bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel 5S Workflow for Production Optimization and Water Management
Authors: Abbas A. , Mascagnini C. , Telang V. N. , Chughtai M. A. 
Published: November 2024

Abstract
Water production can single handedly jeopardize the life of a field unless it is managed adequately and timely. Water management must be a continuous process primarily mapped into three phases- diagnostics, technology screening and field execution, to ultimately optimize water influx and maximize hydrocarbon production while optimizing cost and maximizing operational efficiency.
A systematic water management workflow comprising five stages (5S) was crafted. The initial stage entails analytical screening to pinpoint fundamental concerns across the field. Subsequently, the second stage delves deeper with well-level analysis, creating models to replicate production history. The third stage evaluates viable solutions and their feasibility. Next, a pilot implementation of the chosen technology occurs in a selected well, with performance closely monitored in the fourth phase. Finally, scaling up the solution to a cluster of analogous wells assesses the field-wide production gains achieved through controlled water production.
Heterogeneity Index (HI) analysis involves comparing individual well performance with the average performance of its group over time. Utilizing HI, a study examined ~191 wells within a major oilfield to identify 70 underperforming wells based on trends in oil and water production. Among these, 30 wells were pinpointed as potential candidates for water shut-off following comprehensive well-level analysis. Evaluation suggested that successful water shut-off operations could potentially increase production by ~3000 barrels of oil per day (bopd). The methodology underwent pilot testing in a well. Post-shut-off results demonstrated a significant decrease in water cut (20%) alongside an oil production increase of ~150%. Following the successful pilot test of the water shut-off technology, scaling up to the field level occurred, deploying it at 12 analogous wells. This resulted in controlled water production at 15% and a net increase of 170% in oil production.
The analysis of production and injection data serves as the primary method for identifying the root cause of water production, guiding the water management strategy. The innovative five-stage workflow offers an integrated approach that encompasses reservoir characterization, analysis of well performance, review of completion design, assessment of treatment programs, and execution of solutions.
Transforming Oil Production Efficiency: A Rigless ESP Intervention Approach
Authors: Li Qijun , Zhao Mengpan , Hong Yuandong , Zhang Li , Xue Fan , Dai Rui 
Published: November 2024

Abstract
The global oil industry faces ongoing challenges in maintaining and enhancing production efficiency, particularly in mature fields. Traditional intervention methods for Electric Submersible Pumps (ESPs) often involve significant downtime and high operational costs due to the need for rig-based interventions. This paper explores NOVA Rigless ESP intervention approach, highlighting its potential to transform oil production efficiency. By examining case studies and field applications, we demonstrate how this innovative method can lead to substantial improvements in operational efficiency and cost savings. The findings suggest that rigless interventions not only reduce downtime but also enhance overall production performance, presenting a viable alternative to conventional techniques.
Application of Machine Learning in Downhole CO2 Measurement Using Formation Tester
Authors: Kumar Nishant , Turki Anis , Dai Bin , Yaakob Amirul Afiq B 
Published: November 2024

ABSTRACT
The reservoir fluid composition measurement can provide great insight for petrophysical interpretation, geochemical analysis, and fluid phase behavior. Laboratory analyses of downhole fluid samples have historically provided much of this required compositional data. The delay in providing this critical information for decision making typically ranges from weeks to months. By the time evaluation occurs, the opportunity to acquire additional samples is lost, and any ambiguities regarding the sampled fluids may not be resolved. Characterizing reservoir fluid in-situ and in real-time by means of wireline formation testers (WFT) can enhance formation evaluation and sampling programs. However, direct single station fluid compositional analysis measurements by WFT have historically been limited to gas components C1-C5 and bulk oil C6+.
Downhole quantification of Carbon dioxide (CO2) with formation tester is gaining increasing interest with the different challenges involving monitoring of CO2 content in reservoir fluids. This covers Enhanced oil recovery (EOR) and CCUS monitoring as part of reservoir surveillance among other applications. This paper presents application of downhole fluid analyzer in benchmarking real-time CO2 composition with the utilization of informed machine learning algorithm.
On-Edge Implemented Machine-Learning Based Synthetic Flame Detector for Gas Turbine Operation
Authors: Gori Valentina , Goyal Kanika , Roma Tiziano , Bagni Gianni , Carta Riccardo , Giunta Bruno , Tonno Giovanni , Magistris Giovanni De 
Published: November 2024

