bluuebunny/crossref_metadata_2025_split huggingface dataset:
Successful Application of Innovative Well Intervention Technologies to Effectively Stimulate Extended Reach Wells
Authors: Alsubaie F. A. , Afif O. T. , Duthie L. S. , Harthi M. A. 
Published: October 2024

Abstract
Well interventions with coiled tubing (CT) have played a vital part in increasing well productivity. CT intervention challenges in 2.25" highly restricted extended reach wells demand technological solutions, excellent planning and in-place tailored procedures.
Fluid placement and effectively maximizing reservoir contact are critically important elements during CT interventions for open-hole matrix acid stimulations. Fluid delivery was accomplished with multiple extended-reach techniques, including concentration of friction reducer and volumes, contributing to extending the reach. Technologies such as CT tractors and agitators to increase the reach were selected after considering their performance in the wells. A specially tapered CT string was also employed in the field. Effective fluid placement was achieved through distributed temperature sensing (DTS) providing a real-time optimized pumping schedule.
The CT simulator predicted the CT lockup depth to within 5% of actual depth reached for the CT interventions. This allowed for proper selection of downhole tools and planning of fluid volumes to operate the hydraulic downhole tools. One of the most effective practices was cleaning the wellbore casing shoe with a high-pressure jetting tool (HPJT) to clean any organic or drilling materials, leading to a reduced friction coefficient. This HPJT run increased the reach by an average of 23%, and also reduced the operation time during the stimulation by 15%. Real-time tension-compression information from the bottom-hole assembly assisted in estimating the lockup depth and provided confirmation of the extended reach tool activation. The ERW's open-hole coverage was maximized, delivering an increased well productivity on every intervention.
These engineered solutions illustrate the potential for CT interventions in extended-reach horizontal wells to move the dial and contribute to well productivity. Continual innovation and introduction of new technologies not only play a key role in meeting objectives, they are essential for constantly pushing the boundaries in these ultra-challenging well conditions.
Automated Steering Tendency Estimation for Steering Ellipse Derivation
Authors: BA Samba , Omr Medhat , Mansour Darine , Sahli Hussein , Goel Prateek 
Published: October 2024

Abstract
With directional drilling being a major activity during well construction, using the industry 4.0 platform (Vaidya Saurabh 2018) to transform the operational aspect of well construction represents great risk and reward scenarios for proper planning and execution. In effect, the directional drilling process has grown in efficiency and complexity with a move to more and more 3D horizontal wells. This means that delivering consistent and efficient steering performance can be very tricky.
In this paper, the emphasis is put on an automated steering tendency estimation which is paramount for deriving efficient steering commands to meet trajectory targets without compromising on hole quality goals. In particular, we show a steering ellipse derivation for all rotary steerable system (RSS) downhole steering modes in real time (RT) and how it is used to understand the performance of the downhole controllers and adjust steering parameters accordingly automatically.
After examining what steering ellipse tendency estimation is and giving examples of steering tendency ellipse for different steering modes, a field application of this is discussed and it shows significant improvement in wellbore quality with lower tortuosity index.
Enhancing Oil and Gas Field HSE Training Through Virtual Reality
Authors: Adel A. , Elnogomi A. 
Published: October 2024

The oil and gas industry, integral to the global economy, is inherently fraught with risks and hazards that pose significant threats to worker safety and operational efficiency. Given the high-stakes nature of this sector, rigorous Health, Safety, and Environmental (HSE) training is paramount. Traditional training methods—typically consisting of classroom lectures, instructional videos, and on-site demonstrations—while essential, often fall short in delivering comprehensive, immersive experiences that mirror real-world scenarios. Virtual Reality (VR) technology represents a transformative leap forward in enhancing HSE training, offering unprecedented levels of immersion, realism, and safety.
This manuscript explores the profound impact of VR on HSE training within the oil and gas industry. It provides an in-depth analysis of the technology's benefits, practical applications, and successful case studies. Moreover, it examines the complementary roles of Augmented Reality (AR) and Mixed Reality (MR) technologies, highlighting their potential to further elevate training outcomes.
Improve Imaging of Pre-Messinian Targets Through FWI and RTM in the East Mediterranean Region, Case Study
Authors: Darwish Tamer , Kumar Jyoti , Bell Marcus 
Published: October 2024

