bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing Drilling Equipment Reliability: Deep Learning for Predicting Failure Time and Real-Time Anomaly Detection
Authors: Tharayil Sarafudheen M. , Alrammah Marah M. , Alghamdi Maria A. , Aljohar Fatimah E. , Otalvora William B. Contreras 
Published: November 2024

Abstract
Predict drilling equipment's failure time and real-time anomaly detection play crucial roles in ensuring the seamless Oil and Gas wells drilling operations. In this study, we delve into the application of neural network-based machine learning techniques specifically tailored for these tasks in drilling. Our primary objectives encompass diagnosing equipment health states, detecting anomalies in real-time, and predicting remaining useful life (RUL). To address these challenges, we implement a novel combination of neural network architectures, including convolutional layers, Long Short-Term Memory (LSTM) cells, and attention layers. By meticulously training our model on historical data using carefully selected deep-learning hyperparameters, we tackle the unique characteristics of drilling equipment data. The resulting neural network predicts total lifetime and RUL based on historical input. Our LSTM model achieved an accuracy of 74.03%, given the complexity and novelty of the dataset, these results establish a strong benchmark for future research. This improvement results from hyperparameter tuning and optimized network architectures. Additionally, accurate anomaly detection and minimized unscheduled downtime of 14% demonstrate potential cost savings for oilfield operators. By identifying potential failures in advance, our approach allows efficient scheduling of maintenance activities. Field engineers express satisfaction with our approach, validating its effectiveness. Our research introduces novel aspects to drilling equipment maintenance. Through empirical validation, we rigorously test our approach using real-world drilling sensor data, ensuring robustness and reliability. This instills confidence in industry practitioners. Furthermore, our intuitive real-time anomaly detection system enhances drilling safety, efficiency, and cost savings.
Water Management Strategy in UAE's Unconventional Fields: A Case Study of Closed Loop Operations and Novel Treatment Technologies
Authors: Alhassani A. A. , Baig M. Z. , Elazab S. A. , Burgess C. , Caillon D. P. , Alvarado O. A. , Bannay A. Al 
Published: November 2024

Abstract
As part of the UAE's commitment to Environmental Social Governance (ESG), unconventional exploration operations adhere to a strict zero-tolerance policy regarding spills. Consequently, closed-loop operations were instituted across all rigs and sites, ensuring no water is discharged into pits. This approach is supported by a thoroughly planned treatment and discharge strategy established before operations begin.
This paper will delineate the water management strategy, focusing on the closed-loop system and innovative treatment technologies that facilitate H2S removal without infusing chemicals into the produced fluid. By preventing both over- and under-treatment, this method not only enhances operational efficiency but also reduces costs. A major challenge encountered was managing and treating high-temperature flowback water exceeding 200 degrees Fahrenheit.
Additionally, the paper will explore the technical and operational experiences in establishing the water management process for Zipper frac operations, where over 800,000 barrels of water were pumped. It includes the sourcing, storage, and treatment protocols, alongside modifications to testing and treatment equipment designed to handle high-temperature, high-pressure flowback water. The use of real-time, non-chemical H2S treatment methods reduced testing time by 50%.
Initiatives aiming for efficient and cost-effective water management solutions are being explored to facilitate the profitable development of unconventional gas and oil in the UAE. These initiatives strive to merge optimal performance and low-cost strategies with current regulations and environmental requirements to ensure sustainable operational security. The scope of the paper extends these closed-loop operations to metal extraction, applying circular economy principles to unconventional completion operations.
While the development of unconventional oil and gas resources has transformative impacts on the UAE and global energy markets, concerns about water availability in desert regions remain. The UAE, however, benefits from significant oil and gas reserves as well as abundant water resources—both surface and subterranean—and advanced local water treatment technologies and services. Moreover, the basin's proximity to the sea and the stratigraphic setting of target unconventional reservoirs below known aquifers like Simsima and Um Radhuma provide notable advantages.
Improving Well Control Response Ability via Virtual Reality Technology
Authors: Luo Yuan , Zhu Jun , Pang Ping , Xu Xianjue , Qing Yu 
Published: November 2024

