bluuebunny/crossref_metadata_2025_split huggingface dataset:
Moving to an Autonomous Artificial Lift Concept through Automatic ESP Restart
Authors: Khalaf Ahmed , Norman Bruce , Alquwizani Saud , Almalki Hussain , Ergesous Meshal , AlSowaier Mohammed 
Published: November 2019

Abstract
Electrical submersible pump (ESP) trips and unplanned shutdowns can be a major operational challenge for many oil fields. In most of these ESP trips, the ESP can be returned back to production after conducting proper troubleshooting at surface and without any downhole intervention. The process of manually restarting tripped ESPs can be a complex and costly operation, especially in an offshore environment. Alternatively, automatic ESP restart can offer great advantages by reducing the ESP downtime.
Many of the variable speed drives (VSDs) available in the market offer an auto restart feature that allows the ESP to be restarted automatically without human intervention. This paper presents the concept and the application of this technique. The activation of ESP auto restart requires considerable technical review of the different trip causes and the proper restart methodology for each. Auto restart of each trip type has to be programed differently to prevent possible harm to the ESP. Specific engineering measures and procedures shall be put in place to ensure personnel and equipment safety.
In this paper, some statistical tools for ESP trips and restarts are presented to measure the success of auto restart, its effectiveness, and its limitations. The obtained results from the ESP auto-restart technique show it to be both practical and beneficial; it can significantly reduce the time to put the ESP back in operation resulting in production advancement. In addition, continuous data collection and assessment of auto-restart events play an important factor in ensuring that auto-restart settings are properly applied and adjusted for each type of variable speed drive installed in the field. Finally, the paper provides several recommendations with suggested ways to improve the functionality of this feature.
The technique introduced in this paper can bring artificially lifted fields closer to an autonomous and intelligent concept of operations. The presented model can serve as a good benchmarking tool for future implementation of artificial lift automation.
Deferment of Mini Shut Down with Partial Automation of Manual Control
Authors: Al Dhaheri Abdulla Mubarak , Khalaf Ahmed 
Published: November 2019

Abstract
ADNOC LNG (Train 3) processes High Pressure gases from ADNOC Off shore and the gas goes through a series of processes to remove Hydrogen Sulphide & other impurities and gets dehydrated before the gases are processed to separate the various components as products. The Acid Gas Removal Unit is a hybrid arrangement of the basic Benfield Carbonate unit and Amine technologies. The Carbonate Unit, using Potassium Carbonate as the solvent, does the bulk of the Acid Gas removal from the feed gases.
Subsequent to restreaming of Train-3 after 2018 T/A, in the Acid Gas removal unit, Lean Carbonate Flash Drum level control valve 2C-LV-61 got stuck and became inoperable from DCS. Since then the level of Lean F/D 2C301 was controlled by operation of manual bypass valve in field along with frequent adjustment of Makeup water flow to Carbonate Reflux Drum 2C313 by DCS controller 2CFC0082. The valve 2C-LV-0061 could not be released for maintenance due to passing Isolation valves. To enable complete draining of the system and replacement / repair of the defective valves a mini-SD of Train 3 (minimum of 7 days) was planned in June’19. Seven days’ shut down for the sake of this repair would result in loss of production resulting in a revenue loss of US dollors35 million.
A specialist review meeting was conducted on 12th Feb and on 9th March 2019 with Operations, Process Engineering & Control Maintenance to discuss the alternative option of automating makeup water flow control (2CFC0082), with the objective of reducing daily field operations required to control carbonate flash drum level during steady state conditions, whilst also improving level control and retaining plant stability.
The new control scheme to cascade the level of Lean F/D to existing flow control 2CFC0082 was implemented vide minor DCS change MDCSC/008/19 on 21st March 2019. The Performance has been satisfactory during normal steady state operating conditions.
Based on the observations, it was recommended to, continue with Auto operation of FC0082 to control level of Lean Flash Drum during normal operation with field operator support to operate the LV61 bypass valve, in case of a programmed or unexpected upset in level of Carbonate flash drum.
Thus the Shut down was deferred successfully till the next planned turnaround opportunity resulting in an opportunity to save US dollors 35 million.
Statement of Issue: Soon after restreaming the train after Turnaround, an important control valve in the carbonate circuit of the LNG Train 3, namely 2-C-LV-0061, became inoperable while the Train was running. Attempts to isolate the valve failed due to passing isolation valves which made online repair impossible. A complete shut down of the Train to repair the defective valve would mean a revenue loss of US dollors 35 million due to loss of production (in addition to the impact of flaring).
Statistical Optimization of PDC Bit Designs Based on 3D Simulations Applied to Demanding Directional Applications
Authors: Pelfrene Gilles , Al-Ajmi Hadi , Bashir Jomah , Al-Otaibi Fahad , Al-Nuaimi Ahmad , Al-Jiran Hamad , Baroun Ahmad , Al-Kandari Abdulaziz , Huseen Talal , Mikhail Boktor , El-Genidy Ehab , Reboul Sebastien , Carlos Julien 
Published: November 2019

