bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sucker Rod Make Up: All About Displacement, or is it?
Authors: Anderson Jordan , Oliva Esteban , Mogus Steve 
Published: August 2024

Abstract
Although sucker rod connections are more understood now than they have been in the past, they are a surprisingly complex part of sucker rod operations, and we continue to learn about them. This study aims to further understand sucker rod connection make up variables, how those variables could affect operational reliability, and how to achieve optimal make up conditions. The variables considered were connections with and without pin lube, various coupling and rod grades, and sucker rod tong capabilities.
This study was performed using connection make up and break out testing and secondarily rod tong diagnostics in the field. The connection make up and break out testing was performed using specialized sucker rod make up equipment that could measure make up and break out torque, as well as circumferential displacement. All the previous measurements were taken in varying connection conditions and combinations. This data was analyzed to understand how these conditions affect make up and back off torque. Concurrently with this testing, sucker rod tong diagnostic operations (torque/hydraulic pressure measurements) were being carried out in the field to understand the torque accuracy and capability of sucker rod tongs.
The connection make up and break out testing revealed that connection make up without pin thread lubrication or with proper pin thread lubrication practices both yield acceptable back off torque values. Secondarily, the back off testing confirmed that there is considerable variation in torque necessary when varying rod grade, but not coupling grade. The sucker rod tong diagnostics revealed that many rod tongs do not reach manufacturer specifications for max torque and many also have considerable torque variation that could result in improper make up.
Understanding and Expanding the 1 Feet Per Second Rule of Thumb for ESP Motor Heat Transfer
Authors: Scariot V. K. , Pereyra E. , Sarica C. 
Published: August 2024

Abstract
Some practitioners in the industry target a local velocity of 1 ft/s to ensure proper ESP motor heat transfer. According to this rule of thumb, if the local velocity is lower than this threshold, the flowing area should be reduced to increase the fluid velocity above 1 ft/s and improve heat transfer. The main limitation of this rule of thumb is that it ignores fluid properties and does not provide guidance when velocities are already above 1 ft/s. This paper covers a simplified approach to consider the effect of fluid properties and the ESP motor geometry by identifying the main contributing factors to the motor temperature rise using a simplified heat transfer model. For high water cut conditions, a 1 ft/s velocity with a 1-in. hydraulic diameter results in a Reynolds number of 8× 103. In other words, for water-dominated flows for which the rule of thumb is usually applicable, the rule of thumb ensures a Reynolds number is in the turbulent region. A better alternative for the 1 ft/s rule of thumb is to use a Reynolds number cutoff value to ensure the flow around the motor is turbulent. This minimizes the skin temperature rise component and accounts for fluid properties. This paper analyzes the applicability of the widely used 1 ft/s rule of thumb and provides an alternative way for preliminary motor design or selection.
Field Testing of a Novel Gas Processing System for Electric Submersible Pumps
Authors: Rhys-Davies J. , Luna David , Myska J 
Published: August 2024

Abstract
A new gas processing system, called an Integrated Gas Processor was developed to improve the gas management of an ESP system. The IGP is a multi-module gas processing system designed to increase gas handling efficiency by combining multiple technologies into a single unit. The IGP contains three modules threaded together to form one monolithic unit installed below the main production pump. The Operator installed IGPs in three wells for field trials. Three key performance indicators were evaluated during the field trials: total uptime, total fluid production, and intake pressure. These parameters were compared to previous operation in the wells. It was observed that total oil production was increased by 34% on average, gas production increased by 15% on average and water increased by 40% on average. Intake pressure was reduced by 23% on average and uptime was increased on average by 10%. It was further noted that the ESP’s had a lower number of shutdowns (decreased by 59%) compared to the previous run. The drawdown of these wells increased due to the installation of the Integrated Gas Processor (IGP) compared to the previously installed systems.
Sour Fluid Partial Pressure and Electric Submersible Pumping System Survivability Pattern
Authors: Kalu-Ulu Torty C. 
Published: August 2024