Abstract
The objective of this study is to address the challenges faced in well control emergency response training due to the impracticability of simulating actual crisis scenarios and the rarity of personnel who have experienced real well control emergencies. Traditional training methods are limited and often result in ambiguous outcomes, highlighting the need for an improved approach to preparing teams for well control incidents. Our method involves the utilization of Virtual Reality (VR) technology to simulate and recreate various well control emergency situations. This immersive technology allows for the construction of diverse operational scenarios and facilitates multi-person collaborative drills. By employing VR simulations, trainees can experience realistic well control challenges in a safe and controlled environment, enabling them to practice response strategies and teamwork without the associated risks of real-life emergencies. Also receiving multi-person collaborative training via VR technology results in a lower cost and high efficient way to simulate different scenarios where the teammate rarely to meet in real world which help them get used to their role and familiar with the procedure or environment under such conditions.
The implementation of Virtual Reality (VR) technology in well control emergency training has led to a multitude of positive outcomes. A significant enhancement in the trainees’ decision-making speed and accuracy was observed, as VR simulations provide instant feedback and allow for rapid iteration of scenarios. Trainees have also reported increased confidence in handling high-pressure situations due to the realistic, immersive experience offered by VR. Furthermore, the technology has enabled the creation of a comprehensive database of performance metrics, allowing for detailed analysis of actions taken during each simulation. This data-driven approach facilitates targeted improvements in both individual skillsets and team dynamics. Moreover, the scalability of VR solutions allows for larger numbers of employees to be trained simultaneously, further amplifying the return on investment. In essence, the adoption of VR for well control emergency training has not only transformed the effectiveness of such programs but also provided a sustainable, scalable, and economically viable pathway to building a safer and more competent workforce within the oil and gas industry. The innovative aspect of this approach is the ability of VR to provide an interactive and engaging platform for well control emergency training. Through realistic simulations, VR allows for an unprecedented level of immersion and interactivity that traditional training methods cannot offer. As a result, personnel are better equipped with the necessary skills and confidence to effectively manage well control emergencies, ultimately enhancing safety and operational efficiency in the field.
Advanced Corrosion Classification Utilizing Machine Learning and Deep Learning Algorithms
Authors: Alquraini Ali H. , Al Sadah Hussain H. , Bayounis Ryyan A. , Al-Kadem Mohammad S. 
Published: November 2024

Abstract
One of the most critical elements in petroleum production engineering is downhole casing integrity. Thus, monitoring downhole casing corrosion is an important element as it ensures the safety and integrity of well assets. Corrosion logging is one important tool that provides valuable information on casing metal loss, that is used as part of a comprehensive monitoring program. In this paper, a new methodology that utilizes advanced Machine Learning (ML) and Deep Learning (DL) to classify downhole casing corrosion integrity status is presented. This method provides valuable additional information and insight that can improve safety.
The proposed methodology was to develop an intelligent system using ML & DL that automatically classifies casing corrosion and provides a predicted well downhole corrosion classification to engineers. Firstly, the proposed system actively fetches previously conducted downhole corrosion classification data. Secondly, an advanced pool of ML algorithms was created, and trained on fetched corrosion data. Thirdly, the ML pool evaluated and tested to be uploaded into the system. Finally, newly acquired data for unlogged or old log wells are fed to the advanced ML model to automatically classify downhole casing corrosion based on classes from low to high to engineer and notify them about wells with predicted high corrosion.
After finalizing the advanced ML system, it was evaluated on its performance to accurately classify downhole casing corrosion of well and provided system users with targeted classification results. In addition, performance of the system on classification, mitigation and mapping attributes were evaluated using ROC-AUC performance matrix which is a probability curve. After that, testing and evaluating the ML model showed a promising outcome scoring accuracy exceeding 85 % indicating the high efficiency of the model to accurately classify casing corrosion status instantaneously. The developed ML system enabled production engineers to proactively monitor downhole corrosion status reliably and securely. It's worth noting that by implementing such a system have yielded significant impact on our operation leading to both cost, time and recourses optimization. Moreover, the developed corrosion model optimized of thousands of casing corrosion logs conducted through classifying of downhole casing corrosion for unlogged ones, to better optimize resources and prioritize logging highly classified wells to be logged.
The proposed system leads to a fast and substantial improvement in acquiring a desired result field-wise in no time. Also, the system provides a detailed description and analysis of the downhole corrosion status to engineers. The developed downhole casing corrosion system has yielded promising results in prediction of wells with higher metal loss. This promotes safety by improving the existing comprehensive well integrity surveillance program.
Diethyl Ketone Based Waterflood in Carbonate Reservoirs-Boosting Fluid-Fuid Interaction and Oil Recovery
Authors: Yonebayashi Hideharu , Hiraiwa Takeshi , Yamada Tatsuya , Terajima Kohei , Yamamoto Kohei , Khlaifi Khuloud Tareq , Hoeth Laurien Wichers , Stalker Robert , Graham Gordon 
Published: November 2024

