bluuebunny/crossref_metadata_2025 huggingface dataset:
First Multi-Zone Drill-Stem Test in the UAE Improves Operational Efficiency and Enhances Value of Information
Authors: Hassan Ahmed , Nuriakhmetov Ruslan , Al Hajri Saeed Salem , Sayed Sohdy , Belova Natela , Abdelmawgod Ahmed , Alloghani Jasim Ali , Sarac Sukru , Mugundan Mahidara , Radwan M. Sherif
Published: November 2024

Well testing is a critical stage of reservoir characterization. If not optimized, drill-stem tests (DST) can be time consuming when testing multiple formations in a well. This paper presents a case study for the first dual-zone DST performed in the UAE, to test 2 different zones individually in one single DST run. Significant operational efficiency gains, DST string design with multiple pressure gauges, multiple packers and wirelessly activated downhole tools will be explained.

In standard DSTs, non-value-added time such as running in hole, pulling out of hole, pressure testing the DST string and others can take 50% of the total test duration and cost. Operator companies may also test wells with simple completion strings to save time, but such tests come with limitations such as difficult downhole sampling operation (if possible) and challenging well kill operations. A dual-zone DST with wirelessly controlled downhole tools enabled to test 2 different zones individually. Multiple pressure gauges with real-time data transmission were used to monitor operations. Wireless downhole valves have controlled flow from different zones individually and enabled commingled flow.

Significant efficiency gains were achieved, and multiple operations were enabled with this first dual-zone DST performed in the UAE. Two zones were tested successfully in one DST run using the dual-zone DST string. A combination of 2 different packers were set in the well to isolate two zones from each other. Each zone was opened to flow through the DST string individually by two wirelessly controlled downhole valves. Pressure and temperature responses from each zone were recorded by multiple pressure gauges for pressure transient analysis. Downhole fluid samples were also collected with the built-in samplers on the DST string. Compared to two separate standard DSTs, 21 rig days and associated cost were saved with the use of the dual-zone DST string. In addition, compared to well testing with a completion string, downhole shut-in for accurate reservoir characterization was enabled. Despite high wellhead pressures that sometimes prevent wireline entry in the wellbore, wireline runs were performed without having to kill the well, enabled by the DST tools. Well kill operations were carried out smoothly by placing the kill fluid in the tubing with the use of downhole circulation valve.

The first dual-zone DST performed in the UAE has changed the well test philosophy from testing wells with a completion string to testing with DST. Efficiency gains and new practices are explained in this paper and can be applied to all well tests with multiple zones to test and enable new well test methods to enhance the value of information from well tests.
Utilization of Innovative CO2 Swelling Elastomeric Cement Integrity Sleeve as a Novel Well Integrity Enhancement Solution for Underground CO2 Storage Wells
Authors: Osorio A. , Vliegenthart A. , Vos A.
Published: November 2024

As the world aims to mitigate the climate-changing effects of global warming, intergovernmental regulatory bodies increasingly focus on greenhouse-gas emission reduction by implementing environmental policies to phase down fossil-fuel utilization and develop sustainable energy sources as part of global energy transition efforts. While various greenhouse gasses are emitted from a wide range of natural and artificial sources, human-produced carbon dioxide (CO2) is the primary driver of climate change as it accounts for approximately 70% of global greenhouse gas emissions (Olivier et al, 2020).

Efforts to reduce greenhouse gas pollution from the atmosphere have led to significant advancements in Carbon Capture and Storage (CCS) technologies, which aim to inject CO2 in underground storage wells with non-permeable formations capable of safe and permanent downhole containment. Furthermore, CCS is widely regarded as one of the most effective ways to mitigate climate change as recent studies estimate it could reduce CO2 emissions by 20% before the year 2050 (Elkatatny, 2021).

The planning and execution of a comprehensive CCS well integrity strategy is considerably more complex than conventional well integrity practices commonly found in the oil and gas industry. The hydration of supercritical CO2 leads to multiple carbonation reactions producing elevated concentrations of carbonic acid (H2CO3), which can severely degrade a cement barrier in radial direction and cause longitudinal cement defects. Concurrently, cyclic pressure and temperature fluctuations during long-term CO2 injection can compromise casing-to-cement bond, causing a potential leak path through micro annuli. These factors may lead to gas migration and subsequent Sustained Annular Pressure (SAP) buildup on surface, increasing the risk of direct CO2 leakage into the atmosphere.

An innovative CO2 Elastomeric Cement Integrity Sleeve (C-ECIS) has been developed specifically for the purpose of SAP prevention and well integrity optimization in CO2 storage wells. Distinctly different to a swellable packer, the C-ECIS was designed as a slip-on seal for external installation onto downhole tubulars. It is comprised of a novel swellable elastomer which utilizes CO2 as the primary swelling fluid medium for its volumetric expansion. It permanently swells and seals a casing-to-cement microannular flow path immediately upon direct exposure to gas migration within the casing-to-cement microannulus.

