AI Image Processing for Energy Infrastructure Status Analysis

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Solution Overview

Problem

Current methods for identifying energy infrastructure features and status are manual, time-consuming, costly, and often result in outdated data, especially in large geographical areas like oilfields, where satellite imagery is expensive and permit data is unreliable.

Innovation Solution

An automated image processing system using AI-based EI feature recognition models processes aerial images to identify and classify energy infrastructure features and determine their status, combining image processing with supplemental information to provide timely and accurate data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual methods are used to identify energy infrastructure features, then reliability of identification can be maintained, but time consumption increases and productivity decreases

Engineering Contradiction:

Improveidentification reliabilityVSAvoididentification speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent replaces manual visual inspection methods with an automated image processing system that uses AI-based recognition models to detect energy infrastructure features. The system processes aerial images through machine learning algorithms that automatically identify and classify features such as water storage tanks, drilling equipment, and infrastructure components, eliminating the need for human analysts to manually review each image while maintaining high identification accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service operation where the image processing system autonomously performs feature identification without requiring manual intervention. The AI recognition models automatically analyze aerial imagery, extract relevant information, and provide status updates on energy infrastructure features, allowing the system to serve itself rather than requiring human operators to perform routine monitoring tasks.

Inventive Principle:

Principle #25Self-service

2Area of stationary object

If satellite imagery is used for large geographical areas, then coverage area increases, but cost increases

Engineering Contradiction:

Improvegeographical coverage areaVSAvoidprocessing cost

Core Design Contradiction:

Area of stationary objectVSEase of manufacture

Solution Approach 1:

The patent utilizes existing aerial imagery that has already been captured and stored, rather than requiring new expensive satellite imagery to be acquired for each analysis. The system processes and analyzes these existing image copies through AI recognition models, reducing the need for costly new data acquisition while still providing comprehensive coverage of large geographical areas through the use of previously captured aerial photographs.

Inventive Principle:

Principle #26Copying

3Loss of information

If permit data is used for infrastructure status information, then data availability increases, but reliability of data decreases

Engineering Contradiction:

Improvedata availabilityVSAvoiddata accuracy

Core Design Contradiction:

Loss of informationVSReliability

Solution Approach 1:

The patent introduces aerial image analysis as an intermediary method that provides direct visual evidence of infrastructure status, serving as a more reliable mediator between available data and actual on-site conditions. By analyzing actual imagery of the infrastructure, the system can verify and update permit information, providing more accurate and current status data than permit records alone could provide.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Productivity

If automated image processing is implemented, then productivity increases, but device complexity increases

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent divides the complex image processing task into separate functional modules: image acquisition, AI-based feature recognition, classification, and status determination. Each module handles a specific aspect of the analysis process, making the overall system more manageable and easier to implement. The segmentation allows for specialized algorithms to be applied to each function, improving overall efficiency while maintaining system complexity at acceptable levels through modular architecture.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250021815A1Image processing of aerial imagery for energy infrastructure site status analysis

Publication Date: 2025.01.16 SOURCEWATER INC

AI summary

A computer-implemented method for processing images to determine EI site status is provided. The method includes image processing of an aerial image by two EI feature recognition models. A first EI feature recognition model recognizes a first EI feature and a second EI feature recognition model recognizes a second EI feature. The results of each model are further used to determine a composite indication of EI site status.