Abstract
We have successfully designed and implemented a cutting-edge data-driven flame detection system for gas turbines using a 55-parameter feed-forward neural network. This simple neural network model receives as input seven distinct physical quantities measured at various locations within the turbine, such as fluid temperature, pressure, flow rate, and shaft speed. Basically, a digital twin of the physical flame detector has been developed, which allows to replace the sensor and obtain a more cost-efficient, low-maintenance and accurate solution. The neural network has been integrated into the machine control system (MarkVIe) through edge device implementation, enabling real-time synthetic flame detection. The model has demonstrated exceptional performance, achieving 100% recall and 100% precision on an independent test dataset. Future enhancements will focus on integrating the model onto a MarkVIs device, an enhanced version of MarkVIe specifically designed for managing security-related machine controls automatically, allowing for the closure of the control loop and further optimizing the flame detection process.
Artificial Neural Networks for Optimization of Natural Gas Flow Through Surface Well Chokes
Authors: Ahmed Ashraf , Mahmoud Ahmed Abdulhamid , Elhaj Murtada A. , Elkatatny Salaheldin 
Published: November 2024

Abstract
Optimizing natural gas flow through surface well chokes is critical for maximizing production efficiency and ensuring reservoir integrity. Traditional methods, such as empirical correlations and mechanistic models, often struggle to accurately predict flow rates due to the nonlinear and dynamic nature of gas flow. This paper explores the application of artificial neural networks (ANNs) as a data-driven approach to optimize gas flow through surface well chokes, empirical equation was also developed based on the optimized ANNs model. The ANN model was trained using a comprehensive dataset and then validated against unseen data. The results demonstrate that the ANNs model accurately predicted the gas flow rate for the training data. Additionally, the trained ANNs model was used to derive a predictive equation that can be applied in real-time operations, providing accurate and reliable recommendations for choke settings. The gas flowrate was predicted for the validation data set using the developed equation with a high accuracy, the average absolute percentage error was only 3.77% and the room mean square error was 0.28 MMscf/day. This extracted equation, derived from the ANN model, offers a practical tool for field engineers, enabling them to make informed decisions to optimize natural gas flow. This study highlights the potential of ANNs to enhance the optimization of natural gas production processes, offering a robust alternative to traditional methods. The findings suggest that integrating ANNs-based model and equation into well management practices can lead to significant improvements in operational efficiency and economic outcomes, marking a step forward in the digital transformation of the oil and gas industry.
Mega Hydraulic Fracturing Operations with Innovative Efficiency Transformation
Authors: Alhosani N. , Al Shehhi H. , Refaei A. , Alzaabi A. , Alyafei S. , Alrashdi A. , Al Shamisi E. , Bin Shamlan A. , Ryan A. 
Published: November 2024

Abstract
As United Arab Emirates (UAE) has untapped the unconventional resources, various studies have been implemented based on the uniqueness of resources and the operational challenges. As widely known, unconventional resources are closely related to operation efficiency to provide economical values to the shareholders. Earlier in 2024, a transformative plan to develop unconventional resources was launched. An unconventional resource transformative plan involves strategic development and utilization of non-traditional energy sources from carbonate source rocks to meet growing energy demands while reducing cost and environmental impact. This approach focuses on innovative hydrocarbon extraction technologies, such as multistage hydraulic fracturing on horizontal well, alongside sustainable practices that reduce carbon emissions. The plan aims to diversify energy portfolios, enhance energy security, and support economic growth by tapping into these abundant but technically challenging resources. By integrating advanced research, regulatory frameworks, and community engagement, the plan seeks to balance the benefits of unconventional resources with the need for environmental stewardship and social responsibility. Unconventional resource ramp-up plans outline a strategic approach to scale up operations to efficiently access these challenging reserves.
This paper introduces transformative approaches to hydraulic fracturing in the UAE, emphasizing efficiency, cost reduction, and sustainability in unconventional resource operations. The efficiency project began with industry alignment, encompassing organizational behavior, drill-to-fracture well construction, operational practices, and the logistical environment. It extends to well engineering details that incorporate efficiency enablers.
All these plans are currently being implemented in the project ramp up phase during various multi-year roadmaps, introducing a groundbreaking approach that successfully balances subsurface challenges with economic value. As these strategies are put into action, the project is already demonstrating enhanced efficiency in resource extraction and significant cost reductions. Economically, the project is achieving its goals of maximizing resource utilization. These early successes highlight the effectiveness of this new approach, setting a strong foundation for long-term sustainability and profitability in unconventional resource development.
Efforts to Return New Suspended Offshore Dry-Gas Wells to Production: First Successful of a Rigless Conversion Subsurface Safety Valve from Tubing Retrievable to Wireline Retrievable in Indonesia
Authors: Anggiat Wein , Pamungkas Bimo Arie , Athallah Fairuz , Xiaopo Liu , Weihao Bai , Fajarrenaningtyas Ursula , Daniswara Andhika 
Published: November 2024

