bluuebunny/crossref_metadata_2025_split huggingface dataset:
Laser Descaling Robot for Long Range Scale Removal Applications
Authors: Abdelmoula Hichem , Jabari Rami , Batarseh Sameeh , Alerigi Damian San Roman 
Published: November 2024

Abstract
Scale deposits gradually accumulate within flowlines, often resulting in obstructions. At present, the descaling process primarily relies on chemical cleaning, pigging, or hydroblasting methods. However, these approaches are range limited, requires complex step-up, and carry the risk of potential damage to the inner pipe surface. To overcome these issues, we developed a laser descaling robot that can move within the flowline while carrying a high-power laser that can remove materials in the scale buildup.
The designed robot for descaling operations utilizes an in-pipe crawler designed to be centralized in the pipe. The laser collimator is affixed to a mount and positioned near the edge of the pipe. The robot's mount is attached to the end of the crawler and is equipped with a motor that facilitates the rotation of the collimator. Additionally, the robot is equipped with various hoses and accessories necessary for laser descaling activities. Furthermore, for real-time monitoring of the descaling process, a camera is affixed to the laser mount, ensuring that the operation can be closely observed as it unfolds.
A test setup is constructed extending over 60 m with varying pipes' internal diameters. Some of these pipes have a 7.65-inch internal diameter, while others have an 8-inch internal diameter. Additionally, the pipe setup features a 10 m radius curvature to verify the descaling robot's capability to navigate curved paths. Furthermore, aside from the tether, the robot is connected to multiple hoses that replicate the presence of nitrogen and vacuum tubes, which are essential components in real descaling operations. The robot was able to traverse the entire length of the pipe without encountering any issues. The camera output was recorded as the pipe traversal job was unfolding. The robot demonstrated smooth adaptation to varying pipe internal diameters. The articulated mount efficiently rotated during motion without causing any entanglement of the cables and hoses. Moreover, the robot was successfully retrieved without causing damage to any of the cables or hoses, highlighting its precision and safety during the operation.
The current design successfully validates the concept of remote laser descaling, showcasing the robot's capacity to carry the laser and all the required auxiliary hoses through long pipes. This novel method will allow the replacement of existing descaling methods while allowing a safer, more controlled, and long-range scale removal procedure.
Harnessing the Power of AI: a Data-Driven Well Reservoir Virtual Flow Metering Tool Accessible to All
Authors: Papot F. , Maurin P. , Dabat F. , Solans P. , Cyrot M. , Al-Sahely A. 
Published: November 2024

Abstract
Data-driven Virtual Flow Metering (VFM) by Machine Learning is an increasingly attractive method to perform multiphase flow metering in Oil and Gas production systems. A VFM is a complement to physical meters, using the continuous available field measurements such as tubing pressures, temperatures, and other relevant parameters (choke opening, activation parameters, etc.) as inputs to provide flow rate estimates at any given point of the production and injection network. Good knowledge of Flow Metering is required for production optimization, flow assurance, reservoir management and allocation activities.
In the allocation context, production and injection figures are typically computed monthly using available information at the time to answer budget and operation management immediate needs. As such, information could be biased and the data-driven VFM models are used to provide alternative allocations at each wellhead level to improve the confidence in reservoir history matching.
The paper presents successful use cases of such data-driven VFM built within the tool TDASH developed by the Company as part of its Digital Transformation Roadmap providing reservoir and production engineers friendly access to Artificial Intelligence means through a no code/low code approach.
Revolutionizing Leak Detection and Cost Savings in Valve Predictive Maintenance
Authors: Al Ruqaishi Mahmood Ahmed , Al Kalbani Fahad Khamis 
Published: November 2024

