable Aviation Fuel (SAF) as well as downstream renewable chemicals
Conquering Challenges: A Case Study of Successful Project Execution
Authors: Sarmah Suranjana , Rajak Nitesh Kumar 
Published: November 2024

Oil India Limited's ambitious 30MW Gas Engine based power plant project flagged off at Duliajan, Assam, India, in January 2021. The project site was in one of the remotest corners of North-East India, where adverse climatic conditions, specifically heavy and extended monsoon, and logistical challenges inherently delays constructional activities. The challenges in this project increased manifold as it necessitated transportation of high tonnage equipment from Europe to the site, traversing international seas and thousands of km on road, at a time when the world was reeling under the Covid 19 pandemic and geo-political disturbances arising out of Russia Ukraine conflict. Apart from above, the project, being an extension within an existing power plant, was essentially brown field in nature and to carry out all the construction work with minimum hindrance to the running plants was one of the pre-requisites. Limited maneuverability, water logging issues, unchartered ground condition, need for dismantling of existing structures inside restricted industrial area were few of the many on ground hindrances encountered.
This paper presents a case study of remarkable execution of a high capex brownfield project of approximately $23 million amidst unprecedented challenges in the backdrop of COVID-19 pandemic and geopolitical tensions stemming out of the Russia-Ukraine conflict, in one of the remotest corners of Northeast India. Despite multifaceted adversities, the project stands as a testament to resilience and commitment, having been executed without time and cost overruns. This paper carefully examines and analyses the strategic decisions made to overcome various challenges encountered during different stages of project execution. Best practices that were followed from concept till commissioning of the project that had helped achieving the success are also the highlights of this paper.
Lithium Extraction from Produced Water using Lithium Aluminum Layered Double Hydroxide Chloride Sorbent
Authors: Alshammari Salem , Sangaru Shiv Shankar , Saleem Hussain , Ayirala Subhash 
Published: November 2024

Abstract
Lithium-ion batteries (LIB) are crucial components for renewable energy generation and storage technologies, making lithium an essential mineral due to its irreplaceable role in LIB because of its unique physiochemical properties. While lithium is traditionally extracted from solid mineral deposits or Salar brines in the lithium triangle of South America, alternative sources such as produced water from oil and gas reservoirs offer a promising yet underutilized opportunity. Nevertheless, produced water from oil and gas reservoirs contains low lithium levels but can be enriched through desalination. This approach concentrates lithium and generates fresh water that can be utilized for various upstream oil and gas applications, including improved oil recovery, formulating fracking fluids and oil desalting, along with other potential uses like irrigation. In this study, we analyzed the lithium concentration in produced water desalination reject, finding it to be 60 ppm amid a concentrated brine matrix with a total dissolved solids (TDS) of approximately 290,000 ppm. We synthesized a selective lithium aluminum layered double hydroxide chloride (LADH-Cl) sorbent to effectively capture lithium at low levels. The sorbent was characterized using powder X-ray diffraction (PXRD), thermogravimetric analysis (TGA), and inductively coupled plasma-atomic emission spectroscopy (ICP-AES), confirming its successful synthesis. When applied to real-produced water desalination reject samples, the LADH-Cl sorbent reduced lithium concentration from 60 ppm to 21 ppm using just 51.2 mg of sorbent with 20 g of brine. This work highlights the potential of LADH-Cl as an effective sorbent for lithium extraction from produced water, offering a dual benefit of waste brine utilization and valuable lithium recovery.