ESP Model Parameter Recalibration via Self-Organizing Map Analysis
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Solution Overview
Problem
Traditional methods for recalibrating electrical submersible pump (ESP) design parameters are tedious, error-prone, and inefficient, often requiring manual trial-and-error processes to match ESP performance data with SCADA measurements, making it difficult to identify optimal design parameters for thousands of models.
Innovation Solution
An automated system using a Self-Organizing Map (SOM) and averaging analysis to generate training data sets, cluster similar data rows, and recalibrate ESP model input parameters to match measured output parameters within error tolerances, reducing human intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual trial-and-error methods are used to adjust ESP design parameters, then the process allows for human judgment and flexibility, but the process becomes tedious, error-prone, and inefficient when updating thousands of models
Solution Approach 1:
The patent replaces the manual mechanical process of trial-and-error parameter adjustment with an automated computer-based system that uses algorithms to systematically modify design parameters and match SCADA measurements, eliminating human error and dramatically increasing throughput capability
Solution Approach 2:
The system enables self-service automation where the computer automatically performs parameter recalibration without human intervention, allowing thousands of models to be updated independently and simultaneously, transforming a labor-intensive process into an autonomous computational task
2Measurement precision
If manual analysis is used to identify optimal design parameters, then the analyst can apply expert judgment, but it is unlikely that the analyst will be able to resolve the data sufficiently to identify the design parameters that provide the closest possible match to SCADA measurements
Solution Approach 1:
The patent replaces manual data analysis with automated computational algorithms that systematically evaluate design parameters against SCADA measurements, achieving superior measurement precision through exhaustive computational search rather than limited human analysis capability
Solution Approach 2:
The patent segments the complex data resolution process into systematic computational steps including retrieving model parameters, comparing with SCADA data, calculating differences, and automatically adjusting parameters, making the complex process manageable and repeatable
3Ease of operation
If traditional manual methods are used for ESP model recalibration, then the process is simple to understand, but the process is tedious and error-prone
Solution Approach 1:
The patent replaces manual operation with automated computer execution, maintaining conceptual simplicity while eliminating human error through algorithmic precision and systematic parameter adjustment that can be repeatedly executed without fatigue or mistake
Data Source
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AI summary
Apparatus, computer readable medium, program code, and methods for performing a parameter recalibration on parameters for an electrical submersible pump application model, are provided. An example of a method can include generating a data set containing a plurality of winning data sets or rows containing ESP application model input parameters and associated theoretical output parameters for an ESP application model substantially matching a corresponding set of measured ESP output parameters, through application of a self-organizing map analysis on a substantial number of training data sets. An averaging analysis is performed on the plurality of winning data sets or rows to obtain a set of ESP application model input parameters that can be used to recalibrate the ESP application model.