Abstract
The behavior and survivability of electric submersible pumping systems (ESPs) used for hydrocarbon production vary from one condition to another. Sour environment is generally known to bring about stress cracking of some sort in well completion assembly. Regrettably, the pattern and correlation of the survivability of ESPs to partial pressure remains unclear. Therefore, this paper sets to assess the contributions of partial pressures to ESP systems durability and survivability in a sour environment. An assessment of the relationships of different ESP systems in such environment with naturally occurring element of varying partial pressure is conducted and discussed in the paper. Weibull two-parameter distribution function approach in addition to extensive literature review were applied to understand and represent the contributions of sour fluid partial pressures on ESP’s durability and survivability that operated in hydrocarbon environments. The partial pressures of naturally occurring element - hydrogen sulphide, was conducted and determined to exhibit varying behavioral patterns, and contributions to the durability and survivability of electric submersible pumps in contact with the well fluid. The results obtained were matched with the Bathtub curve to identify the reliability patterns common to ESP assembly completion strings because of the fluid partial pressures. From the analysis, the varied partial pressures considered had different effects on the survivability of ESP systems operating in the various environments. The patterns of the ESP systems in the sour fluid environment cut across three main regions of Bathtub-curve performance patterns, which defined early survivability pattern, and normal or constant operating survivability pattern, and the wear-out survivability pattern. ESP performance and survivability patterns were observed to vary as the partial pressures increased while normalizing at certain levels partial pressures plateauing at about 200 psi. Finally, the naturally occurring sour fluid’s partial pressure had normalizing effects on ESPs as the run-lives increased. The paper adds to the body of knowledge in the oil and gas industry by bringing to clarity the contributions of partial pressures on ESP systems performance and survivability patterns used in sour hydrocarbon environment.
ESP Testing: A Key Role in Enhancing Reliability
Authors: Foresti B. P. , Viana A. M. , Bacellar F. R. R. , Silva J. A. G. , Neves M. S. , Ribeiro M. P. , Oliveira P. S. , Costa B. M. P. , Cemin D. , Sousa C. F. 
Published: August 2024

Electrical Submersible Pumps (ESPs) have been manufactured since 1928 [1], and since then, much has changed regarding the equipment and its application scenarios. When they were first invented, ESPs were used in onshore fields for short tie-backs. Since then, the application scenario has changed significantly. Conversely, for Petrobras, they are mostly used in deep-water offshore fields with wet Christmas trees and long tie-backs, in most cases, inside subsea equipment (such as MoBo [2] or skid-mounted ESP [3]).
For the latter scenario, denominated as critical wells in Petrobras, the resources and costs involved in installing a new ESP and retrieving a faulty one are very different from those in the onshore scenario. Considering the rig costs and deferred production, for a subsea well, one operation might cost more than 30 million dollars. In the case of a premature failure that requires retrieving the faulty equipment and installing a new one, the impact is hence more than 60 million dollars. Once again, this is a very different scenario from the onshore scenario.
The world’s first ESP in a subsea well was installed by Petrobras in RJS-221 (Carapeba field) in 1994, in shallow water. Following that, in deep water, Petrobras installed an ESP in RJS-477 (Albacora Leste field) in 1998 [4]. From 1998 to around 2008, Petrobras experienced numerous premature failures with ESPs. The situation was so dire that there was even consideration given to abandoning the use of ESPs in favor of gas lift. This would result in lower production but also reduced deferred production and decreased workover costs.
A Tubing Anchor Engineered for Rod Pumping Horizontal Wells Improves Production Performance
Authors: Saponja J. , Hari R. , Brignac J. , Jaszan D. , Coyes C. , Chaudhry F. 
Published: August 2024

