bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design, Development and First Operation of a New Redirected Gas Lift Mandrel
Authors: Fraga R. S. , Barrionuevo D. C. , Perovano T. G. , Guerra L. A. O. , Almeida A. R. , Rodrigues H. T. 
Published: August 2024

Abstract
Traditionally in oil production wells that employ gas lift as an artificial lift method, the injection of lift gas is commonly performed from the annular space to the interior of the production tubing string, at a downward oriented angle (in the opposite direction to the fluid flow delivered by the reservoir). The downward gas jet causes turbulence in the flow due to the sudden changes in flow direction, precisely at the location of the gas lift mandrel, which results in a localized additional pressure drop. Optimization of the geometry responsible for the gas injection into the production tubing string consisting of changing the lift gas injection angle is a strategy aimed at achieving production gains by reducing the localized pressure drop. Theoretical mathematical analysis applied to this fluid flow problem, along with computational simulations and experimental execution, showed that, for high gas injection flow rates and/or the adoption of small diameters of the injected gas jet, it is possible to obtain a production gain at a relatively low cost by reversing the direction of lift gas injection. This paper briefly explains the process of conception, development, qualification and prototype operation of the redirected gas lift mandrel.
Observing Dynamic Well Behaviour During Gas Lift with Slickline Deployed Distributed Fiber Optic Sensing Helps Diagnose Well Performance Issues in the White Tiger Field Vietnam
Authors: Webster M. J. , Ferguson N. J. , Nguyen D. Q. , Hoang M. V. , Tran N. T. , Pham T. C. , Vu T. H. 
Published: August 2024

Abstract
Surveillance of dynamic well performance is problematic using conventional sensors as only one location can be observed. But during gas lift, multiple points of gas entry may be active over large distances in a well. This paper presents a case study using a Distributed Fiber Optic Sensing (DFOS) enabled Slickline to monitor the entire length of the well over the whole duration of the survey to enhance well performance diagnostics.
Conventional logs measure events local to the sensor as its pulled uphole. Many dynamic events affect the entire wellbore and can be intermittent in nature. The diameter of conventional logging tools may disturb what they try to measure or are recorded over restricted rates for safety reasons. A DFOS Slickline system was deployed in a gas lifted well to diagnose well performance. Data was recorded over the entire well for the duration of the survey flowing at conventional production rates. This data was processed at wellsite and a quicklook provided within hours of survey.
This is a case study from a gas lifted well in the White Tiger field in Vietnam. Results show the behaviour during both an annulus bleed phase and gas lift injection phase over all 7 side pocket mandrels simultaneously providing evidence showing which mandrel was faulty. The results provided clear evidence of an inefficient gas lift system with a significant reduction in drawdown with consequential loss of production. An intervention to resolve the issue resulted in a significant enhancement of the wells production. The survey provided critical information to help plan remediation and restoration of stable production resulting in an over 300% increase in oil production.
The use of slickline DFOS allowed for the continual monitoring over all gas lift valves simultaneously during kickoff and production of the well. This increased confidence in the diagnosis and remediation needed to restore production.
Successful Application of All-Metal PCP in CSS and Steam Flood to Unlock Hard-To-Recover Oil Resources
Authors: Skoczylas Paul , Sawafi Mohammed , Salem Basem Ahmed , Al Jabri Sulaiman , Zadjali Ahmed , Ponomarenko Roman 
Published: August 2024

