bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wells Around Formation Issues WAFI Tool-Machine Learning Tool to Extract Field Issues from Daily Reports
Authors: Al-Taha Ahmad , Al-Sulaimani Tariq , Al-Bahri AL-Salt 
Published: October 2023

Abstract
The objective of this paper is to share and introduce the Wells Around Formation Issues [WAFI] tool, which was developed by Petroleum Development Oman LLC [PDO] - collaboration between Well Engineering and Data Science teams. This tool's function is to extract Formation Issues from the Daily Drilling Operation Reports [DDOR\ & Other Reports entered by Drilling Site team and display them per formation per field. WAFI is a cutting-edge Well Engineering solution that employs Text Mining techniques to automatically provide offset well information, significantly enhancing efficiency and reducing manual labor spent on data extraction from disparate databases and analysis in Excel.This advanced solution facilitates a deeper understanding of complex relationships between neighboring wells and the well to be drilled. By optimizing this process, our approach aims to effectively pinpoint potential challenge areas, thereby augmenting drilling operations and sustaining overall project success.The tool was trialed in 3 fields in PDO, and it managed to pick up most of the drilling and formation issues identified and expected in each field and in offset wells, based on the Trained Machine Learning Model.The tool picks up the Depth at which the issue occurred, and it links it to the Formation being drilled. The results are viewed in a formation level view or at a Well level view, so it will give an overview of the field issues in offset wells. This will help Team for better planning and preparing for the upcoming wells, and of understanding of the Fields issues.The tool picks up the following Issues: Tight spots, Over Pulls, Reaming and Back Reaming, Vibrations, Stick & Slip, Bit Balling, Fish, Lost Circulation, Fluid Influx, Stuck Pipe & Drill String Failure.The parameters being picked by the model are: Loss Rate range, Flow Rate, Torque, RPM, Overpull and ROP [Rate of Penetration].This is Phase One of the Tool development, and next plan for Phase Two will include more functionalities and more features, Parameters and enhancements to the tool. Both phases will be discussed in this paper.
Rigless Thru-Tubing Gas Lift Retrofit System Optimizes Production in Shut-In Well by Deepening Injection Point Below Production Packer
Authors: Suhaimin F. , Sabri D. , Gutleber S. 
Published: October 2023

Abstract
Well A, a Brownfield offshore oil producer in Brunei, was shut in due to multiple leaks in the tubing. The well was drilled in 2000, so was facing common issues associated with depletion prior to shut-in. Production from the well was restored by installing an innovative thru-tubing retrofit gas lift system, allowing for injection of lift gas below the production packer, while simultaneously restoring tubing integrity by isolating the leaks.
The goal of the rigless intervention was to restore tubing integrity by installing an ISO 14310 V0-validated gas-tight straddle across the leaks. The straddle also serves as a retrofit gas lift system, enabling delivery of lift gas below the production packer, just above the horizontal open hole gravel pack section. The straddle directs lift gas down an inner string hung from the lower packer with an installed gas lift mandrel on the bottom of the tail pipe, delivering lift gas below the production packer. The straddle features internal flow paths, allowing produced fluid to flow through the straddle back towards surface.
Once installation was complete, the new gas lift valve was installed 200 m TVD (true vertical depth) deeper than the lowermost side pocket mandrel. During the initial well test, lift gas was injected down the casing and entered the production tubing through the leak points and SPM, which were contained within the straddle assembly. The upper and lower packing elements in the straddle directed all gas through the crossflow sub and into the inner string suspended from the lower packer. A slim gas lift valve was connected to the downhole end of the tail pipe. By injecting lift gas in the lower completion, hydrocarbon was unloaded from a deeper depth than would have been possible using conventional gas lift. Within four hours of starting lift gas injection, Well A was flowing steadily with 900 kPa of flowing wellhead pressure (FWHP). The well was then shut in, pending a full well test.
This novel approach helped avoid an expensive workover and minimized runs in hole by incorporating the gas lift retrofit system into the straddle isolating the tubing leaks. This installation was the first in Brunei that placed the lift gas injection point beyond the production tubing in a horizontal well. As a result, a well that had been shut in for five years was re-instated and production was further optimized by deepening the lift gas injection point 200 m TVD below the lowermost side pocket mandrel.
Leveraging IoT, Machine Learning and Cloud to Deploy at Scale Remote Monitoring Capabilities in Coal Seam Gas (CSG) Well Pads
Authors: Shekhawat D. , Shannon C. , Grover R. 
Published: October 2023