High gas to oil ratio (GOR) producing horizontal wells is now commonplace. This ratio continues to rapidly escalate as reservoirs suffer regional and basin wide pressure depletion. The North Dakota Bakkeni formation is a prime example of a concerning GOR trend and can be seen in Figure 1. Higher GOR's and depleted reservoir pressures lead to increased gas rates and multiphase fluid velocities within horizontal wellbores. Increased multiphase fluid velocities can then transport more damaging solids to a sucker rod pump and increase failure frequencies. Consequently, challenges for controlling failure frequencies and workover costs with sucker rod pumping continues to intensify, especially for improving downhole gas and solids separation.
Sucker rod pumping normally requires the tubing string to be secured or anchored to the casing, downhole near the sucker rod pump. Anchoring of tubing prevents tubing movement during a rod pump's operating cycle. Tubing movement can undesirably reduce downhole pumping efficiency and increase risks for damage to the tubing, casing, pump and sucker rods. A downhole tubing anchor (TA) or a downhole tubing anchor catcher (TAC) are a bottomhole assembly component installed for this purpose, but they can present risks for increasing operating expenses and limiting of a well's production potential.
Production can be limited if the annular flow path cross-sectional area of a tubing anchor (to the casing's internal diameter) is a flow path restriction. A flow path restriction negatively impacts downhole gas separation performance by causing multiphase flow instabilities. Further, sluggy and inconsistent multiphase flows that commonly emanate from a horizontal wellbore can worsen from a flow restriction, making downhole gas separation even more challenging. Flow restrictions can increase turbulence and then cause undesirable foaming and gas entrainment. Foaming of fluids is generally characterized by smaller gas bubbles in the liquid, which are more difficult to separate from the liquid.
Autonomous ESP Optimization Using Machine Learning Demonstrated in the Permian Basin
Authors: Erickson R. , Ramos R. , Meek J. , Benham D. , Haapanen B. , Hicks B. , Wheeler C. , Vasylyshyn B. 
Published: August 2024

Many oil and gas companies rely on natural intelligence, resident knowledge, and rules-based logic to optimize production. This is especially true for fields where electric submersible pumps (ESP) make up a considerable proportion of production. The nature of ESP artificial lift systems makes them well suited for greater remote monitoring, enhanced automation, and implementation of machine learning (ML) for autonomous optimization. Extensive use of electrical surface controls integrated with downhole sensors provides an ideal operating environment to implement Artificial Intelligence (AI) through machine learning to achieve autonomous full self-pumping (FSP) operation. However, most operating companies stop short of using automation and machine learning to its full potential.
This paper will present a case study highlighting the demonstration, refinement, and implementation of a machine learning algorithm to optimize multiple ESP wells in the Permian Basin. The paper will also present a case study for the development, demonstration, and refinement of an autonomous ESP optimization solution driven by this machine learning model. The paper will discuss key learnings from each study to assist operators in their digital journey with considerations for effective field implementation.
Optimizing Gas Lift Design: Unveiling Ideal Wellhead Temperature Across Diverse Reservoirs at Mehsana Oil Fields
Authors: Chanchlani K. , Gogoi R. , Gunwant D. , Rajak H. , Devshali S. , Meena S. , Kote N. 
Published: August 2024