Abstract
Petroleum Development Oman (PDO) operates diverse fields in Oman, facing challenges in recovering hard-to-recover oil resources characterized by high viscosity and low reservoir temperature in one of the developing fields. Despite implementing Cyclic Steam Stimulation (CSS), the wells exhibit suboptimal responsiveness to steam cycles, rendering conventional Artificial Lift Systems (ALS) ineffective due to high viscosity impact.
Following unsuccessful attempts with other ALS, the decision was made to explore All Metal Progressing Cavity Pumps (AMPCP). AMPCPs were chosen for their capability to seamlessly transition to injection of 350°C Steam through the Stator without requiring extensive workovers. Notably, AMPCP demonstrated resilience against high overloads in cold conditions, enhancing production cycles and reducing reservoir pressure, thereby improving the efficiency of steam injection cycles. The main objective of the project is to enhance the effectiveness of steam support, potentially leading to a shift from CSS to steam flood improving overall production.
Addressing these issues, All- Metal PCP Technology appears to be a reliable solution due to its durable design and ability to withstand high loads when fluid viscosity significantly increases at low temperatures. A field trial has been done to test the performance of AMPCPs in PDO's field in Oman. Out of the 15 installations conducted so far, four are operational, three are awaiting commissioning and six pulled AMPCPs have been re-qualified for re-run. The longest run life so far is 1037 days. It is worth noting that two wells have successfully transitioned to steam flood, improving efficiency of extraction method. Although there were some challenges related to scale and solids plugging, the resilience of AMPCPs has allowed for their re-installation after being operational on a test bench following rotor extraction. The PCM Metal to Metal technology has demonstrated exceptional performance within the low temperature range of 30°C – 60°C, handling viscosities up to 30000 cP in addition to high temperature application. Its ability to withstand high overloads, reaching up to 130% on PCP head loading, confirms its suitability for high-viscosity scenarios
High viscosities cause challenges such as high friction losses, overloading ALS systems and leading to infant failures and significant workover costs. The AMPCP application for unconventional oil recovery, is a proven method to produce the unconventional reservoir, when the conventional ALS methods fail.
Successful Field Trial of Well Completion with Suitable Artificial Lift in Cbm Horizontal Wells of India
Authors: Sharan S. K. , Keswani V. H. 
Published: August 2024

Abstract
Horizontal wells are drilled within Reliance Coalbed Methane (CBM) in India to increase productivity. This can be facilitated by reducing FBHP to a minimum. The commingled flow of gas and water causes high Gas Volume Fraction (GVF) at pump intake. Gas separators with suitable lifting systems were critical to reduce GVF. Well completion was designed with Progressive Cavity Pumps to handle the production of coal fines whilst catering to the chances of high rod-tubing wear.
(GAS HANDLER PCP) were expected to provide improved run-life in these conditions. Software simulation was used to optimize the placement of rod guides and centralizers on the rod string to minimize tubing integrity problems. The process of evaluation and optimization involved the deployment of different Well completion of AL and Gas separators with a provision for metering free gas from tubing to determine GVF. Well, operation and monitoring were optimized with the use of RPM, flow rate, and GVF. Minimum pump submergence was respected to avoid pump failure. Both PCPs and GAS HANDLER PCPs were installed to provide a run-life comparison
The results of the trial have been positive to date, and The GAS HANDLER PCP along with the designed well completion has allowed run times of the pump to increase significantly. The rod string design through Software simulation supplemented the increased run times achieved. Remarkable improvement in reducing GVF was accomplished by proper selection of gas separator. The combination of a gas separator and GAS HANDLER PCP has achieved a very low Flowing Bottom Hole Pressure (FBHP – 20 to 25 psi) for an acceptable period. After successful results from the completion of the trial, Reliance CBM has scaled up the implementation of this technology in multi-lateral CBM Horizontal wells. It has proven to be the most cost-effective method to complete and produce from a CBM horizontal well. With the substantial increase in productivity from CBM wells this technology is set to change the course of how CBM field can be developed more productively.
Work is continuing to improve the well production lifespan with the addition of a Tubing Rotator and close monitoring of tubing wear analysis. It will eliminate the cumbersome and costly hydraulic fracturing (HF) operations in coal seams with or without contrasting boundaries (shale boundary). Significant reduction in environmental hazards due to HF is an advantage, that will encourage more operators to adopt this technology. Horizontal wells in CBM will enhance the gas production output of India.
Gas Lift Optimization in the Permian Using Machine Learning and Artificial Intelligence
Authors: Movahed P. , Burmaster D. , Karantinos E. , Villarreal A. L. , Memarzadeh M. , Vela S. G. , Tapley S. C. , Newlin C. , Banes T. A. 
Published: August 2024

