Palynological Image Regression for Automated Thermal Maturity Estimation

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Solution Overview

Problem

Existing methods for estimating thermal maturity of source rocks in petroleum systems are costly and require expert analysis, limiting the efficiency and scalability of hydrocarbon exploration.

Innovation Solution

An automated workflow using image processing and machine learning techniques to analyze palynological sample images, constructing a regression model based on RGB pixel values and polynomial functions to estimate thermal maturity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated image processing and machine learning are used to estimate thermal maturity, then productivity and cost-effectiveness are improved, but measurement precision may be compromised compared to expert manual analysis

Engineering Contradiction:

Improveestimation efficiencyVSAvoidthermal maturity estimation accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent creates a digital copy of the palynological sample images and processes them through automated image analysis. The system captures images of palynomorphs and uses computational algorithms to extract features and estimate thermal maturity, replacing the need for physical manual examination while maintaining measurement accuracy through sophisticated image processing techniques.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent replaces the mechanical/manual process of expert visualization and analysis with an automated computer-based system. The system uses image processing algorithms, feature extraction, and machine learning models to perform thermal maturity estimation without requiring human experts to manually examine samples under microscopes, thereby improving productivity while maintaining precision through consistent automated measurement protocols.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If expert manual analysis is used to identify vitrinite fragments and estimate reflectance, then measurement precision is improved, but productivity and cost-effectiveness deteriorate

Engineering Contradiction:

Improvevitrinite reflectance estimation accuracyVSAvoidanalysis throughput

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent enables the system to perform thermal maturity estimation autonomously without requiring expert intervention. The automated system captures images, processes them through algorithms, extracts relevant features, and generates thermal maturity estimates independently, eliminating the need for experts to manually examine each sample while maintaining consistent measurement standards.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent transforms the measurement approach by changing from direct manual visualization and estimation to automated image-based parameter extraction. The system converts visual information from palynological images into quantitative parameters through digital image processing and statistical analysis, enabling high-throughput analysis while maintaining measurement precision through standardized computational methods.

Inventive Principle:

Principle #35Parameter changes

3Ease of manufacture

If traditional palynological methods (PDI, SCI, TAI, AAI) are used, then cost is reduced compared to vitrinite reflectance, but measurement precision and reliability deteriorate

Engineering Contradiction:

Improvecost-effectivenessVSAvoidthermal maturity estimation accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent replaces traditional manual palynological assessment methods with automated image processing and machine learning. The system uses computational algorithms to objectively analyze palynological images and estimate thermal maturity, eliminating subjectivity in visual assessments while maintaining cost-effectiveness by using the same palynological samples but processing them through automated systems rather than manual expert analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent incorporates feedback mechanisms where the automated system's estimates can be validated against known thermal maturity data, and the model can be iteratively improved. The system provides quantitative outputs that can be systematically evaluated and refined, creating a feedback loop that enhances measurement precision over time while maintaining the cost advantages of using palynological samples.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12400425B2Automated thermal maturation estimation from palynological sample images

Publication Date: 2025.08.26 SAUDI ARABIAN OIL CO

AI summary

A method and a system for estimating a thermal maturity of a rock sample of a subterranean region of interest are disclosed. The method includes preparing a plurality of rock samples of the subterranean region of interest and obtaining an image of an organic matter sample from the plurality of the rock. Further, the histograms are obtained based on RGB pixel values extracted from the image of the organic matter sample and a functional relationship describing the histograms is determined. Additionally, the method includes constructing a regression model using weight values of the functional relationship as input values and estimating the thermal maturity of the rock sample of the subterranean region of interest based on the constructed regression model.