Abstract
Simulating the mechanical response of PDC drill bits contains a lot of uncertainties. Rock and fluid properties are generally poorly known, complex interactions occur downhole and physical models can hardly capture the full complexity of downhole phenomena. This paper presents a statistical approach that improves the reliability of the PDC bit design optimization process by ensuring that the expected directional behavior of the drill bit is robust over a well-defined range of drilling parameters.
It is first examined how uncertainty propagates through an accurate bit/rock interaction model which simulates numerically the interaction between a given PDC drill bit geometry and a given rock formation, both represented as 3D meshed surfaces. Series of simulations have been launched with simulation parameters defined as probability density functions. The focus has been set on directional drilling simulations where the drill bit is subjected to significant variations in contact loads on gage pads along its trajectory. A global sensitivity analysis has also been performed to identify the key parameters which control drilling performance.
Directional system parameters are critical in terms of steerability and tool face control, particularly in high dogleg severity applications. Based on these simulations, a statistical optimization strategy has then been implemented to ensure that the directional performance of the drill bit remains effective under a given uncertain drilling environment. Statistical analysis combined with drilling simulations indicated that ROP improvements could even be achieved without compromising steerability. A balanced bit design was selected and manufactured in an 8 1/2-in. model to drill a 714 ft section of a Kuwait field. The bit was run on a high dogleg rotary steerable system and directional assembly. The bit achieved the high steerability goals required by the application while showing a good compatibility with the directional tool. Moreover, ROP was increased by approximately 27% compared to offset wells, setting a record rate of penetration in the field.
Whereas statistical analyses are commonly conducted in the field of geosciences, it has rarely been applied in the field of drilling applications. The statistical bit design optimization strategy deployed in this work has allowed to improve both the drilling performance of the drill bit and its reliability.
Intelligent Planning of Drilling Trajectory Based on Computer Vision
Authors: Wang Han , Chen Dong , Ye Zhihui , Li Jun 
Published: November 2019

Abstract
The conventional well trajectory design mainly developed from spatial mathematical model e.g. arcs or cylindrical spiral lines method, focusing on seeking optimal kickoff point and curvature. However, the complex well trajectory design requires more sophisticated and efficient method, considering greater contact with reservoir pay zone, which means time consuming computation works based on conventional well trajectory design. The automated well trajectory planning can meet such requirements, based on reservoir area identification, reservoir matrix evaluation, wellbore trajectory path generation. The present study aims to develop this algorithm for automated drilling trajectory design without assistances from human experts. Based on the stratigraphic figure of a specific reservoir, the present algorithm is able to provide an optimal trajectory with more contact zone while still meeting the curvature requirement. An intelligent planning algorithm of drilling trajectory is proposed on basis of computer vision. Based on the stratigraphic figure of a specific reservoir, the present algorithm is able to provide an optimal trajectory with more contact zone. By converting the reservoir profile (pay zone) to digital matrix and evaluating the pay zone matrix, the optimal well path is able to be automated generated. The research finding can be potential applied in geosteering drilling or autumated drilling.
Molecule to Molecule M2M Water Injection Performance Review to Achieve Water Injection Excellence in PETRONAS – Part 1 Surface Operations
Authors: Hadi Sriyanta , Ab Wahab Mohammad Afiq , Nasron Budi Mawardi , Sharkawi Wira Abadi , A Latiff Nazri 
Published: November 2019