ABSTRACT
The Eastern Mediterranean region has substantial hydrocarbon potential, marked by proven Jurassic/Cretaceous oil and gas reserves, Pliocene Nile-sourced sandstones, and the potential for Pre-Messinian carbonate buildups analogues to the Zohr discovery. Even though, the thickness of the post-Messinian section is generally limited in the Eastern Mediterranean region but the presence of the Messinian heterogenous evaporites introduce significant velocity contrasts in the overburden, which needs to be addressed to improve the image of the Pre-Messinian targets.
Accurate imaging of the Pre-Messinian targets faces several challenges, including correctly illuminating the sub-salt section and understanding of the interaction between clastic sediments and Messinian evaporites. This involves capturing the necessary velocity details of the heterogeneity within the Messinian evaporites and addressing illumination issues arising from the complex relief of the Messinian layer, including optimizing acquisition parameters (Kumar et al., 2022).
Optimizing the depth velocity model building process necessitates the application of advanced imaging technologies such as Full Waveform Inversion (FWI) and Reverse Time Migration (RTM) (Brandsberg-Dahl et al., 2017).
This paper proposes solutions for diverse overburden challenges to enhance the Pre-Messinian image. The results from this work demonstrate that the suggested VMB workflows including the application of FWI and RTM have been successful in capturing the majority of Post-Messinian and Messinian complexities, thereby improving the image of the Pre-Messinian target.
We present data examples from recent seismic surveys in the Eastern Mediterranean to demonstrate these novel solutions. Along with improved subsurface imaging, these recent seismic data could provide the interpreters with necessary input for a better understanding of potential high-quality reservoir facies.
Digital Twin: New Back Allocation Algorithm Based on the Maximum Likelihood Principle
Authors: Ishmuratov R. , Maslennikov D. , Guzhikov P. 
Published: October 2024

Abstract
The rapid advancement of digital technologies in the oil and gas sector has led to the development of innovative solutions for optimizing production and enhancing asset management. One such solution is the Digital Twin, a dynamic, real-time digital representation of physical assets. This paper introduces a novel back allocation algorithm for gas and gas condensate fields based on the Maximum Likelihood Estimation (MLE) principle, integrated within the Digital Twin framework.
The core thesis of this paper is the application of the MLE principle to the back allocation of fluids to wells and reservoirs, solving this task with the highest possible likelihood. The MLE-based approach allows for precise determination of fluid origins, pinpointing the specific wells and even the intervals within those wells, including the detailed component content.
For the MLE algorithm to function correctly, robust fluid characterization is essential. This involves comprehensive compositional grading and the use of Equations of State (EOS) to model fluid properties accurately. Understanding the compositional distribution from the output to the input, along with knowledge of how composition changes with depth and phase behavior at every node in the system, is crucial for achieving accurate back allocation using MLE.
Key aspects of the Digital Twin and MLE-based back allocation algorithm include:
Accurate Fluid Allocation: Determining the most probable production rates and fluid origins by adjusting parameters such as flow rates, fluid compositions, and equipment dimensions to minimize deviations. Compositional Grading: Utilizing detailed compositional data to understand how fluid properties change with depth, which is vital for accurate modeling and allocation. Equation of State (EOS) Models: Employing EOS models to accurately describe fluid phase behavior under various conditions, providing the necessary data for the MLE algorithm to function effectively.
This integration of MLE within the Digital Twin environment enhances the accuracy of production allocation, leading to significant improvements in operational efficiency and economic performance. Case studies from gas and gas condensate fields demonstrate the algorithm's capability to optimize production allocation, reduce operational risks, and enhance overall asset management.
This paper will detail the technical aspects of the MLE-based algorithm, the importance of fluid characterization and EOS models, and the resulting benefits in terms of production optimization and economic gains. The findings suggest that adopting this advanced back allocation approach can lead to substantial improvements in field development strategies and operational efficiency.
No Risk, No Reward: A New Era of Risk-Based Hydrate Management for Gas-condensate Developments
Authors: Sherrard C. J. , Poursanidis K. , Georgis M. , Golczynski T. , Hamilton S. 
Published: October 2024

