Development and Implementation of an Automated ESP Failure Database and Reliability Analysis Platform

2021 ◽  
Author(s):  
Robyn Rabbitt ◽  
Jesus Chacin
Keyword(s):  
Data Analytics ◽  
Data Transfer ◽  
Production Equipment ◽  
Lessons Learned ◽  
Integrated System ◽  
Net Benefit ◽  
Application Development ◽  
Commercial Software ◽  
Operational Conditions ◽  
Software Products

Abstract Identifying and prioritizing reliability improvement opportunities for ESPs, requires proper consideration of hundreds of parameters that include equipment characteristics, operational conditions, and root cause analyses results (Brookbank, E. B., 1997). One of the main challenges is that this data typically resides in a variety of commercial software products used internally by ConocoPhillips Canada as well as various other repositories such as spreadsheets, PDFs and numerous other internal databases and usually needs to be manually integrated for analysis. A second challenge is how to easily and consistently data mine such an extensive dataset. This paper presents the approach taken, hurdles faced, and results obtained to effectively address both challenges above. First, a failure database was designed to automatically capture time continuous data flows from various data streams, many of them flowing from commercial software tools but also some via email. To address the second challenge, an advanced visualizations and data analytics layer was developed to mine the database, in order to estimate various reliability and optimization metrics, uncover trends and generate forecasts instantaneously. Our solution was to create a unique cradle to grave ESP tracking and visualization integrated system, supporting the complete ESP reliability engineering workflow. It includes vendor to operator ESP equipment data transfer, database and nomenclature structure, operational data capture during the life of the ESP and RCA results data capturing via a 3rdparty low-code application development platform (LCADP). A visualization layer for data analytics and reliability metrics was seamlessly integrated through the use of a commercial software analytics and visualization platform (AVP). Results to date are very encouraging, both in terms of efficiency gains and quality of analysis and results. Consistent use of reliability metrics when used by different members of the production team have been achieved. Lessons learned during the development and specific examples on how the system is being used are presented, including AVP based trend visualization and failure forecast estimations. Key examples of the value captured with this Failure Database and Visualization Platform are also presented, including improved data quality, increased analytical capabilities and enhanced understanding of reliability improving options. The overall net benefit being optimized ESP life cycle costs. This development has the potential to be easily extended to other downhole production equipment such as fiber optic strings, liners, flow control devices, steam splitters and other artificial lift methods utilized in SAGD such as progressing cavity pumps.

Holistic Network Modelling for Debottlenecking of a Highly Integrated and Complex System for Optimizing Hydrocarbon Evacuation

2021 ◽  
Author(s):  
Frankie Kia Tan ◽  
Sukrut Shridhar Kulkarni
Keyword(s):  
Network Model ◽  
Data Transfer ◽  
Network Capacity ◽  
Integrated System ◽  
Situational Analysis ◽  
Network Modelling ◽  
Integrated Network ◽  
Field Development ◽  
Gas Network ◽  
Integrated Facility