Abstract
valves are essential components of safeguarding and control systems, playing a crucial role in ensuring that plants operate efficiently and safely. Valve failures can lead to significant production losses, increased maintenance (operating) costs and contribute to process safety incidents. In plants, a common technique for valve maintenance is condition-based replacement at fixed time intervals. Evaluating the condition of in-service valves that process fluids present substantial challenges, particularly when diagnostic methods requiring valve movement are impractical during plant operations. This limitation complicates future maintenance planning, often forcing maintenance teams to either schedule potentially unnecessary valve work for upcoming shutdowns or forego maintenance entirely. Delaying maintenance can lead to costly, unplanned maintenance activities, unplanned shutdowns, and operational deferments, with the associated loss of production often far exceeding the maintenance costs. To address these challenges, the use of Acoustic Emission (AE) techniques is proposed for valve condition assessment. AE techniques offer a non-intrusive and effective method for monitoring the integrity of in-service valves without requiring operational disruptions. By detecting the high-frequency waves generated by crack growth, leakage, or other structural changes within the valve, AE techniques can provide real-time diagnostic information, enabling more accurate maintenance planning and preventing costly unplanned events.
This innovative approach aims to improve the reliability and efficiency of valve maintenance schedules, reduce unnecessary maintenance activities, and minimize the risk of unplanned shutdowns. The integration of AE techniques into valve condition monitoring represents a significant advancement in maintenance strategy, offering a more proactive and informed approach to ensuring the operational integrity of fluid processing systems. Hence, this paper aims to examine the effectiveness of the Acoustic Emission technique in detecting early leakage in safety and control valves when they are fully closed on-site. With an investment of around $20K in a small portable measurement device and utilizing cutting-edge Acoustic Emission technology, this project markedly reduced saleable gas loss. Achieving substantial progress toward our zero-emission objective, improving the overall maintenance cost and strategy and also slashed shutdown times by 70% while maintaining plant integrity and availability.
Advances in High-Performance Computing for Static and Dynamic Modelling
Authors: Kamashev A. , Azagbaesuweli G. , Sudiro H. , Al-Jenaibi F. , Bogachev K. , Gusarov E. , Kuzevanov M. , Kostin G. , Shimonin E. 
Published: November 2024

Abstract
In recent years, the oil and gas industry has increasingly leveraged high-performance computing (HPC) to tackle complex reservoir simulations. These simulations are crucial for understanding subsurface conditions, optimizing hydrocarbon recovery, and ensuring efficient resource management. Among the various simulation techniques, compositional modeling stands out due to its ability to capture detailed fluid behavior and interactions within the reservoir. This type of modeling is particularly valuable for predicting the behavior of multi-component fluid systems, which are common in many reservoirs.
One of the primary challenges in compositional modeling is the need for high-resolution grids. High-resolution grids enable more accurate representation of geological features and fluid dynamics but come with significant computational demands. As the resolution increases, so does the number of active grid cells, which can quickly escalate into the billions. Managing such large-scale models requires not only advanced software capable of handling vast amounts of data but also powerful hardware to process and visualize the results efficiently.
This study focuses on the development and implementation of a high-resolution compositional dynamic model with almost half billion active grid cells. The primary aim is to explore the capabilities and limitations of current software and hardware in managing these large-scale models.
Expandable Liner Hanger Installation in Middle East Exploration Well - South Arabic Gulf Offshore
Authors: Khadr M. , Williford J. , Osama M. , Palumbo D. , Saragih N. 
Published: November 2024