Abstract
Relevant to maximizing oil recovery, water injection is implemented for reservoir pressure maintenance and to maximize oil sweeping. The water injection involves both surface and subsurface matters. Since the objective is reservoir pressure maintenance and oil sweeping efficiency improvement, the subsurface domain includes reservoir engineering, geology and geophysics as well as the production technology. For surface operations, the water injection operation includes water injection source, water plant operations and water injection infrastructure. Water injection bottle neck and water quality issue may occur and damage the water injection efficiency. An idea of molecule to molecule (M2M) water injection performance review is raised to conduct a comprehensive and collaborative water injection review that involving many and outreach parties such as reservoir engineers, geologists, geophysicists, operation engineers, production chemists, production technologists, maintenance engineers, production planners and process engineers. The opportunity to include technical providers, partner representatives and host government representatives is taken in order to allow an effective discussion and quicken the maturing of relevant solution proposals. Comprehensive end to end review from the point of water source up to the point of producer is done to identify problem at each point, threats and improvement opportunities at every single node within the whole chain. With the M2M, water injection performance review has effectively provided an effective collaborative working environment as well as a learning avenue for young professionals that are involved in water injection matters. Many action items are resulted from the exercise and they are having high impact including safeguarding potential cost of USD 10 million per year for the water injection plant and infrastructure operations. In the short run, no disturbances for oil production and in the long run, the oil recovery can be maximized. Due to some limitation, this paper discusses only the surface water injection operations.
Asphaltene Management Leading to Significant Reduction of Production Deferment and Operation Maintenance in One of the Sour Fields in Southern Oman
Authors: Narwal Tushar , Alias Zaal , Kumar Kamlesh , Abri Zahir , Dickson Sara-Jane , Hadhrami Abdullah 
Published: November 2019

Abstract
In Southern Oman, PDO is producing from several critically sour fields (1-10% H2S). Initial flow assurance studies from these fields based on available data at the time did not predict asphaltene plugging issues in depletion mode for most of the fields. However, over the period, wells from one particular field (Field SA3) started experiencing asphaltene deposition in the wellbore, which initially affected only surveillance activities but later led to significant production deferment and posed operational challenges. This paper discusses the asphaltene management strategy developed by the team to tackle asphaltene problem in a systematic manner by improving the current asphaltene detection and cleanout techniques, which led to to reduction in unscheduled deferment by ~50% and the intervention costs by ~20-25%. This work also describes the potential asphaltene risks during gas injection based on an asphaltene study performed on downhole samples.
Subsea Pipeline Design Automation Using Digital Field Twin
Authors: Bhowmik Subrata , Noiray Gautier , Naik Harit 
Published: November 2019

Abstract
The main objective of this paper is to present a cost-effective, user-friendly and highly reliable subsea pipeline design automation framework under the cloud-based digital field twin platform Subsea-XD. The FEED and detail design phase of the subsea pipeline is normally quite long and need to run several analyses sequentially to achieve the desired results. In this cloud-based design automation method, a significant number of calculation hours are saved due to systematic and sequential approach with minimum remediation work by reducing human error.
In this proposed design automation framework, all the standard pipeline calculations including code checks are performed through a web-based graphical user interface (GUI) designed in cloud-based digital field twin. In the design phase of the subsea pipeline, some more advanced level pipeline finite element analyses are performed for buckling and walking assessment. The design phase of the subsea pipeline consists of different analytical as well as finite element (FE) calculations which are performed systematically and sequentially in cloud-based digital field twin. Various calculations including wall thickness calculation based on API/DNV/ASME code check, on-bottom stability analysis, pipeline span analysis, pipeline end expansion analysis, out of straightness analysis and pipeline buckling analysis are performed sequentially and systematically in the cloud using the metadata information available from the digital field data. All the standard pipeline calculations are developed using Python API and connected to cloud-based digital twin Subsea-XD. For advanced FE analyses for lateral buckling and pipeline walking, the preliminary susceptibilities are assessed through analytical calculations developed through python- based API. For the pipeline FE analysis for lateral buckling and walking assessment, pre-processor and post-processor are developed in python based on various metadata (pipe data, soil, environment) information available in the subsea digital field.
The pipeline design calculation outputs are stored in a standardised report format in the cloud platform. The GUI is developed and the whole pipeline design process is automated through the python API. This design automation approach significantly reduces the total project cost. Integrating all the pipeline design calculations and automated report generation in a cloud-based digital field twin is very much beneficial for the early stages where some changes are expected.
This pipeline design automation system relates to cloud-based digital field Subsea XD through API so that it is worked as an integrated system giving 3D digital field diagram as well as all pipeline design calculations in one digital platform.
Artificial Intelligence in Autonomous Operation of Oil and Gas Facilities
Authors: Devold Håvard , Fjellheim Roar 
Published: November 2019