Abstract This paper deals with debottlenecking approach of complex and integrated system through means of Holistic Modeling for optimizing hydrocarbon evacuation. As prudent operator for the complex network, it is crucial to pursue strategic ideas and innovative concepts to optimize supply demand balance, fulfill contractual obligations to optimize resources to maximize value creation, whilst protecting investment decisions for monetization of the new field development. It therefore necessitates to prioritize system reliability and de-bottlenecking initiatives to implement successful business plans with appropriate timely reconfiguration at various intensities of the network. It is consequently essential to decipher the pain points by performing root cause analysis and troubleshooting to achieve optimal fit for purpose solution by gaining better understanding of network characteristic, supply distribution & operating topology. Paper focus on a bold step change that was commenced to develop an end-to-end Holistic Network Model from well head (fields) to product delivery to scrutinize the network and propose suitable alleviation by appraising the debottleneck requirement at offshore riser collection manifold which serves as integrated facility for multiple hubs and fields. Model was validated with plant information and deployed to yield robust & realistic results. Multiple sensitivity scenarios were accomplished to analyze current riser manifold configuration limitation checks for tie-back of new field such as ullage opportunity, pressure variations, hydraulic fluxes, potential choking of low-pressure wells/fields and prospective blending specifications violations etc. Obstacles across affected manifold could be estimated and its reconfiguration was planned by means of variations in operating philosophy, alterations in the manifold assembly with appropriate manifold debottlenecking recommendation. Analytics of Integrated Network modelling could qualify not only technical obligations but also empower representative economic evaluation for debottlenecking by appending precise requirement in terms of manifold reconfiguration, backed up by appraised data from network model. Model output also assisted to gauze the potential for enhancing network capacity by implementing appropriate reforms to optimize evacuation for new field line ups. Integrated network model developed with an aid of basic network elements can be subjected to estimate vital features for comprehensive network such as pressure and flow across the various nodes in the system. Methodology describes how by developing an integrated network model that summarize the granularity of a highly complex offshore gas network has facilitated to strategize the manifold reconfiguration and appraise debottleneck requirement besides proposing appropriate mitigation. With integrated network modeled on a single platform allows a uniform data transfer from various elements such as fields, facilities, pipelines, gas highways and terminals into the model which assist for network optimization. The situational analysis via modeling could enable the elimination of new dedicated infrastructure for field evacuation leading to CAPEX optimization there by facilitating its optimal monetization. It reveals extensive usage of model with physical boundaries steering decision for project implementation.

A Holistic Approach to Achieve Excellence in Pipeline Security Using "SOLIDS"

2021 ◽  
Author(s):  
M. Rais
Keyword(s):  
Crude Oil ◽  
Asset Management ◽  
Management System ◽  
Oil And Gas ◽  
Detection System ◽  
Holistic Approach ◽  
Integrated System ◽  
Operational Conditions ◽  
Oil Pipeline ◽  
Detection Technology

Indonesian oil and gas transporter, PT Pertamina Gas (Pertagas), has a special task to operate the Tempino to Plaju Crude Oil Pipeline (TPCOP) to deliver 15,000 barrel-oil per day (BOPD) crude oil. Pertagas faced a big challenge and concern in the operation due to the frequent illegal tapping activities and risk of pipeline product theft. In 2012, 748 illegal taps cases or equal to a daily average of 2 cases were reported. The loss from crude oil transportation was approximately 40% per day and loss revenue was more than $20 million a year. Moreover, illegal tapping by cutting into pipelines can cause pipeline ruptures and explosions, leading to human casualties, destruction of property, and damage to the environment. Pertagas reported that illegal taps have increased to 400% from year 2010 to the year 2013. Efforts were taken to minimize the illegal tapping frequency by developing an integrated system that includes supervision and security of assets along the pipeline called “Security and Oil Losses Management with Integrated Detection System (SOLIDS)”. This system consists of Asset Management System (AMS), Liquid Management System (LMS), Leak Detection System (LDS), security patrol, Emergency Response Team (ERT), and is supported by Corporate Social Responsibility (CSR) programs. The implementation of SOLIDS proved to be an effective oil loss detection technology and pipeline security control that detects product thefts quickly and locates illegal tapping points accurately, so protective measures could be applied immediately. The implementation showed a good result. Pertagas has been succeeded in reducing losses from illegal taps from 748 cases in 2012 to zero cases in 2018. Consistent implementation of this system will provide a solution in reducing losses and illegal tapping under all operational conditions.