Abstract
The integration of digital solutions, engineering expertise, operational knowledge, and advanced laboratory testing is unlocking value in stranded assets. By assessing the unique fluid properties and operating conditions of each asset, cutting-edge technologies, laboratory analyses, and modeling techniques can be leveraged to quantify hydrate formation and plugging risks in economically marginal gas- condensate fields. Hydrate management strategies have facilitated the development of numerous projects worldwide that were previously considered unviable due to economic and technical challenges. While there is extensive literature on risk-based hydrate management approaches for oil systems, this paper focuses on the emerging application of these strategies in gas-condensate developments.
Collaborations with leading flow assurance laboratories and academic institutions enable quantification of hydrate risks associated with a project. By analyzing the critical factors for stable hydrate formation, these developments gain an additional layer of confidence, enhancing their attractiveness for investment. Utilizing the latest hydrate kinetics software embedded in OLGA (e.g., UWA, CSMHyk) provides a more pragmatic approach to subsea design for hydrate management. The insights and methodologies shared in this paper demonstrate leadership in flow assurance, guiding the implementation of effective solutions and driving future growth and optimization of production processes.
Furthermore, this paper emphasizes the importance of a robust hydrate remediation strategy to minimize production deferment due to hydrate blockages. It highlights the need for upfront investment in critical infrastructure to ensure the swift and efficient resolution of any blockages that may occur throughout the field's life.
Enhanced Machine Learning Modelling Techniques for Better Classification of Carbonate Reservoir Rocks
Authors: Hamada G. , Al-Khudafi A. M. , Al-Yazidi A. T. , Al-Sharifi H. A. , Al-Qadhi T. , Al-Gathe A. A. 
Published: October 2024

Abstract
This study aims to enhance machine learning models for classifying carbonate rocks into limestone and dolomite using well logging and core analysis data. The research evaluates various machine learning algorithms' performance and identifies effective techniques to improve model accuracy for geological and environmental applications.
The study employed several strategies to improve classification models, including grid search, random search, Bayesian optimization, SMOTE, and ensemble techniques (boosting and bagging). A dataset of 4290 points was used to train eight different classification models: Random Forest (RF), Multilayer Perceptron (MLP), Naive Bayes (NB), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Radial Basis Function (RBF), Regression Tree (RT), and Parallel Additive Regression Tree (PART).
All implemented strategies significantly enhanced the machine learning classification models, achieving a correlation coefficient near one and a mean absolute error of 0.16 averaged across all techniques. Random Forest and Multilayer Perceptron demonstrated exceptional performance, with accuracy rates of 99.2% and 98.7%, respectively. The Kappa statistic further confirmed the superiority of these models. The study highlights the importance of selecting appropriate machine learning models and optimizing their hyperparameters for effective carbonate rock type classification. The findings underscore the potential for improved accuracy through ensemble methods and hyperparameter optimization in geological classification tasks.
This research provides new insights into applying machine learning techniques for geological classification, particularly in carbonate rock type identification. The results have significant implications for developing more accurate and reliable classification models in geoscience applications, potentially improving various geological and environmental studies.
Monitoring the Liquid Level of Shale Oil Well Through EM Telemetry, a Case Study
Authors: Chen Qiang , Jia De-li , Sun Fu-chao , Hao Zhong-xian 
Published: October 2024