Abstract
Objectives/Scope: Remote, inaccessible locations, hazardous environments and cost are some of the drivers for unmanned or remotely-operated facilities. With insight from facilities which are already operating remotely, it is time to take the next step towards running autonomous plants with no people. With reference to external sources and client case studies, this paper will discuss the preconditions and technological developments which now make it possible to do this safely and economically and how Artificial Intelligence is a key component.
Methods, Procedures, Process: The paper describes key criteria and technologies needed for successful autonomous operations. In particular, companies must ensure operations are safe through process safety management. They must also be able to run operations with no physical presence via automatic controls for startup, change and shutdown. Maintenance and inspection must also be done with no-one there, using plant-wide condition monitoring and predictive analytics, as opposed to only tracking critical equipment as the latter is insufficient in processes with so many interdependencies. Robots and drones must also be leveraged where manned intervention is required e.g. for pipeline scraper handling.
Results, Observations, Conclusions: The importance of zero operators is significant. Even just one employee, actually means 20 are needed for a site running all day, every day by the time rest, vacation and sick leave cover requirements are factored in, not to mention support functions like catering and cleaning. This is not only expensive but also means a significant number of people remain exposed to a hazardous working environment. Underpinning the above are Internet of things technologies to sense, measure and control operations, connectivity to share the information in a timely manner, the analytics to process it ‒with a significant reliance on artificial intelligence‒ and appropriate dashboards to bring the information to the remote operator, domain expert or vendor partner. The importance of digital engineering and digital twins in facilitating such activities will also be discussed.
Novel/Additive Information: We show that new safety, operational and maintenance procedures are needed to implement autonomous unmanned operation. Artificial intelligence with machine learning is needed to reach this goal. The paper will provide examples of howunmanned operations are becoming a reality. The safety and cost-saving benefits achieved from pilots and wider field applications of technology will be presented. Many of the technologies and operational changes will in themselves deliver reduced costs by eliminating operator errors, reducing maintenance expenditure and improving availability.
Evaluating Foam Stability using Tailored Water Chemistry for Gas Mobility Control Applications
Authors: AlYousef Zuhair , Ayirala Subhash , Gizzatov Ayrat , Kokal Sunil 
Published: November 2019

Abstract
Generating in-situ foam is regarded as one of the most promising techniques to overcome gas mobility issues and improve sweep efficiency in both miscible and immiscible gas injection enhanced oil recovery (EOR) processes. Gravity override, viscous fingering and channeling through permeable zones are the major limiting factors that can impair the efficiency of gas floods, mainly due to low density and viscosity of the gas relative to reservoir fluids. Generating strong and stable foam while injecting gas is one way to achieve in-depth conformance improvement in the reservoir.
In this study, a tailored water chemistry (formulated low salinity water) has been evaluated in comparison to using typical high salinity injection water (i.e. seawater) and deionized water in surfactant solutions to determine its overall effect on the produced foam. Using bulk foam tests, foam rheology apparatus and microfluidics device, the foam stabilization factors were analyzed and quantified by measuring the foam-life over time of different surfactants in varying salinity water solutions. In addition, the foam rheological properties were measured under high pressure. The microfluidics device was also used to examine the generated foam strength in porous media.
The results from laboratory experiments clearly demonstrated that the use of tailored water chemistry can improve the stability of produced foam when compared to both high salinity water and deionized water. Low salinity tailored water chemistry solutions resulted in a longer lasting foam, by almost 1.8-3.0 times depending on the surfactant type. The foam rheology results showed that the produced foams with the tailored low salinity water are of higher apparent viscosity when compared to those obtained with deionized water. Both longer foam-life and higher apparent viscosity are indicative of better, stronger and more stable foam. The higher resistance to gas flow was observed in porous media with foams generated using the low salinity tailored water chemistry solutions when compared to those foams obtained with deionized water and high salinity water.
This experimental study, for the first time, demonstrated substantial improvements in the foam stability by using a tailored water chemistry aqueous solution. Such huge foam stabilization improvements obtained with tailored water chemistry has the promising potential to increase the apparent viscosity of injected gas and subsequently more effectively mitigate gas mobility issues encountered in EOR applications.