Abstract
In July 2024, Husky-CNOOC Madura Limited (HCML) completed the protected bellows (PB) valve installation to two (2) wells and it was the first successful rigless conversion of tubing retrievable safety valve (TRSV) to wireline retrievable safety valve (WLRSV) at a new offshore dry-gas well in Indonesia. A PB valve, a WLRSV, was installed to reactivate a new suspended well that failed to produce in the startup phase. To investigate the root cause analysis, a slick line diagnostic operation was performed, and it was found that the TRSV was in a closed position with a malfunctioning flapper. Several strategies regarding safety, operational feasibility, lead time, and cost to reactivate the wells were assessed. It concluded that converting the TRSV to a WLRSV by installing a PB valve using slick line well intervention was the most feasible solution to reactivate and return the wells to production in the shortest time. Based on current date well observation, the PB valve has performed very well, allowing the well to flow up to 20 MMSCFD and successfully making HCML the largest gas producer in East Java – Indonesia with a total gas production rate of 300 MMSCFD. These results showed that WLRSV can be utilized in mature and green fields and proves to be the most effective and operationally efficient to replace troubled TRSV function in new offshore dry-gas wells. This also means that the option of workover was not always the answer for subsurface safety valve issues, since PB valve installation to convert TRSV to WLRSV has proven to be a cost-effective option. Another advantage of PB valve installation is that it eliminates potential reservoir damage during the killing of wells and well loss due to problems of retrieving old tubing with a workover unit. In addition, PB valve installation as a slick line well intervention can solve small footprint issues and load restrictions on offshore platforms, i.e. small-unmanned platforms, due to the lightweight of the slick line well intervention equipment. This paper intends to share how to reactivate the new suspended offshore dry-gas well due to troubled TRSV by installing PB valve as WLRSV and document invaluable lessons learned, workflow, and best practices for society as well as for reference of other researchers and companies.
Assessing the Effectiveness of Image Hashing and Vector Databases in Improving the Detection of Financial Statement Fraud in the Oil and Petroleum Sector
Authors: Albuqaytah Dalia , Tharayil Sarafudheen , Idris Muhammad Azmi 
Published: November 2024

Abstract
Financial statement fraud in the oil and petroleum sector poses a significant challenge, necessitating advanced detection methods. This study evaluates the effectiveness of integrating techniques from Approach 1 and methods from Approach 2 to enhance fraud detection in scanned financial documents. The research addresses limitations of existing rule-based algorithms by adopting a novel hybrid approach. The methodology incorporates an encryption technique to generate unique cryptography for document images, enabling fraud evidence identification through cryptography comparisons. This is complemented by generative AI and deep learning techniques to refine the filtering process and uncover hidden fraud patterns. The training dataset is enriched with various fraud combinations, and the model's performance is assessed using established metrics. Post-processing involves employing image fuzzy logic to mitigate potential inaccuracies. Results indicate that this integrated approach significantly surpasses traditional image processing techniques in both accuracy and detection speed. The deep learning AI component demonstrates particular efficacy in identifying concealed fraud patterns within scanned documents. Furthermore, the model's ability for continuous learning enables adaptation to emerging fraud patterns through periodic retraining with updated document sets. The study's novelty lies in its systematic evaluation and comparison of combined traditional and advanced AI techniques for fraud detection in the oil and petroleum industry, addressing a critical research gap. The implementation of an AI-driven learning mechanism for ongoing refinement further enhances the model's maturity and accuracy over time, contributing to the establishment of a robust and adaptive fraud detection system. This research constitutes a notable contribution to the field of financial fraud detection, presenting a promising avenue for enhancing security and integrity in financial reporting within the oil and petroleum sector.
Challenges and Mitigations in an End to End Well Test Validation Work Process Post Integrated Smart Field Asset Model Implementation
Authors: Alhammadi Rashed , Albadi Mohamed , Alsaeedi Ayesha , Alzeyoudi Mohamed , Alharethi Fahed , Alhammadi Maryam , Elabrashy Manar , Konkati Sarath , Alsenaidi Shemaisa , Mathur Avnish Kumar , Jani Mansi , Siddiqui Sameer 
Published: November 2024