Summary
Gas lift is among the most prevalent artificial lift methods in the Permian Basin, accounting for over 50% of total oil production. Despite that, gas lift optimization has historically been a time-consuming process, which limited optimization efforts to cases with the most significant potential for improvement. Automated gas lift optimization can add incremental volumes without the need for major OPEX/CAPEX expenditures. In this paper, we present a closed-loop iterative well-by-well Gas Lift Optimization Workflow deployed to more than 1300 ExxonMobil wells in the Permian Basin. The workflow conducts multi-rate tests via remote control of gas lift injection rate setpoints in combination with automated well data acquisition. Optimal injection rate setpoints are determined by quantifying the relationship between gas injection rate and downhole pressure, and automatically maximizing drawdown/production. This is achieved with minimal disturbance to the surface facilities network. A machine learning model provides optimization recommendations for wells without a downhole pressure gauge. Production data undergoes a rigorous quality control process to ensure that measurements are accurate and representative of current well conditions. Incremental uplift is tracked using a model-based approach based on well productivity and steady-state well tests. The optimization workflow has been applied to more than 1300 wells, with an average oil production uplift of approximately 2.0%.
State of the Art of Patient Therapeutic Education in Morocco: A Systematic Literature Review
Authors: El Habchi Maha , Elouardi Abdelghani , El Aatik Yassine , Doghmi Kamal 
Published: August 2024

Introduction
This article examines the current state of Therapeutic Patient Education (TPE) in Morocco through a systematic literature review. With the rising prevalence of chronic diseases in the country, TPE is pivotal in aiding patients to manage their conditions and treatments, thus enhancing their quality of life. Despite the efforts of Moroccan authorities to promote TPE, its utilization remains largely constrained, partly due to the lack of structured programs and accessible data.

Objective
In this manuscript, we explore the current state of existing TPE, focusing on various therapeutic education interventions for patients in Morocco. This study aims to enhance public health policies and practices in Morocco by exploring existing TPE interventions.

Results
The systematic review analyzed 11 studies from 2010 to 2024. Recommendations from the World Health Organization (WHO) and other relevant bodies could facilitate the integration of TPE into healthcare systems. However, challenges persist, including region-specific obstacles in Morocco and the need for enhanced training of healthcare professionals.

Conclusion
This systematic review underscores the importance of investing in TPE and offers insights into research, clinical practice, and health policies in Morocco. Despite its potential, sustained attention and further efforts are necessary to ensure the comprehensive integration of TPE into Moroccan healthcare settings.
Cristo Rey Schools and the Preferential Option for the Poor
Authors: Robinson Julie , Cooney Pauline , McKinney Stephen 
Published: August 2024

Cristo Rey schools are a unique and distinctive form of Jesuit education. They have been very successful since the mid 1990s and are deemed to be coherent with Jesuit educational principles and the preferential option for the poor. They are only available to young people from low-income homes and are open to young people of all faiths and none. The Cristo Rey schools offer an intense and supportive environment for the students and prepare them for admission to college and university. Nevertheless, there are critiques of these schools that focus on: the financial model that means that the students must work one day a week; the nature of this work and questions about the ethical perspectives of the employers. There are further questions about cultural dissonance between the students and staff of the schools. This article explores the sociological and theological foundations of the Cristo Ray schools, evaluates their effectiveness and success and analyses the various points that are raised in the critique of these schools.
The “Magical Theory” of AI in Medicine: Thematic Narrative Analysis
Authors: Lorenzini Giorgia , Arbelaez Ossa Laura , Milford Stephen , Elger Bernice Simone , Shaw David Martin , De Clercq Eva 
Published: August 2024

Background
The discourse surrounding medical artificial intelligence (AI) often focuses on narratives that either hype the technology’s potential or predict dystopian futures. AI narratives have a significant influence on the direction of research, funding, and public opinion and thus shape the future of medicine.