Abstract
Coal seam gas (CSG) is a naturally occurring methane gas found in most coal seams and is similar to conventional natural gas. CSG is a major source of energy, accounting for about 15% of Australia's electricity generation. Also, CSG is an integral part of the gas industry in eastern Australia, particularly in Queensland. Origin Energy is the upstream operator for a leading joint venture in Australia and is responsible for the development of its CSG fields in the Surat and Bowen basins as well as the main transmission pipeline that transports the gas to the LNG facility on Curtis Island near Gladstone, Queensland.
Origin Energy has been exploring ways to leverage modern technology solutions to increase field staff productivity, reduce operating costs per well, and improve asset reliability while also bringing more wells into production to meet growing customer demands. Field operators drive up to 100km per day and may have up to 20 well visits per day as part of a routine inspection that involves visual checks of the site to gain situational awareness.
In recent years, with advancements in technologies such as edge compute (IoT), modern network connectivity options (satellite, narrow-band LTE) and Machine learning (no-code/low-code solutions) leveraging Cloud infrastructure early experiments are suggesting the implementation of safe, reliable, low-cost remote monitoring capabilities at scale is a possibility.
This paper discusses how Amazon Web Services (AWS) collaborated with Origin Energy to deploy a trial focusing on remote monitoring of well pads using a camera solution. This trial captures images from the well pad at regular intervals, which when scaled out will help reduce the need for routine inspection of well pads by field operator at the current interval. This trial has also developed a data repository of all the images in the AWS Cloud and is designing a data processing pipeline to label images and use low-code/no-code ML to detect visual anomalies.
In addition to the Origin Energy use cases (described in use case section 2.1 and 2.2) AWS has also helped an operator in North America (use case section 2.3) with building Machine learning models using Amazon SageMaker for anomaly detection. Hence, based on these projects it has become evident that using IoT, Machine Learning, and Cloud computing can accelerate innovation that drives down cost and increase operational safety of managing Oil & Gas assets remotely.
Decommissioning a Lightweight Marginal Field Platform: Challenges and Journey to Successful Execution
Authors: Yee Teh See , Badrol Raja Sharifuddin Ahmad B. Raja , Shaharuddin Noor Hidayah , Zakaria Amirah Bt C. , Alifah M. Norfisyah B. , Azali M. Syaifullah B. M. , Kasah M. Aziehan Mat 
Published: October 2023