The C-ECIS is a unique technological innovation with the potential to transform the industry's current approach to CCS well integrity planning due to its simplicity and reliability. This publication provides an in-depth overview of the technology, its qualification process, and current field implementation status.
Combatting Mercury Threat in Sustaining Asset Integrity for Offshore Production Facilities
Authors: Nazori Q. Muhamad , Hamdan M. , Zulfa Z. Ahmad , Hashim W. Wan , Jaafar R. , Ali Z.
Published: November 2024

Mercury production from reservoir is exceedingly challenging to predict, especially at the development stage of the project with limited data. Therefore, it poses operational challenges during production and may possess integrity risk to the assets and downstream buyer. This paper offers a comprehensive evaluation of product quality, integrity, and economic assessment for an offshore facility in managing elemental and solid mercury, which could impact the downstream system.

A comprehensive approach was undertaken, encompassing the analysis of historical production data, including mercury data, sampling and analysis, mercury partitioning simulation, pipeline partitioning simulation, integrity assessment, particles analysis, solid computational fluid dynamic (CFD) modelling, impact on product quality, and mercury technology screening. Historical and sampling data, along with future forecasts, were analyzed to develop scenario for the production facilities. Based on this, the elemental mercury partitioning and drop out was simulated throughout the facilities and the pipeline, comparing with the actual production data. The result was used for elemental and solid mercury integrity assessment for the facilities.

Study indicates there are no clear correlation between the gas and mercury production. For elemental mercury, partitioning study indicated that elemental mercury would partition into the gas phase and some of the elemental mercury would be partitioned into the liquid when there are changes in operating pressure and temperature in the processing and transport system in the offshore facilities. During transport of fluid in the pipeline, most of the elemental mercury would partition into the gas phase. The mercury is still within the downstream mercury removal unit and sales agreement specification. The particulates mercury will mostly be at the liquid side where a solid mercury removal unit (MRU) had been installed. However, sampling result indicated smaller particles had been produced from the reservoir compared to the design stage. Computational Fluid Dynamic (CFD) study was conducted to evaluate the behavior of the particles. Based on study finding, there is no evidence to suggest that there is a threat to the integrity of offshore facilities or cross contamination possibility to gas phase. As a result, there are no requirement to remove the smaller particulates as it does not pose erosion risk. In addition, there is limited technology available in the industry for removal of sub-micron particles.

This paper provides a holistic and systematic approach on evaluating the impact of changes on mercury production to the existing gas production facilities. Understanding of the integrity and product quality threat would direct the operation's management in making the right decision on the technology investment.
Complete Workflow and Case Study for Thermal Dynamic Simulation of Carbon Dioxide Storage in Depleted Gas Reservoirs
Authors: Rahman Shah Abdur , Golaco C. , Stashevsky V. , Shaykhattarov M. , Rat C. , Chepik E. , Hasan H. , Shady M. , Robert M. J. , Guerra J. , Stojic S. , Povstyanova M. , Bentaher A.
Published: November 2024

Using a case study from the Sajaa Field, onshore Sharjah, United Arab Emirates (UAE), we devised several workflows to set up a fully thermal dynamic simulation case for carbon dioxide (CO2) storage in a depleted gas reservoir.

The construction of the thermal dynamic model started with the setup of dissolution tables for CO2. A published dataset to model CO2 dissolution was used. This was followed by the setup of enthalpy tables for each component of the equation of state (EoS). The thermal capacity of the reservoir and caprock formations was also computed while considering the mineral composition of the rocks. Additionally, the thermal conductivity of the formations was calculated and corrected for formation temperature, considering the mineral composition of the formation as well as the saturation of the rocks.

A thermal dynamic model enables the user to capture several important processes while injecting CO2 in a depleted gas reservoir. These processes include the wellbore changes of temperature due to expansion of injected fluid (Joule-Thomson cooling), the salting-out effect near the wellbore, and the impact of temperature and pressure changes on the rock mechanical properties for the reservoir and caprock. Dissolution is one of the most important trapping mechanisms for CO2. To capture the CO2 dissolution accurately, it is important to capture the dissolution changes with pressure, temperature, and brine salinity. The thermal properties of the reservoirs are crucial to capture the heat transfer between injected CO2 and the rocks.