Abstract
Water-based enhanced oil recovery (EOR) has become more important in oil fields which have applied water injection because of lowering additional investment with use of existing facilities, minimizing carbon footprint, and keeping profit of sales gas by excluding a use for gas-based EOR purpose. Thus, several EOR options such as low salinity water (LSW), polymer, and hybrid methods have been studied in Middle East carbonates. This paper focuses on a new water-based option using dialkyl ketones as more polar solvents which have larger dipole moment compared with common ones such as dimethyl ether, ethanol, etc. The previous hybrid EOR studies highlighted an advantage of diethyl ketone (DEK) for boosting LSW EOR effectiveness in our objective offshore giant carbonate reservoir. The DEK advantage was proved from both aspects of core floods and fluid-fluid interaction (FFI) which forms micro-dispersion phase as an interfacial reaction of oil-water mixing. This paper pursued further potent advantage of adding DEK to non-diluted sea water (SW) injection. This option can save the cost for desalination water make-up process and facilities which are required for LSW based option.
Based on the compatibility and phase separation results (i.e., no solid precipitation for all types of fluids: SW, LSW, formation water, and crudes and no separation up to 2% DEK in SW), the injectant of SW-plus-DEK was designed at 2 wt% DEK concentration in non-diluted SW for fluid-fluid interaction (FFI) test and core flood evaluation. The FFI test revealed noticeable increment of micro-dispersion ratio (MDR), representing water content increment due to oil-water interfacial reactions, by adding ketones in both SW and LSW cases. The magnitude of DEK additive impact on MDR increment was more significant in non-diluted SW cases (i.e., 3.7 times of MDR from 2.0 v/v for pure SW to 7.3 v/v for SW-plus-DEK) compared with LSW cases (i.e., 2.6 times of MDR from 20.3 v/v for pure LSW to 52.6 v/v for LSW-plus-DEK). The core flood test (CF05) reached an oil recovery factor of 44% IOIP after a secondary mode of SW injection and achieved extra recovery of +15.6% in a tertiary mode of SW-plus-DEK. This oil increment was the largest among the previous core floods (CF01: tertiary pure-LSW injection, +3.0%; CF02: tertiary LSW-plus-DEK injection, +10.7%; CF04: tertiary LSW-plus-DMK injection, +14.4%). Furthermore, the oil recovery in the CF05 was clearly quicker as shown in the steeper recovery profile compared with those of other LSW based cases (i.e., CF01, CF02, and CF04). From both aspects of pursuing ultimate oil recovery and saving cost for desalination system, the non-diluted SW-plus-DEK injection was concluded as potentially the most attractive option.
Oil&Gas Decarbonization: Low-Carbon Fuels and Carbon Capture & Storage Offshore Power Barges, a Comprehensive Concepts Comparison
Authors: Anfray J. , Pactat A. , Gaouyat E. , Boscals-de-Reals T. 
Published: November 2024

Abstract
The objective of this paper is to present and compare two concepts to decarbonize Oil&Gas production facilities, particularly remote deep-offshore assets. The two offshore power barges concepts, called PGU (Power Generation Unit) are either based on low-carbon fuels or on local Capture & Storage to supply low carbon power & enable offshore facilities electrification.
One of the main challenges of the Net Zero ambition for the Oil&Gas industry (scope 1 and scope 2) is the reduction of GHG emissions related to the fuel gas consumption for power generation (&gt;70% of the CO2 emissions), particularly for offshore remote sites where Power from Shore is not feasible. Centralized floating Power Generation Units (PGU) can be connected to existing platforms and/or FPSOs to supply low carbon electricity.
Either with an offshore PGU fed with low carbon fuels (green or blue ammonia). The PGU include all the functions to store, treat & convert ammonia into a blend of hydrogen and ammonia. Either with an offshore PGU with carbon capture and injection into a local CO2 storage (CCS). The PGU includes a compact backpressure combined cycle, a post combustion solvent based (MEA), a capture package designed for 95% CO2 removal. Some units are directly integrated in the structure of the hull to optimize weight & space.
325 MWe of net electrical power are generated. This low carbon power is exported from the PGU to existing offshore facilities equipped with single cycle gas turbines (&lt;40% efficiency, 500 gCO2/kWh). This decarbonized power is exported through subsea electrical cables. The two concepts are compared in term of technical feasibility, maturity, GHG reduction and costs. A Life cycle analysis was performed to evaluate the environmental impact.
These low carbon power generation solutions (30 gCO2/kWh) enable to stop gas turbines on site. The two concepts result in similar floaters dimensions and Capex, with a higher Opex for the carbon free fuel due to fuel cost. The offshore CCS concept is seen as a shorter-term solution, applicable in the current decade, main challenge being the availability of an adequate CO2 storage to ensure a sustainable local reinjection. R&D focus on technology innovations to reduce costs. As an alternative, the offshore NH3 PGU concept is a longer-term solution for hard to abate sites, where CO2 reservoir availability can be an issue. A Life Cycle Analysis (LCA) shows that ammonia chain shall be green or fully sequestrated. R&D is driven by the need for new technologies, fully fuel flexible Gas Turbines to address multiple low carbon fuels scenarios. These developments shall be started now to enable this concept when the low carbon fuel market will be ready.
The novelty relies on the development and comparison of offshore power barges concepts delivering a minimum of 325MWe, either based on low-carbon fuels (ammonia) or CCS to power & decarbonize existing assets.
Case Study of Implementing Various Hydraulic Fracturing Software in the Challenging Operational Conditions of Saudi Arabia
Authors: Yudin A. , Nurlybayev N. , AlYaseen A. , Qadir W. , Al-Jalal Z. , Aljawad M. 
Published: November 2024