Objective
The paper aims to offer critical reflections on AI narratives, with a specific focus on medical AI, and to raise awareness as to how people working with medical AI talk about AI and discharge their “narrative responsibility.”

Methods
Qualitative semistructured interviews were conducted with 41 participants from different disciplines who were exposed to medical AI in their profession. The research represents a secondary analysis of data using a thematic narrative approach. The analysis resulted in 2 main themes, each with 2 other subthemes.

Results
Stories about the AI-physician interaction depicted either a competitive or collaborative relationship. Some participants argued that AI might replace physicians, as it performs better than physicians. However, others believed that physicians should not be replaced and that AI should rather assist and support physicians. The idea of excessive technological deferral and automation bias was discussed, highlighting the risk of “losing” decisional power. The possibility that AI could relieve physicians from burnout and allow them to spend more time with patients was also considered. Finally, a few participants reported an extremely optimistic account of medical AI, while the majority criticized this type of story. The latter lamented the existence of a “magical theory” of medical AI, identified with techno-solutionist positions.

Conclusions
Most of the participants reported a nuanced view of technology, recognizing both its benefits and challenges and avoiding polarized narratives. However, some participants did contribute to the hype surrounding medical AI, comparing it to human capabilities and depicting it as superior. Overall, the majority agreed that medical AI should assist rather than replace clinicians. The study concludes that a balanced narrative (that focuses on the technology’s present capabilities and limitations) is necessary to fully realize the potential of medical AI while avoiding unrealistic expectations and hype.
A Brief Web-Based Person-Centered Care Group Training Program for the Management of Generalized Anxiety Disorder: Feasibility Randomized Controlled Trial in Spain
Authors: Ramos-García Vanesa , Rivero-Santana Amado , Peñate-Castro Wenceslao , Álvarez-Pérez Yolanda , Duarte-Díaz Andrea , Torres-Castaño Alezandra , Trujillo-Martín María del Mar , González-González Ana Isabel , Serrano-Aguilar Pedro , Perestelo-Pérez Lilisbeth 
Published: August 2024

Abstract

Background
Shared decision-making (SDM) is a crucial aspect of patient-centered care. While several SDM training programs for health care professionals have been developed, evaluation of their effectiveness is scarce, especially in mental health disorders such as generalized anxiety disorder.

Objective
This study aims to assess the feasibility and impact of a brief training program on the attitudes toward SDM among primary care professionals who attend to patients with generalized anxiety disorder.

Methods
A feasibility randomized controlled trial was conducted. Health care professionals recruited in primary care centers were randomized to an intervention group (training program) or a control group (waiting list). The intervention consisted of 2 web-based sessions applied by 2 psychologists (VR and YA), based on the integrated elements of the patient-centered care model and including group dynamics and video viewing. The outcome variable was the Leeds Attitudes Towards Concordance scale, second version (LATCon II), assessed at baseline and after the second session (3 months). After the randomized controlled trial phase, the control group also received the intervention and was assessed again.

Results
Among 28 randomized participants, 5 withdrew before the baseline assessment. The intervention significantly increased their scores compared with the control group in the total scale (b=0.57; P=.018) and 2 subscales: communication or empathy (b=0.74; P=.036) and shared control (ie, patient participation in decisions: b=0.68; P=.040). The control group also showed significant pre-post changes after receiving the intervention.

Conclusions
For a future effectiveness trial, it is necessary to improve the recruitment and retention strategies. The program produced a significant improvement in participants’ attitude toward the SDM model, but due to this study’s limitations, mainly the small sample size, more research is warranted.
Newly Qualified Canadian Nurses’ Experiences With Digital Health in the Workplace: Comparative Qualitative Analysis
Authors: Kleib Manal , Arnaert Antonia , Nagle Lynn M , Sugars Rebecca , da Costa Daniel 
Published: August 2024

Background
Clinical practice settings have increasingly become dependent on the use of digital or eHealth technologies such as electronic health records. It is vitally important to support nurses in adapting to digitalized health care systems; however, little is known about nursing graduates’ experiences as they transition to the workplace.