Abstract
As reserves of some of the oil and gas field start to deplete, and in addition, certain platforms have reached their end of design/producing life, it comes the time for the relevant platforms to be removed and disposed or widely known as decommissioning. Topsides decommissioning includes complete removal while the substructure removal options include total removal for onshore disposal, reefing (in-situ or ex-situ) and leave in-place. This paper will discuss the recent Malaysia offshore decommissioning project which had been completed in June 2023. This project was distinctive from other decommissioning projects as the decommissioned topside would be re-used and refurbished by other operator for a new oil and gas development project.
The decommissioned platform was designed as a three (3) legged conductor-supported platform which was installed by jack-up rig. Located at only 3.3 Nautical Miles (circa 6.1km) offshore Kuala Baram, Sarawak Malaysia, its soft soil condition makes it too risky to remove the platform using the jack-up rig based on the challenges/complications encountered during post-installation. The shallow water depth of 10 meters limits the lifting vessel selection as well as its associated marine spreads. These had contributed many challenges in planning the wells P&A and the overall facilities removal. Furthermore, the concept and removal methodologies for this ‘conductor supported platform’ would be different from any other typical wellhead platforms.
This paper will elaborate the entire decommissioning process and its challenges in all the phases, including wells abandonment, pre-abandonment survey and data gathering, engineering, decommissioning, structural removal and transfer, disposal, and final site clearance. The engineering study, cutting tools selection, removal sequences and vessel selections played important roles in succeeding the entire campaign.
In addition to the technical challenges, this paper will also discuss the schedule and cost optimisation that the Project Management Team had put an effort into.
This paper should be an interest to those who are exploring platform and facilities abandonment and decommissioning, and we will walk the reader through the whole journey of the platform facilities decommissioning and removal.
Unlocking Potentials of Big Data: A Method for Enhancing H2S Specification in NGL Product From Condensate Stripper Column
Authors: Bajuaifer Hatem A. , Khan Ashiff– , Hawsawi Ahmad M. , Otaibi Majed M. 
Published: October 2023

Abstract
This paper covers an optimization study in Saudi Aramco Khurais Facility through data analytics and modeling to enhance NGL Quality and maximize C3+ Yield through Process Modeling and big data statistical modeling of correlations. The paper objective is to:
Share the optimization approach and how it can be replicated. Presents the results and outcomes of this optimizations along with utilized big data approaches.
The main concept of this study is to utilize a big data approach to analyze +5 million data point to discover unknown relations between various parameters that cannot be explained from process point of view. Moreover, the discovered relations and other parameters were further investigated through statistical models of correlations. The generated results were evaluated from process point of view to be utilized in enhancing NGL quality and maximize the yield through developing new process schemes and system modifications via HYSYS simulations followed by a field trials prior actual deployment on plant level.
This optimization approach resulted in discovering three new process schemes to enhance NGL quality and maximizing product yield including:
External vapor propane injection to stripper column to artificially increase the traffic in the column and maximize the yield where a portion of the propane will be condensed in the column and generate more liquid volume of the higher product value (i.e liquid NGL) Vaporizing a slip strip from generated NGL to increase the traffic in the column artificially to increase the confidence level in maintaining the product quality to 99.7% (i.e 3 standard deviation). Vaporizing a slip stream of OFF-SPEC product to artificially increase the traffic in the column and maximize the yield.
The main outputs of this optimization are:
Developing 3 novel process schemes for hydrocarbon condensate processing. Increasing the confidence level of maintaining product quality to 99.7%. Generating additional value of additional NGLrecovery.
The novelty in this paper is the approach to utilize big data and multivariate analysis along with process modelling to identify hidden relations and factors impacting yield and product quality that resulted in developing new process schemes to increase NGL yield and the confidence in achieving quality specifications to 99.7%. This process along with developed process schemes can be replicated and add benefits to any gas plant that utilize stripper columns for NGL sweeting process resulting in multiple circular economy initiatives and ideas such as reducing reprocessing time, reducing feed stock and reuse of off spec products in better applications.
PDO Waterflood Gap to Potential Focus Area and Key deliverables from Central Waterflood Team
Authors: Al Balushi F. I. , Hadfield N. S. , Al Brashdi D. K. , Al Shaaili M. M. , Al Hinai K. M. 
Published: October 2023