Abstract
A multitude of pseudo 3D and advanced 3D modeling software solutions are available for hydraulic fracturing optimization. These tools serve as indispensable aides for predicting fracture behavior, optimizing performance, and making informed decisions. This paper provides an overview and comparative analysis of the existing fracturing simulation techniques available and concludes practices for simulating the fracturing that helps achieving the optimum fracturing job execution.
The comparative analyses were performed by using pseudo 3D and advanced 3D modelling software packages. All simulations were conducted in unconventional (&lt;0.01 mD) and tight gas sandstone (0.1 – 1.0 mD). Each simulation revealed fracture behavior nuances specific to these reservoirs, providing valuable insights for informed decision. For the execution and data acquisition study, reliability and troubleshooting efficiency were used among the main criteria. Applications were grouped by geological and operational conditions.
For the first-time users and experts, the selection process can be daunting. Each software package comes with its own algorithms, assumptions, and limitations. Understanding these nuances is crucial for accurate predictions and effective decision-making, as even experts face dilemmas. As they need to delve into complex reservoir scenarios, and grapple with questions like: Which simulator accounts for geomechanical effects most accurately? How does each tool handle fluid flow in heterogeneous formations? What computational trade-offs exist between pseudo 3D and advanced 3D models? Current research endeavors to bridge the knowledge or understanding gap. By meticulously comparing various fracturing software tools, aiming to: quantify performance, by evaluating predictive accuracy, computational efficiency, and scalability; probe assumptions, by uncovering hidden assumptions within each model; benchmark against field data, by validating simulations against more realistic fracture behavior; recommendations, by providing evidence-based recommendations for tool selection based on reservoir characteristics, operational constraints, and user expertise.
This paper offers the readers a comparative analyses study that seeks to empower engineers, geoscientists, and decision-makers by unraveling the intricacies of fracturing software tools. Through rigorous analyses, it paves the way from raw data to informed decisions.
Boosting Offshore Uptime: Accurate Real- Time Sea State
Authors: Røstad J. , Aarset M. F. 
Published: November 2024

Abstract
Accurate, real-time sea state information is critical for ensuring the safety, efficiency, and economic viability of offshore operations. Traditional methods, often relying on distant forecasts or data from irrelevant water bodies, fall short in providing the precision required for effective decision-making and risk mitigation.
This paper explores the significant advancements in sea state measurement technologies, focusing on innovative methods adopted by early technology adopters. By leveraging advanced radar systems, analytics, and integrated sensor networks, these pioneers obtain precise, actionable insights into wave conditions directly from the operational site. Such real-time, location-specific data enhances the safety and efficiency of various offshore activities, from vessel navigation and stability to predictive maintenance and dynamic positioning systems.
The paper also delves into the critical role of accurate sea state information in the offshore energy industry. It examines the technological advancements in data acquisition and analysis, the integration of real-time monitoring systems, and the benefits these innovations bring to offshore operations. Case studies and practical applications demonstrate the superiority of these modern methods over traditional practices, highlighting the tangible benefits of improved vessel positioning, operational uptime, and overall safety.
By documenting these advancements and their practical applications, this paper aims to encourage the broader adoption of cutting-edge sea state measurement technologies within the maritime industry. Transitioning from outdated methods to precise, modern techniques marks a significant step forward in enhancing the safety, efficiency, and reliability of offshore operations.