Surveillance, Optimization and Data Analytics Workflows for ESP Engineers

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Disciplines: Production and Operations

Course Description

Course Description
To ensure profitable ESP well operation with minimal NPT and failure rates, robust surveillance and optimization are crucial. Real-time data streams from heavily instrumented ESP wells can be challenging to manage with traditional methods. The course bridges gaps by using data analytics, machine learning approaches facilitated by generative AI.

 In this hands-on course, the participants learn about surveillance, optimization, data analysis and data science techniques and workflows applied to ESP wells while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles. After completing the course, participants will have a set of tools and some pathways to analyze and manipulate their data in the cloud, find trends, and develop data-driven models.
Specifically, the following use cases are discussed covering their business impact, code walkthroughs, and solutions: 
•    ESP state identification 
•    Virtual Flow Meter 
•    Choke flow rate Estimation for high-volume wells using offshore dataset. 
•    Reservoir Productivity assessment for unconventional wells
•    ESP Failure Analysis and Prediction 

Customization
•    The training can be extended to 2-days or four half-day long virtual sessions. The extended option includes five additional use cases.
•    Client’s dataset-based examples are optionally incorporated in the class discussions. This option requires discussions with the client about the problem, two-days of consulting effort, and access to the client dataset at least 4 weeks before the class. 

Learning Outcomes
After completing the course, participants will have a set of tools and some pathways to model and analyze their ESP wells’ data in the cloud, find trends, and develop data-driven models.
 

Learning Level

Intermediate

Course Length

1-day

Why Attend

Business Impact
This course/workshop aims to give an understanding of surveillance, data analytics, and machine learning principles as they relate to ESP wells through practical applications. Field data is employed to clarify workflows related to surveillance, optimization, and data analysis. The participants will assess and extract value from the data sets with the help of easy-to-follow solution scripts. The practical, hands-on approach will enable them to confidently test these techniques on their ESP well data.

Who Attends

This Intermediate level course is primarily intended for artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets.

Special Requirements

This Intermediate level course is primarily intended for artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets.

CEUs

.8 CEU/8 PDH for this 1 day course

Cancellation Policy

All cancellations must be received no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Refunds will not be given due to no show situations.

Training sessions attached to SPE conferences and workshops follow the cancellation policies stated on the event information page. Please check that page for specific cancellation information.

SPE reserves the right to cancel or re-schedule courses at will. Notification of changes will be made as quickly as possible; please keep this in mind when arranging travel, as SPE is not responsible for any fees charged for cancelling or changing travel arrangements.

We reserve the right to substitute course instructors as necessary.

Instructor

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