Abstract
Shale oil had been invested heavily in China, as exampled by Daqing oil field, Xinjiang oilfield and so on. The liquid level of shale oil well was generally tested through acoustic means at the wellhead. This method was not accurate due to factors such as the wax, dead oil and well deviation, incorrect data led to the wrong development strategy or even downhole pump damage.
In this paper, downhole telemetry was raised based on EM transmission, its working principle was discussed. Relevant tools were manufactured based the principle, field trial was also completed in the oilfield.
EM had been familiar to us for the purpose of communication, but its application downhole was a complete different scenario due complex electric conductivity environment. We explored the downhole EM transmission mechanism and developed the tubing-casing-subsurface channel model, low frequency EM source at the tubing could pass through casing to enter the reservoir and be detected on the ground. To turn the theory into reality, we designed the telemetry system including the modules of electric circuit, coil, metal centralizer and receiving device. Electric circuit could modulate the pressure data into low frequency alternative current and pass it to the coil module. Under the effect of alternative current, the coil module would induce magnetic field on the tubing with the pressure date. EM signal could flow along the path of metal centralizer and penetrate the casing to enter the subsurface, the receiving device could detected the voltage potential between wellhead and ground, its precision was microvolt level. Downhole liquid pressure monitoring gauge was manufactured and tripped into shale oil well up to 1466m to gain the knowledge of liquid level. The signal attenuated as the gauge went deeper but was still 1.5 times of noise at the bottom of well. The gauge helped the operator monitor the change of liquid level and took relevant measures accordingly if the change was abrupt.
This paper prescribed the application of EM into downhole liquid level monitoring. We shared the experience with our counterparts and helped the expansion of downhole telemetry technology.
Delivering Wells Without Backreaming: Implementation of High-Performance Water Base Fluid System with Highly Inhibitive Triple Mechanism in Unconventional Wells in The UAE
Authors: Al Menhali Shamsa , Anez Marcos , Marzouk Ahmed Mortadi , Khatib Faiz 
Published: October 2024

Abstract
A customized high-performance water-base fluid system was used to drill intermediate sections in an unconventional gas field located in Abu Dhabi, UAE. The customized system with a highly inhibitive triple-mechanism was used to drill troublesome shale formations achieving high rates of penetration without any bit-balling or shale related incidents. One challenge commonly faced while drilling these formation is the excessive back reaming required while tripping out of the hole. However, the superior performance of the fluid system ensured that tripping out of the hole was achieved by using only elevators, without any backreaming, saving a significant amount of rig hours. This paper discusses the design, implementation and results obtained by implementing customized high-performance water base systems to drill troublesome shale formations in six wells in the unconventional gas field.
Improved Regional Geological Understanding And Impact On The Hydrocarbon Prospectivity Of The West Mediterranean, Egypt
Authors: Hamilton M. , Gewaily A. H. , Khattab M. , Hussein M. , Mahran N. , Basher K. , El Mahdy M. , Elokazy M. 
Published: October 2024

Abstract
Egypt's west Mediterranean is a truly frontier basin in terms of hydrocarbon exploration, however, continued seismic data acquisition and exploration drilling scheduled for 2024/2025, is driving the region towards becoming an exploration hotspot. Regional 2D seismic data and a 24,000 sq km merged 3D seismic volume have recently been supplemented with two additional broadband 3D seismic volumes. Along with improved imaging, these recent seismic data allow interpreters to focus on stratigraphic elements and have more confidence in structural interpretation compared with 2D limitations.
The larger of the new multiclient 3D seismic surveys is located on the northwest of the offshore Nile Delta cone and west of the Rosetta fault trend, connecting the west to the more mature Nile Delta understanding and also having a direct tie to the Kiwi 1 well. The subsurface imaging is challenging, with complexities such as both dirty and clean evaporites as well as shale intrusions and extrusions being present. These challenges have been addressed using high-end depth imaging workflows. In the final 3D seismic volume, it is possible to extract spectacular channel systems in both Post and Pre-Messinian evaporite sections, using various seismic attributes, providing the interpreters with a better understanding of where high-quality reservoir facies may be located. Primary targets in this area are likely to be Oligo-Miocene clastic reservoirs in combination stratigraphic-structural traps, with secondary targets in the Pliocene shallow section.
In contrast, the second new multiclient 3D seismic survey is located far to the west and almost entirely on the shelf. These surveys are however linked by a large 3D merge volume, which allows the explorationists to have an excellent regional geological context. The new survey is extremely close to the Sidi Barrani 1 well, which was drilled on 2D data, and is thought to have failed due to poor trap definition. This is something the new 3D KPSDM depth seismic volume addresses, allowing explorers to better image and define traps in the area. Targets in this survey are most likely to be Jurassic and Cretaceous clastic reservoirs in structural traps.
Improved regional understanding has been achieved using these seismic data and this work highlights some of the imaging complexities and prospectivity using relevant seismic examples.
Effect of Knowledge of Bubble Point Pressure on Estimating PVT Properties from Correlations
Authors: El-Banbi Ahmed H. , El-Maraghi Ahmed 
Published: October 2024