Abstract
This document will capture the experience of Expandable Liner Hanger successful installations for an Offshore Exploratory Well in South Arabic Gulf considered the first well profile in the Area to contain 4 different cemented Liner sizes starting from 16" Liner to 9-5/8" (with possibility of 2 contingency Liner Sizes 7" & 4-1/2").
In a challenging sour environment and complicated well design, the Expandable Liner Hanger system was selected as a proven reliable technology recognized worldwide.
The document will discuss the challenges in design and execution phases to reach the required TD of the well, exceeding 20,000 ft, to explore 2 main 4 ways structural closures. Liner Hanger implementation in the well was a key point to reach the required depths without jeopardizing the well design.
Procedures to run, install and cement the expandable liner hanger in place capturing all lessons learned and implementing the required risk assessments was a result of collaboration between engineering and operation teams to plan and prepare for all contingencies resulting in a smooth execution.
Expandable Liner Hanger helped to set and cement all casing shoes at planned depths in a complex well design offering a high capability of reaming while encountering high Pressures, high flow rates & high torques with no risk for premature release or premature set which is not feasible with a Conventional Liner Hanger system.
16"x20" Liner was installed through multiple kicks overcoming more than 75 tight spots (either with SOW, rotation or ream down) and cemented.
13-5/8"x16" Liner with single trip tieback system - designed and built for the project - that enabled minimizing the large OD length of the hanger system in 13-5/8″ × 16″ whilst also providing the tieback operation flexibility through a 20ft stroke system to surface was successfully installed.
13-3/4"x13-5/8" faced Intensive reaming down for more than 48 hours while slacking off all Liner weight & facing high torques with high flow rates/pressures. Finally, 9-5/8" Liner and 20 ft tie back to surface was successfully installed.
Utilizing the Expandable Liner Hanger as a reliable system in such challenging well allowed us to exploit all its potential. Continuous Improvements in Planning through execution phase within the simulations (Torque and Drag, Surge & Swab, wellCat simulations) and in the rig installation procedures resulting to mitigate risks and providing improved reliability, enhanced operational capabilities, and well integrity assurance.
Applied Sequence Stratigraphy Combined with Geological Modeling of the Greater Cheleken Area (Central Caspian Basin, Turkmenistan) Using New 3D OBN Acquisition to Reveal Channel Complex Systems from Delta to Deepwater Environments in Plio-Pleistocene Clastic Reservoirs
Authors: Ellen H. , AlAli Abdulla , Ajayi A. T. , Guney H. 
Published: November 2024

Abstract
The Greater Cheleken Area (GCA) reservoirs, developed offshore by Dragon Oil, are located along a complex NW-SE dextral transcurrent zone that separates the Northern and Southern Caspian Basins (SCB). This area hosts numerous hydrocarbon fields within thick, highly faulted Pliocene-Pleistocene clastic successions of the paleo-Amu-Darya Delta System, originating in the N-Balkan Fold Belt. We present a new model for the geological evolution of this region, based on the analysis and sequence stratigraphy interpretation of new 3D OBN seismic data, well logs, and integration with existing published data.
With the new 3D OBN acquisition, Dragon Oil has both PSTM and PSDM data for analysis, employing a sequence stratigraphy approach. Horizon markers have been defined using sequence boundaries and flooding surface markers for detailed interpretation. The seismic data reveals promising geological features from the Apsheron to the red bed series reservoir levels. Seismic sequence stratigraphy has identified various stratigraphic components, such as basin floor fans, channel levees, and prograding deltas. Fault interpretation has revealed faults extending from the Miocene level to younger levels of the Apsheron, exhibiting typical positive flower structure configurations.
Unconformity-bound sequences of alternating sandstones and shales, with limited limestones, conglomerates, and evaporites, are deposited in environments ranging from shallow marine, delta front, and delta plain to alluvial, lacustrine, and deepwater. These sequences include the Uppermost Miocene to Lower Pliocene Red Series (Lower, Middle, Upper Red Series), Upper Pliocene Akchagyl Formation, Lower Pleistocene Apsheron Formation, and Upper Pleistocene to Holocene, comprising twelve productive levels. Hundreds to thousands of mappable faults are connected to deep-seated shear zones and exhibit fault-sealing characteristics that create highly compartmentalized reservoirs with vertical and horizontal separations. These faults vary in shape and size and display continuous Pliocene-Pleistocene syn-sedimentary activity, including sediment thickness heterogeneities, pinch-outs, lateral facies changes, channel structures, and inversion structures.
The sedimentary complexity as well as structural geology configuration described through the new 3D OBN data provides fundamental insights into the major challenges in reservoir production strategies and opens new opportunities for exploration and appraisal.
Artificial Intelligence Powered Non-Destructive Testing for Inline Inspection
Authors: Al-Jarro Ahmed , Mostafa Tarek M. , Ooi Guang , Khater Moutazbellah , Mohamed Fahd , Ba’adani Mohammad , Abdulmohsin Mohammed , Bahky Thamer , Ghamdi Khalid , Zahrani Salah , Bagci Hakan , Ahmed Shehab 
Published: November 2024