Objective
This study aims to (1) describe newly qualified nurses’ experiences with digital health in the workplace, and (2) identify strategies that could help support new graduates’ transition and practice with digital health.

Methods
An exploratory descriptive qualitative design was used. A total of 14 nurses from Eastern and Western Canada participated in semistructured interviews and data were analyzed using inductive content analysis.

Results
Three themes were identified: (1) experiences before becoming a registered nurse, (2) experiences upon joining the workplace, and (3) suggestions for bridging the gap in transition to digital health practice. Findings revealed more similarities than differences between participants with respect to gaps in digital health education, technology-related challenges, and their influence on nursing practice.

Conclusions
Digital health is the foundation of contemporary health care; therefore, comprehensive education during nursing school and throughout professional nursing practice, as well as organizational support and policy, are critical pillars. Health systems investing in digital health technologies must create supportive work environments for nurses to thrive in technologically rich environments and increase their capacity to deliver the digital health future.
Digital Health as a Mechanism to Reduce Neonatal Intensive Care Unit Admissions: Retrospective Cohort Study
Authors: Brinson Alison K , Jahnke Hannah R , Henrich Natalie , Moss Christa , Shah Neel 
Published: August 2024

Abstract

Background
Admission to the neonatal intensive care unit (NICU) is costly and has been associated with financial and emotional stress among families. Digital health may be well equipped to impact modifiable health factors that contribute to NICU admission rates.

Objective
The aim of the study is to investigate how the use of a comprehensive prenatal digital health platform is associated with gestational age at birth and mechanisms to reduce the risk of admission to the NICU.

Methods
Data were extracted from 3326 users who enrolled in a comprehensive digital health platform between January 2020 and May 2022. Multivariable linear and logistic regression models were used to estimate the associations between hours of digital health use and (1) gestational age at birth and (2) mechanisms to reduce the risk of a NICU admission. Multivariable logistic regression models estimated the associations between (1) gestational age at birth and (2) mechanisms to reduce the risk of a NICU admission and the likelihood of a NICU admission. All analyses were stratified by the presence of any gestational conditions during pregnancy.

Results
For users both with and without gestational conditions, hours of digital health use were positively associated with gestational age at birth (in weeks; with gestational conditions: β=.01; 95% CI 0.0006-0.02; P=.04 and without gestational conditions: β=.01; 95% CI 0.0006-0.02; P=.04) and mechanisms that have the potential to reduce risk of a NICU admission, including learning medically accurate information (with gestational conditions: adjusted odds ratio [AOR] 1.05, 95% CI 1.03-1.07; P<.001 and without gestational conditions: AOR 1.04, 95% CI 1.02-1.06; P<.001), mental health management (with gestational conditions: AOR 1.06, 95% CI 1.04-1.08; P<.001 and without gestational conditions: AOR 1.03, 95% CI 1.02-1.05; P<.001), and understanding warning signs during pregnancy (with gestational conditions: AOR 1.08, 95% CI 1.06-1.11; P<.001 and without gestational conditions: AOR 1.09, 95% CI 1.07-1.11; P<.001). For users with and without gestational conditions, an increase in gestational age at birth was associated with a decreased likelihood of NICU admission (with gestational conditions: AOR 0.62, 95% CI 0.55-0.69; P<.001 and without gestational conditions: AOR 0.59, 95% CI 0.53-0.65; P<.001). Among users who developed gestational conditions, those who reported that the platform helped them understand warning signs during pregnancy had lower odds of a NICU admission (AOR 0.63, 95% CI 0.45-0.89; P=.01).

Conclusions
Digital health use may aid in extending gestational age at birth and reduce the risk of NICU admission.