Abstract
PDO waterfloods over 70 fields in both North & South Directorates with full range of geology and developments concepts like: carbonate & clastic, light & heavy oil (1cP - +3000 cP), five spots, peripheral, line drive, Horizontal & Vertical. Waterflooded fields anticipate wide range of challenges which are related to pattern size, well count, Water quality & Injectivity decline, Vertical & Horizontal Conformance, Metering & Surveillance, Integrity & Facility constraints, and lack of well & reservoir management models that used for quick optimization. 50% of PDO Production & Reserves is delivered through Water flood Projects.
Around 90% of waterfloods were not using baseline or models in which to compare their performance to help driving opportunity and threat management (e.g., Top Quartile Recovery factor, Tube model, Field Development plan models, external benchmark). In PDO Many fields were having low throughputs leading to slow recoveries from Waterflood, and injection decrease as BSW increases. Also, effective sweep optimization was not stablished in both how to achieve it and how to demonstrate the benefits. Finally integrated optimization of both surface and subsurface opportunities is lacking in many projects.
In 2019 PDO established the definition of the Waterflood gap to potential in terms of throughput and sweep, and this will be used to identify individual fields with Gap to Potential and opportunities to close the gap above those currently captured Program Build Cycle. Additionally, Waterflood Improvement plan was developed based on deep dive exercise which aim to improve production by reducing Field decline rate as result of optimisation
Getting the right amount of water, of the correct Quality Improve sweep oil in the most effective way Reduce the opex cost of water flooding
Deployment of Automated Dynamic Kill System to Manage Well Control Activities in High Risk Shallow Gas Cap Wells
Authors: Al Salmi Ammar Hamed , Al Makhmari Nasser Issa , Al Naamani Noaman Hilal 
Published: October 2023

Abstract
One of the greatest dilemmas in Petroleum Development Oman in workover operation is incidents related to gas cap wells where primary well control barrier is maintained by dynamic kill methodology which is the use of fluid velocity to prevent gas evacuation to surface. This paper discusses the well control method in oil wells associated with gas cap by automation and innovation of Dynamic-kill equipment and procedures. Gas cap wells which are located in the north of Sultanate of Oman are considered as high-risk wells from well control prospective. For long period of time, conventional killing manifold has been used to establish the filling rate to maintain the primary well control barrier. Multiple failures occurred related to the reliability of the conventional system which inspire the need of new methodology. Statistical analysis study was carried out to identify the well process safety incidents related to workover activities in gas cap wells. Moreover, route causes analysis took place to identify the main challenges using the conventional kill manifold system.
This paper highlights the use of [Automated Dynamic kill system, Rotating control device (RCD)] which was implemented for the first time and resulted in a significant reduction in Well Process Safety risk exposure, people exposure and environment exposure.
This paper will give an overview about the old system and its related operational challenges that created an opportunity to innovate and design a new system. The new system went through a unique design process to fulfil and overcome the associated challenges of the conventional system. Commissioning phase for the new system carried over to identify the limitation and confirm the reliability of the new dynamic kill system by performing several tests including extended function test, flow test and logarithm accuracy test. Several enhancements were added based on field trails and requirements to meet the optimum system delivery as final product. In addition to the final approved system, RCD (Rotating Control Device) was utilized as a fail-safe system to provide sealing mechanism around the pipe and to act as an additional barrier in case of primary barrier loss. The combined systems led to improvement in HSE by reduction in human dependency by 70% as well as significant reduction in WPS incidents related to gas cap wells. Finalizing the paper by visual comparison between the conventional and automated systems in terms of HSE and operational aspects.
The Dawn of Routine Satellite-Based Monitoring for Energy Infrastructure is Now
Authors: Weaver R. Peter 
Published: October 2023

Abstract
Hyperspectral imagery (HSI) began in the 1980s and has been used by the U.S. government for years, but it just recently became available for commercial use. This technology has a vast range of potential applications, with oil and gas pipeline monitoring being one of the most prominent examples. HSI enables unparalleled daily global pipeline leak and change detection capabilities. This technology, deployed by satellite, is now beginning to replace conventional aerial monitoring compliance while also enabling enhanced emissions detection. This paper discusses the state-of-the-art for HSI, with examples of pipeline leaks and encroachment observed using hyperspectral data and analysis.
Successful HSI deployment will drive a decrease in the number and magnitude of pipeline leaks using frequent, global, high-resolution data collection, rapid and reliable analysis, and reporting of actionable information. This paper focuses on Oil & Gas, but the application spans industries. Across the board, HSI commonly enables use cases throughout the resource lifecycle.
For decades, satellite-based HSI technology has offered the promise of remote detection of hydrocarbons and other disturbances. It is finally becoming scalable and cost-effective for the pipeline operators and thus a reality for cost-effective asset stewardship.
Hybrid Data Driven Intelligent Algorithm for Stuck Pipe Prevention
Authors: AitAli R. , Arevalo P. , Dashevskiy D. , Mahmoud M. , Pocaterra A. , Al Bouny A. , Hussain Mohamed Qassem , Baruno Agung , Mohammed Satia 
Published: October 2023