Several novel workflows were established during this study, including setting up dissolution tables for CO2 and impurities being injected, tabulating the enthalpy of each component, and computing reservoir and caprock formations’ thermal capacity and thermal conductivity. This paper will provide a complete guideline for thermal modeling for carbon capture and storage (CCS) projects in a depleted gas field.
Mechanics and Kinematic Evolution of Structural Styles Associated with Fold-Thrust Belt- Evidence of Inversion, UAE
Authors: Noufal Abdelwahab
Published: November 2024

Oman Mountains deformation is being continued by massive thrust fault systems in Eastern Abu Dhabi basins with dissipating stresses laterally to the subsurface. Thrust faults with a strike-slip component that include a fault damage zone of strong rock shearing, and complicated zones of deformation. The initial episode was caused by the compressional movement of the Masirah, which faulted and folded again during the Semail tectonic events. Large faults are typically modelled on seismic as a single, large slip plane, but the outcrop analogues demonstrate the case is far more intricate, according to understanding of fault zone complexity and fault rock attributes. To understand the strength characteristics and seismic behaviour of faults in the subsurface, more in-depth information of the growth and structural style of thrust systems on outcrop analogues is essential considering the future exploration in eastern Abu Dhabi. Architecture, geometry, and tectonic uplift resulting from accumulated slip on the faults are all expressed at the surface that can express the geometrical prediction in subsurface.

The paper describes the geological features and evidence of inversion structures, such as anticlines, reverse faults, and detachment surfaces, using seismic data, well logs, and surface outcrop analogues. It also explains the kinematic models, strain rates, and restoration methods used to understand the structural evolution and deformation history of the region. It highlights the positive and negative effects of inversion tectonics on hydrocarbon generation, migration, and trapping, and how they vary depending on the fault orientation, lithology, fluid pressure, and tectonic context. It suggests that the Abu Dhabi basin has experienced multiple phases of extension and compression, resulting from the interaction of the Arabian and Eurasian plates, and that the strike-slip faulting regime has played a significant role in shaping the basin geometry and hydrocarbon potential.

This study has provided new insights into the geometry, timing, and driving mechanisms of thrusting deformation, as well as the regional tectonic implications of the fold-thrust belt. The fold-thrust belt can be further divided into three sub-belts, including the Northern Emirates zone, the eastern Abu Dhabi and the Abu Dhabi basin including onshore fields and further west. The former is characterized by imbricate stepped-thrust sheets composed of developed thrusts and related folds, and the detachment-fold sub-belt, which is composed of box, chevron, and closed overturned-isoclinal folds. The second eastern Abu Dhabi zone is characterized by thrust-fold sub-belt observed on seismic. The last western zone is mainly showing strike slip regime with few thrusts zones, which may due the transpressional regime between the fault segments.
Reactivating Oil Producer and Water Injector Wells Using Single Phase Retarded Acid and Fiber Optic Equipped Coiled Tubing
Authors: Maheshwari Y. K. , Subaihi M. H. , Almuharrami A. O. , Shaqsi A. K. Al , Leguizamon J. A. , Ahmad B. , Bashir A. , Delgado E. Franco , Mahmoud W. , Belkadi W. , Seoudy S. , Elattar A. , Ryan A.
Published: November 2024

This technical article outlines the implementation of single-phase retarded acid (SPRA) and its advantages over double-phase retarded acid systems. It follows an established Matrix Stimulation Engineering (MSE) workflow, leading to improved hydrocarbon production in an oil producer well and enhanced water injection in an injector well within the operator's field.

Previous stimulation techniques, employing a constant volume/feet dosage of hydrochloric acid via conventional coiled tubing (CT) in 6-inch open-hole horizontal wells targeting tight-carbonate formations, yielded inconsistent results and rapid declines in hydrocarbon production rates or water injection rates. In response, an MSE workflow was introduced in 2019 (Abdelrehim et al, 2020), incorporating fiber-optic-equipped CT and high-pressure jetting guns. Now, with the adoption of SPRA, the process is further optimized, leveraging slow acid reaction to enhance worm holing.

The understanding of formation damage plays a crucial role in designing appropriate matrix stimulation fluids. Pre-flush fluid system was designed and pumped prior main treatment for wellbore conditioning. To address damage bypass in tight carbonate formations, a novel single-phase retarded acid technology with a slow reaction rate was employed for deeper penetration.

Utilizing fiber optic cable as a temperature surveying logging device during injectivity tests allowed for the assessment of fluid distribution along the horizontal openhole section. This data, juxtaposed with petrophysical data and post-treatment production logs, empowered the engineering team to fine-tune chemical pumping schedules.

Implementing SPRA through the established MSE workflow facilitated selective fluid placement in target producing zones, leading to deeper penetration and enhanced wormholes. Consequently, there was a notable improvement in hydrocarbon production from producer well and increased water injectivity in injector well.

This article highlights the utilization of SPRA within a MSE framework, incorporating distributed temperature surveying (DTS) for assessment. It demonstrates SPRA's efficacy in enhancing hydrocarbon production and water injection in the operator's field.