Abstract
The operation of gas lift valves of the gas lift systems at field scale is controlled by the nitrogen pressure charged in the dome. Nitrogen pressure in gas lift systems is influenced by the gas injection temperature and production fluid temperature. In gas lift wells completed in water drive reservoirs, emulsion flowing with high water cut causes an increase in opening pressure of the topmost gas lift valves (GLV). When these wells are shut or provided with low gas injection supply pressure, these wells get loaded with minimal gas injection taking place. In depletion drive reservoirs, lower reservoir temperature causes a decrease in the opening pressure of the bottom-most gas lift valve, causing higher gas injection and lowers the grid pressure. In mixed drive reservoirs, any abrupt wellhead and reservoir temperature gradient will cause an ineffective gas lift operation. Flowing bottom-hole surveys with convection and conduction thermal methods are the prerequisites for the compact thermal model. Through the analysis, it was established that the nitrogen gas temperature in the dome is much more influenced by radial heat transfer along the mandrel-GLV interface than the axial heat transfer along the GLV body. The mathematical correlation for the ideal wellhead temperature was established based on heat transfer coefficients of production fluid and injection gas, and it can be expressed in terms of production fluid and injection gas temperatures. Conventional Gas Lift (CGL) wells experience the phenomenon of loading due to higher temperatures brought by bottom water to the surface and Intermittent Gas Lift (IGL) wells experience the problem of grid pressure drop. Both problems can be tackled by the unveiling of the wellhead temperature during design and can improve the efficiency by reducing downtime. The paper will focus on gas lift valves operating on diverse reservoir drive mechanisms and the calculation of their wellhead temperature using a unique thermal model for conventional gas lift mandrels.
Liquid Management in Gas Wells: Exploring the Impacts of Tubular Restrictions
Authors: Mateus-Rubiano Camilo , Alsanea Maziad , Karami Hamid 
Published: August 2024

Abstract
Liquid accumulation in gas wells impairs their production capabilities and reduces their operational lifespan. Various techniques have been explored to address this issue, yet no optimum solution has been identified for all wells. Operators continue to seek cheap and efficient methods to mitigate liquid loading in gas wells. Previous works have suggested that partial tubing restrictions, or inserts, have the potential to increase interfacial shear and droplet entrainment, thus delaying liquid loading. Due to increases in frictional pressure losses when inserts are present, a challenge remains in finding the operational conditions where their use results in a net positive effect for the well. In this work, experiments are conducted in a flow loop with a 25-ft vertical section, made from 2″ ID clear acrylic pipes, using air and Isopar-L oil at room temperature and near-atmospheric pressures. The accuracy of various two-phase flow models and correlations is evaluated for low superficial liquid velocities. Tests are conducted using insert rings with two internal diameters, 1.5″ and 1.75″. Liquid-gas flow pattern, liquid holdup, and pressure gradient are recorded and analyzed for each test. Results are compared with previous studies to assess the locality of the effects caused by the inserts and identify optimal conditions for their implementation
The combined effects of insert size and spacing are analyzed on well deliquification at various flowrates. Video recordings show the dual mechanism by which inserts enhance liquid lifting, droplet generation promotion and liquid film fallback retention. Results indicate that inserts are particularly effective in modifying flow behavior within the churn flow region. Commonly used models are inadequate to predict pressure gradient and liquid holdup in this flow pattern, particularly at low liquid rates. The use of a single insert shows positive changes in the liquid holdup compared to the tests without inserts. Yet, better outcomes are obtained for both liquid holdup and pressure gradient when two inserts are used. This configuration, with an 18-ft spacing between inserts, closely matches tubular joints length. This suggests that properly designed tubing joints can function similarly to inserts, offering a cost-effective and passive solution to mitigate liquid loading in gas wells. The optimum range to use this technique is for low liquid loading conditions and gas rates of churn flow. The results of the analysis can provide a guideline on the best conditions to apply this technique and significantly reduce the operational costs and improve the revenues.
Intelligent Autonomous System for Electrical Submersible Well Based on Metalearning Techniques
Authors: Lacret Angel , Camargo Edgar , Mendoza Edwin , Canelon Jose , Lacret Ybeth 
Published: August 2024