Novel Data Interface for Evaluating Cardiovascular Outcomes in Women

2011 ◽  
pp. 2094-2113
Author(s):  
Amparo C. Villablanca ◽  
Hassan Baxi ◽  
Kent Anderson
Keyword(s):  
Clinical Data ◽  
Success Factors ◽  
Data Transfer ◽  
Cardiovascular Outcomes ◽  
Lessons Learned ◽  
High Risk Women ◽  
Critical Success ◽  
Visual Basic For Applications ◽  
Extensible Markup ◽  
User Friendly

This chapter discusses critical success factors in the design, implementation, and utility of a new construct and interface for data transfer with broad applicability to clinical data set management. In the context of a data coordinating center for evaluating cardiovascular outcomes in high-risk women, we detail and provide a framework for bridging the gap between extensible markup language (XML) and XML schema definition file (XSD) in order to provide greater accessibility using visual basic for applications (VBA) and Excel. Applications and lessons learned are discussed in light of current challenges to healthcare information technology management and clinical data administration. The authors hope that this approach, as well as the logic utilized and implementation examples, will provide a user-friendly model for data management and relational database design that is replicable, flexible, understandable, and has broad utility to research professionals in healthcare.

scholarly journals MONIT: Monitoring the CERN Data Centres and the WLCG Infrastructure

2019 ◽  
Vol 214 ◽  
pp. 08031 ◽  
Author(s):  
Alberto Aimar ◽  
Asier Aguado Corman ◽  
Pedro Andrade ◽  
Javier Delgado Fernandez ◽  
Borja Garrido Bear ◽  
...  
Keyword(s):  
Open Source ◽  
Lessons Learned ◽  
Monitoring Data ◽  
Commercial Software ◽  
And Performance ◽  
Monitoring Service ◽  
Monitoring Architecture ◽  
Data Centres ◽  
Cloud Resources

The new unified monitoring architecture (MONIT) for the CERN Data Centres and for the WLCG Infrastructure is based on established open source technologies to collect, stream, store and access monitoring data. The previous solutions, based on in-house development and commercial software, have been replaced with widely- recognized technologies such as Collectd, Kafka, Spark, Elasticsearch, InfluxDB, Grafana and others. The monitoring infrastructure, fully based on CERN cloud resources, covers the whole workflow of the monitoring data: from collecting and validating metrics and logs to making them available for dashboards, reports and alarms. The deployment in production of this new DC and WLCG monitoring is well under way and this contribution provides a summary of the progress, hurdles met and lessons learned in using these open source technologies. It also focuses on the choices made to achieve the required levels of stability, scalability and performance of the MONIT monitoring service.

Toward Evidence-Based Software Engineering: Lessons Learned in Healthcare Application Development

IEEE Software ◽  
2017 ◽  
Vol 34 (5) ◽  
pp. 67-71 ◽  
Author(s):  
Artur Nowak ◽  
Holger J. Schunemann
Keyword(s):  
Software Engineering ◽  
Lessons Learned ◽  
Evidence Based ◽  
Application Development ◽  
Healthcare Application

Big data analytics for proactive industrial decision support

atp magazin ◽  
2016 ◽  
Vol 58 (09) ◽  
pp. 62 ◽  
Author(s):  
Martin Atzmueller ◽  
Benjamin Klöpper ◽  
Hassan Al Mawla ◽  
Benjamin Jäschke ◽  
Martin Hollender ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Historical Data ◽  
Big Data Analytics ◽  
Lessons Learned ◽  
Support Functions ◽  
Big Data Applications ◽  
Big Data Technologies ◽  
Process Plants ◽  
Plant Data

Big data technologies offer new opportunities for analyzing historical data generated by process plants. The development of new types of operator support systems (OSS) which help the plant operators during operations and in dealing with critical situations is one of these possibilities. The project FEE has the objective to develop such support functions based on big data analytics of historical plant data. In this contribution, we share our first insights and lessons learned in the development of big data applications and outline the approaches and tools that we developed in the course of the project.

scholarly journals Lessons Learned From Implementing an App-Based Resilience Training Program in a Naval Operational Setting

Iproceedings ◽  
10.2196/14935 ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. e14935
Author(s):  
Cynthia Simon-Arndt ◽  
Suzanne Hurtado ◽  
Casey Kohen ◽  
Michael Hunter ◽  
Sandra Sanchez
Keyword(s):  
Training Program ◽  
Military Service ◽  
Training System ◽  
Lessons Learned ◽  
Service Members ◽  
Training Time ◽  
Response Options ◽  
Operational Conditions ◽  
Training Support ◽  
Resilience Training