The use of the SPRA has a positive environmental impact by reducing carbon emissions as a result of less volume, consequently utilizing less logistic and well operation time compared to regular acid or double-phase retarder acid systems.
Intelligent ESPs Diagnostic Model Based on Big Data and Machine Learning
Authors: Jiang Lu , Jiang LiPing , Guo Songyi , Xue Heng , Yang Lingfeng , Tang Xialan
Published: November 2024

There are various types of available data, with different data structures, dimensions, and intervals. Conventional big data algorithms can lead to poor interpretability. In this study, novel methods are proposed based on big data analysis and machine learning. First, the data are categorized into 4 pairs to build parameter analysis model: pump static data, pump dynamic data, production static data, and production dynamic data. Combining static and dynamic data to establish parameter analysis modeling and different data pairs adopt different modeling methods: current and voltage data adopt picture recognition algorithm, vibration data adopt time domain analysis, and production data adopt random forest algorithm. Then, a deep neural network is developed to couple four models to diagnose ESPs production status. All the models have high accuracy through optimization. In the end, a management platform had been established for ESP wells including data visualization, production analysis, fault diagnose and warning. Visual production dynamic tracking management can improve the management efficiency of ESP wells and reduce the cost of future workover and relocation.
The Impact of Artificial Intelligence on Cybersecurity
Authors: Basu Amit
Published: November 2024

The digital revolution over the last several decades has ushered in an era of unparalleled dependence on interconnected information systems. The smooth functioning of modern society, its critical infrastructure, from power grids and financial institutions to healthcare networks and communication channels depends on information technology. However, this reliance has also created a fertile ground for cyberattacks, posing significant risks to national security, economic stability, and public safety.

Cybersecurity involves protecting information systems and networks from unauthorized access, use, modification, or destruction. It is essential for ensuring the confidentiality, integrity, and availability of data and services, and for safeguarding the privacy, security, and trust of individuals, organizations, and societies. Cybersecurity is a dynamic and complex domain, characterized by the constant evolution and escalation of cyber threats, the rapid development and adoption of new technologies, and the diverse and conflicting interests and values of various stakeholders. It requires a multidisciplinary and holistic approach, involving technical, human, organizational, and societal factors, and addressing the technical, ethical, legal, and social implications of cyber activities.

Over the years, cybercriminals have evolved into highly organized and sophisticated entities, resembling traditional crime syndicates with clear hierarchies and specialized roles. They collaborate extensively and use advanced techniques such as zero-day exploits, sophisticated malware, and social engineering tactics like spear phishing. State-sponsored actors and cybercrime syndicates leverage the latest technologies to automate and enhance their attacks, exploiting vulnerabilities in target organizations. Financial motivations drive them to use cryptocurrencies for anonymous transactions, fueling the growth of ransomware and cyber fraud. Their global reach and ability to target critical infrastructure pose significant challenges, necessitating continuous advancements in cybersecurity measures and international collaboration to effectively counter these threats. Traditionally cybersecurity measures are often reactive and limited in their ability to cope with the rapidly evolving threat landscape.
Automatic Electrical Wiring Inspection with Advanced Computer Vision Models
Authors: Valvano G. , Rossi A. , Caridi G. , Vanzo G. , Politano A. , De Magistris G. , Salusti L.
Published: November 2024

Safety and reliability are paramount in energy industries. In this context, guaranteeing precise electrical wiring connections within terminal blocks is crucial for maintaining quality standards and enabling efficient remote support for on-site installations. Unfortunately, the current wiring quality checks are time-consuming and repetitive, and they are prone to human errors. This situation has led to an increasing interest in leveraging the capabilities of Artificial Intelligence (AI) to expedite the inspection process. AI assistants can either help in or completely automate the tedious checking operations, thereby enhancing operational efficiency. In this work, we introduce a novel approach that can be used to automatically verify the correctness of wiring connections to a terminal block. Our proposed methodology consists of a series of sequential operations, each contributing to the overall effectiveness of the system. First, we use an instance segmentation model to identify and isolate the connections between PINs and wires on a terminal block image. Then, we use text detection and recognition models to translate the pixels into an alphanumeric string. Lastly, we parse the obtained strings and compare results with the expected wiring connections in a reference database. Our proposed approach is not only simple and modular but also highly effective. It only requires a camera and a mobile device, and it swiftly generates a comprehensive report about the wire connections that are under inspection. This method is not only fast, but it also demonstrates promising performance levels (e.g. detecting connections with Precision and Recall > 96%), thereby confirming the potential of AI-based systems in revolutionizing the inspection process. With our work, we underscore the potential of AI-based systems in advancing traditional processes and setting new standards for efficiency and accuracy in the energy sector.
Novel 5S Workflow for Production Optimization and Water Management
Authors: Abbas A. , Mascagnini C. , Telang V. N. , Chughtai M. A.
Published: November 2024

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

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

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

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

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

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

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

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

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

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

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.