Summary
This work presents an intelligent autonomous system for Petroleum Processes (SAi2P), whose objective is to monitor and supervise wells for artificial lifting of crude oil specifically by electro-submersible pumping (ESP) integrating operational and financial scenarios. Thus, SAi2P will observe, interpret, make decisions, and execute actions that contribute to maintaining the most efficient operating conditions of the BES, seen from the paradigms of autonomic computing, data analytics (AdD), machine learning, and meta-learning. In general terms, the initial result is a practical Computing System (autonomous sub-cycle of the SAi2P, Analysis of the Operational Behavior of the Oil Well (ACo2P)) and functional that initially allows identifying failure patterns in a concise manner and that makes it possible to carry out simulated tests of the BES operation, which would be unfeasible to carry out in an operational environment.
The Utilization of Machine Learning and Deep Learning to Predict Real-Time ESP Well Status
Authors: Alquraini A. H. , Al Sadah H. H. , AlBori M. M. , Al-Kadem M. S. 
Published: August 2024

Abstract
One of the most common, efficient and reliable artificial lift methods used for lifting high volumes of fluids from wellbores is the Electric Submersible Pump (ESP). Thus, monitoring the live status of this ESP is essential to determine whether a well is on stream or off. In this research, a new methodology that utilize advanced Machine Learning (ML) to recognize ESP performance status in real time and provide it to engineers instantaneously.
In this research, the proposed methodology was to develop an intelligent system that consciously monitor ESP sensors and provide a reliable predicted well status to engineers. Firstly, the proposed system actively fetches real-time data from ESP sensors. Secondly, an advanced pool of ML algorithms was created, and trained on historical well status data. Finally, the real-time acquired data are fed to the advanced ML model to automatically identify ESP well status to engineer and notify them in advanced.
After finalizing the advanced ML system, it was evaluated on its performance to accurately predict the real-time status of ESP well and provided system users with targeted results. In addition, performance of the system on extraction, mapping and mitigation attributes were evaluated using ROC-AUC performance matrix. Validating and testing the ML model disclosed a promising outcome scoring accuracy exceeds 98 % which indicated high reliability of the model to accurately predict well status instantaneously. The developed ML system enabled engineers in the office to actively monitor well performance status fast and securely. Moreover, by implementing such a system, significant impact on our operation were achieved leading to cost and time savings. The developed ESP well model enhances the way artificial lift engineers visualize and analyze wells status in real time. It's worth noting that the proposed system lead to fast and substantial improvements in achieving a desired result field wise. Also, the system provides a detailed description and analysis of the well status to engineers.
The developed ESP performance recognition system has achieved significant fiancial and time saving especially in offshore location where a reliable ESP well and field status are critical in decision making saving millions of dollars as well as thousands of engineering hours.
Physics-Informed Reinforcement Learning for Motor Frequency Optimization in Electrical Submersible Pumps: Enhancing AI-Led Decision-Making in Production Optimization
Authors: Abdalla R. , Toumi O. , Gönczi D. , Sidaoui A. , Nikolaev D. , Schweiger A. , Schweiger G. 
Published: August 2024

Abstract
This paper presents a novel approach, Physics-Informed Reinforcement Learning (PIRL), designed to tackle optimization challenges within complex systems. Focusing on oil wells equipped with Electrical Submersible Pumps (ESP), the study aims to enhance decision- making processes by integrating physical principles with reinforcement learning techniques. The primary goal is to optimize motor frequencies for ESPs leading to maximizing production rates, reducing brake horsepower consumption, and ensuring operational efficiency within the Best Efficiency Performance (BEP) range. By leveraging PIRL, this research offers a promising avenue for enhancing productivity and efficiency in oil extraction processes, addressing the limitations of conventional practices, thereby enhancing decision making capabilities in production optimization. Traditionally, a constant frequency is applied over extended periods of time, disregarding variations in reservoir and fluid properties as well as operational field conditions. This approach often leads to suboptimal performance and unnecessary electricity consumption. In contrast, the proposed methodology employs reinforcement learning (RL) to develop a machine learning (ML) model, acting as an advisory system for dynamically adjusting operational frequencies. By continuously evaluating feedback from the system and adhering to operational, field, and reservoir constraints, the proposed framework offers an automated response to changes during the production phase of ESP wells, ultimately enhancing production efficiency and reducing energy consumption.