Abstract
PVT properties are needed as input data in all reservoir, production, and surface facilities engineering calculations. In absence of PVT reports on valid reservoir fluid samples, engineers rely on PVT correlations to generate the required PVT data. Accuracy of PVT correlations vary and no correlation group has been found to provide accurate results for all oil types. The effect of inaccurate PVT data can be significant in engineering calculations and is well documented in the literature. Bubble point pressure can be sometimes obtained from external sources. In this paper, we show how to utilize the known bubble point pressure to improve the accuracy of calculated PVT properties from correlations.
A systematic study using around 250 reservoir oil samples was conducted to quantify the effect of pre-knowledge of bubble point pressure. The samples spanned a wide range of oils from very volatile oils to black oils and all the way to low-GOR oils. A method for shifting both undersaturated and saturated sections of the PVT properties curves to the correct bubble point is explained. Seven PVT correlation families were used in this study. All PVT properties (e.g. solution gas-oil ratio, formation volume factor, density, viscosity, and compressibility) were calculated using the correct bubble point pressure and the correlation estimated bubble point pressure. Comparisons between the calculated PVT properties, and actual laboratory measured values were made. It was found that pre-knowledge of bubble point pressure and using the shifting technique presented in the paper, improved the correlation-estimated values up to more than 30%. The most improvement was seen in solution gas-oil ratio and oil formation volume factor.
A technique to improve the accuracy of PVT properties derived from correlations was introduced. It improves the accuracy of all derived PVT properties for oil with variable degrees.
Driving Operational Excellence in Oil Gas Sector ETHYDCO Innovative Pi System Integration
Authors: AFIFI M. T. 
Published: October 2024

The Petro-chemicals industry is a special industry. All transactions and data processes must be comprehensively managed. Such includes reliable equipment, if it is a failure not only cost money (maintenance man hours or Spare parts inventory) but also the maintenance downtime of the job rates directly impacts production and reflects on company sales. Saving energy: Sources from operation systems that generate energy (E.g., Steam, fuel gas, heat transfer) decrease the amount wasted as long as they are cycled back together (or treated). Thus, energy utilization can be decreased in all respects. Human safety and compliance A data management system that is not a real-time insight platform or intelligent All this inevitably leads to a potential increase in the operator's operational costs (maintenance, etc.).
A leader in the Egyptian petrochemical industry, ETHYDCO is committed to achieving operational excellence and thus retaining its competitive edge in this field. Its strategies include raising the level of productivity, saving some energy costs, decreasing overall operating costs, and adopting cutting-edge technologies which led to efficiency gains over time as well as promoting sustainable development.
To address these issues, ETHYDCO has adopted the PI System, an industry-proven performance monitoring system. The strengths of the PI System are in wide data collection and acquisition possibilities, real-time storage of data from different sources and constant data analysis that may help to monitor operations, detect the signs of wear out facilities and equipment, and thus may help in decision making process.