Abstract
In this work, we present a novel AI-powered non-destructive testing (AI-NDT) technique for the examination and diagnostic of pipelines. This digital transformation development targets the detection and identification of degradation in metallic pipelines. It stems from various business needs to address an increasingly urgent challenge in the Oil and Gas sector and other related industries for the characterization of energy pipelines. This effort employs cutting-edge and bespoke AI models applied to hybrid data-physics modelling and acquisition techniques coupled with advanced sensing methods. The system interrogates the structural integrity of pipes via novel in-pipe advanced electromagnetic based sensing techniques. The AI inversion models learn on the hybrid data-physics modelling with high fidelity simulation techniques. The recorded data are fed into the AI model that directly maps them into images to represent the health status of inspected pipelines. Notably, not only this IR4.0 driven system allows for the examination of pipelines for their integrity, it also provides a direct mapping of the recorded spatiotemporal sensors’ responses to images that represent the cross-sectional profiles of the inspected pipelines along their entirety. The outcome is a system that equips end-users with effective and easy-to-use inspection methods to determine the health status of targeted assets; leading to a precise, accurate, and near real-time assessment, a first of its kind.
Revolutionizing Exploration Risk Mitigation: Strategic MPD Design for HEMMER-1 Startup Project
Authors: Justiniano Luis Carlos , Viera Leonardo Landivar , Ospina Jenny , Ojeda Luis Vidal , Ruiz Carlos Costales , Drpic Juan Mardones 
Published: November 2024

Abstract
In the 1970s, the Marcou-1 well was drilled in the continental area of the Manzano block in Punta Arenas, Chile. This well served as a key reference point for understanding the reservoir dynamics and geological characteristics of the region. The Manzano block is characterized by the presence of gas pockets in highly pressurized sandstone intercalations. The exploration of HEMMER-1 is crucial for assessing the potential of high-pressure zones, which could significantly influence future resource extraction strategies in the San Jorge basin. The HEMMER-1 well, using managed pressure drilling (MPD), represents the first such implementation in Chile.
This technology proved essential for effectively managing the unpredictable pressure variances within the highly pressurized sandstone layers of the San Jorge formation. The success of the project was not solely due to the execution of advanced drilling techniques, but, as the first implantation into the region, it also hinged significantly on comprehensive training programs and meticulous planning. These preparatory steps ensured that the project team could adeptly handle the complex challenges presented, enhancing both drilling safety and operational efficiency. This study details the implementation of MPD and managed pressure cementing (MPC) as integral solutions to overcome the geological challenges and operational hazards.
The employment of these techniques facilitated the control of wellbore pressures and allowed for early kick detection and influx management, both essential for maintaining well integrity. Pressure buildup tests (PBUTs) and precise pressure management ensured the accurate characterization of the formation, confirming pore pressures and enabling safer drilling practices. Moreover, the successful execution of coring operations in MPD mode marked a significant advancement. Operating under statically underbalanced conditions, this approach ensured the integrity of core samples, which is critical for evaluating the reservoir's potential. The MPC technique further stabilized the wellbore, preventing fluid contamination and optimizing cementation processes, thereby enhancing overall operational efficiency.
This project not only demonstrates the feasibility and benefits of MPD in high-risk and unpredictable environments, but also sets a precedent for future exploratory and development projects in similar settings. The results underscore the effectiveness of MPD in reducing non-productive time (NPT), optimizing resource extraction, and mitigating operational risks, thus contributing substantially to the regional energy strategy and the broader goal of advancing drilling technologies in challenging environments.
First Dual Completion Digital Gas Lift System Installed in Middle East
Authors: Cannon G. D , Caproni C , Al Zaabi F. N , Al Sereidi A. O , Alshamsi AA , Salama E. S , Fonseca R. M , Abdulla M. F , BenAmara A , Faux S 
Published: November 2024

