Drilling Motor Model for Real-Time Optimization

Solution Overview

Problem

Current drilling technologies face challenges in optimizing drilling motor performance and selecting suitable motors for drilling operations due to the complexity of downhole conditions, which can lead to inefficiencies and motor failures.

Innovation Solution

A method involving machine learning to train a drilling motor model based on simulation results, allowing for the instantiation of a motor engine component with an interface in a computational environment, enabling real-time return of drilling motor information and optimizing motor selection for improved performance and reliability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional simulation methods are used to optimize drilling motor performance, then accurate results can be obtained, but the computational time and resources required are excessive

Engineering Contradiction:

Improvemotor optimization accuracyVSAvoidcomputational time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent creates a simplified copy or proxy model of the complex drilling motor simulation system. This proxy model pre-processes and stores simulation results in a structured format that can be quickly queried and applied during actual drilling operations, eliminating the need to run full simulations in real-time while maintaining optimization accuracy.

Inventive Principle:

Principle #26Copying

2Reliability

If complex simulation models are used for drilling motor analysis, then comprehensive performance data can be obtained, but the system complexity and computational resources increase

Engineering Contradiction:

Improvemotor selection accuracyVSAvoidcomputational system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent performs comprehensive simulation analysis and motor performance characterization in advance, before actual drilling operations begin. Simulation results are pre-processed, stored, and organized into easily accessible formats with pre-defined performance metrics and selection criteria, allowing rapid motor selection during operations without requiring complex real-time computations.

Inventive Principle:

Principle #10Preliminary action

3Productivity

If real-time motor information is required for drilling operations, then operational efficiency improves, but computational speed must be increased

Engineering Contradiction:

Improvedrilling operational efficiencyVSAvoidcomputational speed

Core Design Contradiction:

ProductivityVSSpeed

Solution Approach 1:

The patent creates a simplified copy or proxy model of the complex drilling motor simulation system. This proxy model pre-processes and stores simulation results in a structured format that can be quickly queried and applied during actual drilling operations, eliminating the need to run full simulations in real-time while maintaining optimization accuracy.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS11499409B2Dynamic system for field motor operations

Publication Date: 2022.11.15 SCHLUMBERGER TECH CORP

AI summary

A method can include providing a trained drilling motor model trained via machine learning based at least in part on drilling motor simulation results; instantiating a motor engine component with an interface in a computational environment; and, responsive to receipt of a call via the interface, returning drilling motor information based at least in part on the trained drilling motor model.