Instructor: Francisco E. Trevisan

Disciplines: Production and Operations

Once the ESP Dismantle, Inspection, and Failure Analyses (DIFAs) are concluded, the production professional must turn the lessons learned from all the individual ESP failures into information that identifies the most efficient way to apply the limited time and resources towards improving ESP run-life. The key process for this is to conduct a reliability analysis.

This course is designed to give the attendees an overview of the existing best practices towards ESP reliability data collection, metrics, and analyses. Discussions begin with some important nomenclature definitions, parameters typically collected, and best practices for building an ESP installation database. The lecture then transitions to a more theoretical content; for a brief overview of the mathematical and statistical tools used in reliability engineering. Later application of the theory is reviewed, to properly build and analyze survival curves and different metrics (such as Failure Rate, MTTF, and MTTP), and how they can be used to identify early failures, track run-life improvements, and estimate the number of workover and ESP needed for the next time period. Guidance is provided to the trainees on how to build their own Key Performance Indicators (KPIs) graphs and dashboards using MS-Excel.

Topics:

• Data Collection: Definitions, Standards, Best Practices, and Examples
• Database Structure
• Life-Time Distributions and Survival Function Analysis
• Run-Life Measures: Definitions, Best Practices, and Examples

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Instructors: Jeff Dwiggins and Kristen Munguia

Disciplines: Production and Operations

Course Description:

his advanced course is intended for artificial lift and production professionals currently working with or managing ESPs. The teardown (or dismantle) of the ESP is the final phase of an ESP’s operation, but one that can give the most information on how the ESP performed during its life. Additionally, and maybe more importantly, the teardown and subsequent analysis can tell you why it failed. This key step is not simply taking each component apart, the ESP must be disassembled in a particular order, carefully inspecting for specific failure modes at each step, and, that order may vary with conditions and circumstances.

• Types and expectations of ESP teardowns and failure analyses
• How to incorporate failure analysis into daily operations
• Who should participate in the failure analysis process
• ESP failure modes caused by various operating conditions
• Vendor nomenclature and procedures for failure analysis
• Determining root cause

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Instructor: Lawrence Camilleri 

Disciplines: Production and Operations

Course Description:

This course provides the production engineer with the physics and petroleum engineering tools to understand the how and why of both ESP design and production optimization:

• Design: The engineer will acquire the engineering tools to forecast production with ESP simulations and generate cumulative production curves for a range of IPR curves and rising GOR which capture the effect of depletion over time.
   
• Production optimization: Utilizing real-time gauge data and production rate measurements to select the optimum frequency and choke settings to maximize drawdown, while managing the impact of gas.

With the increase in wells operating in saturated conditions, such as unconventional wells, the agenda provides a focus on ESP behavior in high GVF (gas void fractions) environments i.e. two-phase flow (liquid and gas) with an explanation of both the physics and a detailed review of five case studies, which cover both “gas locking” and slugging effects.

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Instructors: Carlos Yicon, Walter Dinkins, and Hany Zakhary

Disciplines: Production and Operations | Data Science and Engineering Analytics

Course Description:

This course equips learners with the tools to operate permanent magnet motor (PMM) systems effectively. Artificial lift engineers will learn methods to size ESPs driven by PMMs, ensuring a safe and efficient artificial lift method. As most PMMs require VFDs, the course covers the design, application, installation, maintenance, and troubleshooting of PMM and VFD systems. It also addresses how these systems adapt to changing well conditions in unconventional settings. The course includes theory, case studies, and hands-on practice.

Agenda

• PMM: Operating Principle
• Design, compare with IM
• Testing and qualification (PMM and VSD control)
• Industry Standards
• Power studies of IM versus PMM systems
  • Example procedure
  • Power Savings
• Procedures / Operation
  • Operation - VSD set ups, the importance of this and what could happen if the drive is not set up properly
  • Operation - the do's and don't to changes in control
  • Operation - Power optimization on the fly
• Safety Considerations
  • Safety - downhole tools and processes for safety during installation trouble shooting and pulling
  • Safety - training program
  • Safety - installation and pull check list
  • Safety - PMM identification when shipped to location
• Alternative applications such as low speed PCP, high speed ESP and linear PMM will be briefly covered.

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Instructors: Rajan Chokshi

Disciplines: Production and Operations | Data Science and Engineering Analytics

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

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