Gas lift is one of the most crucial components for achieving and maintaining production targets for ADNOC Offshore assets. One major factor for this is the utilization of dual completions, whereby two production zones can be produced via a single casing conduit. Gas lift within dual completion wells is extremely challenging with conventional pressure operated gas lift valves due to the dynamic downhole conditions, fluctuating pressure and temperature and the inability to individually control the gas injection rate to each production string. In most cases, the string dedicated to the formation with lower productivity and reservoir pressure tends to "rob" the injection gas from other. Furthermore, well intervention is required to change out the gas lift valve orifice as downhole conditions evolve over the life of the well. To maximize the gas lift performance of the dual completion well, a Digital Gas Lift System (DIAL) was applied to a dual completion well on both production strings.
A suitable dual completion well candidate was selected in the Green Field SS. Once the candidate was selected a comprehensive design review was completed. The gas lift design determined that two DIAL Gas Lift Units were to be installed on each string. Orifice port sizes were selected to ensure that the optimum gas injection rate would be delivered. The DIAL Units are connected to a Surface Control System (SCS) which would enable surface control of the electric valves downhole. Each DIAL Unit features pressure and temperature gauges and valve position sensing to allow the operator to determine the Vertical Lift Performance (VLP) of each string, casing gradient and gas injection rate in real time. Furthermore, the DIAL System was integrated with the Field Distributed Control System (DCS), allowing for remote data driven decision making. A full System Integration Test (SIT) was completed ahead of the field installation, integration, and commissioning.
The DIAL System was successfully installed and commissioned. Through the ability to monitor and control the gas injection rate throughout the well life, the implementation of the DIAL System has resulted in substantial net present value generation through real time production optimization and the avoidance of well intervention, associated costs and deferred production required for gas lift valve change out and Flowing Gradient Surveys (FGS).
Realtime Well Engineering: Estimating Casing Runnability Risk While Drilling
Authors: Kumar S. Kiran , Samuel Robello 
Published: November 2024

Abstract
There is an urgent requirement in the drilling industry to discern the plausible causes associated with a casing stuck event and short landing of a casing. Traditional methods involve analyzing widely used legacy models such as the Torque and Drag/Swab Surge models and requires the interpretation of several plots at once, making it not comprehensive enough to account for many factors that may cause the casing stuck; in particular, the geometrical aspect of the wellbore is often overlooked while determining the risk. Furthermore, the available methods rely heavily on the experience of the drilling engineer, which is exacerbated by the fact that the casing stuck event is usually detected close to the casing stuck event, leaving very little time to perform any corrective measures that might alleviate the situation. Any last-minute intervention is generally not enough or is expensive and not ideal. Thus, there is a need in the drilling industry to have solutions that work in real-time that asses the risk of the casing stuck event which is comprehensive enough to take most factors into account that might affect the probability of casing stuck. The solution provided should also be simple and must not involve reading several plots at once; this removes the operational fatigue of the drilling engineer while monitoring the drilling operation. Moreover, the casing stuck event ideally must be predicted way ahead of time so that appropriate intervention is possible without having to resort to extreme measures. This paper proposes one such solution which is validated across several wells. The solution encapsulates the risk of the casing stuck considering several factors that might affect the probability of getting stuck into a single number(index) between 0 to 100, higher the value indicates higher risk. The solution offers to predict the casing stuck during the drilling operation itself leaving sufficient time for any intervention that may be needed. The geometrical aspect of the wellbore is also included in the construction of this index along with several other factors making the solution comprehensive. Finally, a single plot of the index value versus the depth is presented to drilling engineer for easy interpretation. This paper presents the methodology adopted in the construction of the real-time solution and discusses a few validation points using real cases.