Abstract
This paper will demonstrate the challenges faced by the end users in utilizing the well test validation end to end workflow within the integrated production platform. Therefore, along with the validation of the large number of well tests on daily basis, seamless sync of bi-directional data flow between the corporate database and asset optimization tool is challenging and critical.
The closed-loop well test validation workflow was implemented to overcome the challenges of disconnect between the corporate database and the asset optimization tool. In this automated workflow. Within this process, the well tests are fetched from the corporate database then automated validation is performed within the asset optimization tool. The validation status is written back to the corporate database. This bi-direction data flow requires a proper and precise sync between the scheduler of both the corporate database and the asset optimization tool. The user-defined dashboard was created to highlight the misalignment/ broken loop in real-time.
It was observed that the writing back of the validation status to the corporate database was broken. The cause of the issue was identified as the change in the scheduler time of the corporate database which broke the sequential automated schedular task of the asset optimization tool.
As a result, the disconnect between the corporate database and the asset optimization tool was highlighted on a real-time basis. This reduces the system downtime, and manhours spent on troubleshooting. It has also enabled users to utilize more efficiently the data management (like validation status of Well test), It also creates an environment of a single source of record (SoR) thus enabling utilization of the more accurate and validated data by the different departments within a large asset. This resulted in maintaining an overall higher Well Test KPI %.
A process was established in collaboration with the stakeholders from the corporate database to identify this gap in the sync process. The required changes in the sequential schedular time were made. Both the servers are in sync to update the well test changes, any change in either of the server would affect the other.
Incorporating the manage by exception philosophy with the closed loop well test validation workflow aligns with the corporate vision of using an integrated asset operation Model (IAOM) for providing end users tremendous opportunities related to system optimization and empower the engineer to process bulk data rapidly. This also supports the user's drive of standardized process orientated.
Best Practices Implementation for Monolithic Isolation Joints on Ultra Sour Gas Applications
Authors: Medina Antonio , Al Shamsi Fatma , Al Ameri Mohamed 
Published: November 2024

Abstract
Monolithic Isolation Joints (MIJ) are widely used on pipeline systems to electrically split the line into two (2) sections for Cathodic Protection (CP) coverage delimitation, as example.
Failure of two MIJ are investigated for the gathering system handling ultra-sour gas multiphase fluid from ADNOC Sour Gas field, containing more than 23% H2S and 10% CO2 and operating at 90 °C and 93 barg conditions (design data: 118 °C and 96.5 barg).
The testing aimed to assess the mechanical and chemical properties of the materials to identify any detrimental situation contributing to the failure. The results indicated that metallic sections of the MIJs did not contribute to the failure of the joint. Instead, the non-metallic components within the joint were identified as the source of the leak, with Glass Reinforced Epoxy (GRE) gasket material showing signs of degradation due to exposure to the ultra-sour service conditions.
It was found that the GRE gasket material showed inadequate thermal resistance, likely due to manufacturing deficiencies such as insufficient curing, was a primary factor in the degradation observed. To prevent such issues, it is recommended to use materials with higher thermal ratings, such as ASTM D709 G11, which offers a nominal thermal resistance of 140 °C, and to implement meticulous quality control measures throughout the manufacturing process.
The O-rings have been significantly compressed and exhibited cracking after one (1) cycle of decompression which is classified as premature considering resistance required as per ISO 23936-2. Selected FKM materials were found not suitable for long-term aging resistance to the service conditions. Literature [8,9] reflects a suitable compatibility by utilization of FFKM elastomer to the intended service.
Material selection is a crucial aspect to ensure optimal performance, and it is equally critical to implement stringent quality control and assurance throughout the manufacturing process. This dual focus guarantees that the materials not only meet the nominal requirements but also exhibit minimal variance, thus preventing potential failures and ensuring reliability.
An Approach to Safely Install Tie-Back Casing String in Workover Operations Having Existing Lower Completion by Utilization of V0 Stage Tool
Authors: Bukhari Abuzar , Marwat Qaisar Khan , Mohamad Abdul Salam Awad , Al Reyami Mazin 
Published: November 2024

Abstract
The paper illustrates a novel approach for Tie-back casings installation in Workover operations scenario where lower part of the wellbore may have limitation due to pre-installed lower completion or a complex well profile. The conventional approach for Tie-back casing installation contains high risk or is inapplicable in Workover application with existing lower completions. Therefore, cementing technique for Tie-back casing using a V0 stage tool presents a fit to purpose solution to a unique problem in industry. Since the technique addresses a fundamental application of tie-back casing running therefore its utilization can have a worldwide impact in similar applications in petroleum industry.
Development of presented approach is through the process of lesson learnt & continuous improvement. In conventional tie-back cementation, a barrier plug (float equipment / cement plug / bridge plug) is utilized as a base to circulate up cement behind tie-back casing. However, the conventional scenario changes for a workover well where lower completion is pre-installed and cement plug or bridge plug cannot be set due to the risk of clogging downhole completion tools. In such cases, V0 stage cementation approach for tie-back casing provides an optimum solution to minimize the risk of downhole completion tools damage and securely achieves the well objectives.
The technical advantage lies in minimizing the risk of cement sinking into lower completion and minimizing the drill out debris generated & sunk in hole from landing collar in comparison to a permanent bridge plug or cement plug. In addition to the technical benefits, the overall job process is streamlined by removing additional trips for bridge plug or cement plug placement, equivalent to an average saving of a half day to two days of Rig time and associated cost.