Abstract
In today's drilling industry, it is essential to utilize both downhole and surface real-time sensor systems along with physics-based models to detect drilling hazards at an early stage and take timely measures to mitigate drilling related risks reducing non-productive time (NPT) and invisible lost time (ILT). Stuck pipe events are a major cause of NPT with an estimated cost to the oil and gas industry in the range of hundreds of Millions USD per year. Given its impact to drilling operations, stuck pipe prevention has high relevance and attention in the industry. In fact, in the last decade, the number of initiatives using drilling data coupled with advanced algorithms (combination of artificial intelligence (AI) and machine learning (ML)) to better understand and prevent stuck pipe events has greatly increased. Different approaches utilizing surface data are available ranging from data driven models, physics-based models, or even hybrid approaches combining physics-based models with data driven models. In any case, the outcome is an algorithm tasked with the identification of stuck-pipe events before they happen. If such an algorithm is deployed at the rig site (i.e., running on an edge device), ingesting surface and downhole data in real-time, the potential to improve the drilling process in terms of performance and safety greatly increases. Furthermore, safer drilling operations have an impact not only on the reduction of the overall capital expenditure (CAPEX) for well construction, but also on associated carbon emissions.
The approach presented in this paper is based on drilling automation applications focused on the integrity of the drilling process. The system includes a set of advanced algorithms coupled with digital twins (e.g., physics-based models of the wellbore) running on an edge device deployed at the rig site, to create a comprehensive monitoring and alert solution for surface hookload. The monitoring system consists of three main components: a reference environment given by digital twins, which provides safe operating envelopes (SOE) defined by overpull and buckling as boundaries; a set of algorithms to detect and sample common indicators of torque and drag automatically, such as pick-up (PU), slack-off (SO), rotation off bottom (ROB) torques and loads; and a higher layer to identify trends and deviations between the samples to create early warnings related to stuck-pipe symptoms.
The monitoring system implemented can be deployed for all kinds of drilling operations (i.e., drilling, tripping, circulating). By providing early warnings of stuck pipe like symptoms, the system enables users (i.e., rig crew, drilling operations, drilling optimization engineers) to mitigate such symptoms in time, hence avoiding costly consequences.
ADNOC's Approach in Piloting ESG Third Party Due Diligence Framework
Authors: Al Hameedi Samar , Al Raisi Azza , El Ghazouli Majid , Balalaa Mona Ahmed , Orsini Yadaira , Smith Courtenay 
Published: October 2023

Abstract
The aftermath of COVID-19 has highlighted the importance of resilient and sustainable supply chains. There is a growing body of evidence demonstrating how sustainability programmes can help companies recover from disruptions by optimising and reducing costs associated with these. Research from McKinsey shows that strong ESG performance can drive down costs by 5-10%, as companies focus on operational efficiency and waste reduction. It also shows that ESG high performers enjoy faster growth and higher valuations (Cherel-Bonnemaison et al, 2021).
Becoming an ESG top performer undoubtedly means understanding and proactively managing supply chain risks, particularly as two-thirds of an average company's ESG footprint lies with its suppliers (Cherel-Bonnemaison et al, 2021). There is no denying the value proposition that ESG brings and the key role it plays in managing risks associated to third parties. What is less clear is how to effectively integrate ESG into company-wide decision making.