Background Enhancing resilience and reducing stress are critical to increasing the readiness and performance of military personnel in operational settings. Stress and resilience programs can improve service members’ ability to manage their stress during both normal and extreme operational conditions, and have the potential to enhance safety at sea. Implementing an efficient and effective application-based training program in a military setting has unique challenges, including minimizing intrusion on the command’s training time and technological considerations (eg, Wi-Fi and Bluetooth technology restrictions). Objective An enhanced version of a training program called the Stress Resilience Training System (SRTS) was implemented into the operating environment of a naval vessel. The system contains an in-person workshop, regular mentoring in resilience-building techniques, and an iPad-based app used for biofeedback of heart rate variability coherence and training support. This work describes the lessons learned from the implementation process of the app component of the program, based on responses from active duty service members. Methods Crew members aboard a Navy vessel (N=92) volunteered to participate in the evaluation of the 10-week program. All ship personnel were provided with an initial 2.5-hour workshop, mentorship, and iPads containing the SRTS app to use for the duration of the 10-week program. Participants rated different components of the training, and their app usage during the course of the study was recorded. Results Participants somewhat agreed that the app was appropriate for military service members (mean 2.51, SD 1.14; response options 0=strongly disagree to 4=strongly agree for all ratings) and were somewhat likely to recommend the app to fellow service members (mean 2.53, SD 1.03). Ratings of the workshop’s relevance to military readiness (mean 2.68, SD 0.95) and of the instructors’ credibility (mean 3.22, SD 0.92) were higher than ratings of the app. Additionally, usage of the app was low and highly variable (mean 42.26, SD 60.53; range 0 to 312.54 minutes). Anecdotal evidence provided by crewmembers suggested that using the app on an iPad was cumbersome and that the Wi-Fi was often inaccessible, making the iPad a less valuable tool overall. Conclusions This implementation of the app component of SRTS raised questions regarding the suitability of the technological format for this operational setting. User ratings and participant comments suggested that the technology was not the most successful component of the program. The implementation in the iPad format was not conducive to the operational setting and the inconvenience of this format may have deterred participants from using it in settings where a personal or more compact device may have been more appropriate. Recommendations going forward include making the app component available for use on smartphones operating on both iOS and Android platforms to make it user friendly, accessible, and more engaging, which, in turn, is expected to increase usage and uptake of the program’s techniques. Furthermore, incorporating more engaging content, gamification, and tracking and reporting user progress into the overall app may enhance motivation to use more components of the app and increase usage, ultimately enhancing its impact on resilience.

scholarly journals Online modelling of water distribution systems: a UK case study

2010 ◽  
Vol 3 (1) ◽  
pp. 21-27 ◽  
Author(s):  
J. Machell ◽  
S. R. Mounce ◽  
J. B. Boxall
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Data Transfer ◽  
Simulation Models ◽  
Distribution Networks ◽  
Water Supply Systems ◽  
Full Potential ◽  
Operational Conditions ◽  
The Impact

Abstract. Hydraulic simulation models of water distribution networks are routinely used for operational investigations and network design purposes. However, their full potential is often never realised because, in the majority of cases, they have been calibrated with data collected manually from the field during a single historic time period and, as such, reflect the network operational conditions that were prevalent at that time, and they are then applied as part of a reactive, desktop investigation. In order to use a hydraulic model to assist proactive distribution network management its element asset information must be up to date and it should be able to access current network information to drive simulations. Historically this advance has been restricted by the high cost of collecting and transferring the necessary field measurements. However, recent innovation and cost reductions associated with data transfer is resulting in collection of data from increasing numbers of sensors in water supply systems, and automatic transfer of the data to point of use. This means engineers potentially have access to a constant stream of current network data that enables a new era of "on-line" modelling that can be used to continually assess standards of service compliance for pressure and reduce the impact of network events, such as mains bursts, on customers. A case study is presented here that shows how an online modelling system can give timely warning of changes from normal network operation, providing capacity to minimise customer impact.

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