Non-linear Petrofacies Identification via Cross-Plot Partitioning

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Solution Overview

Problem

Current methods for identifying petrofacies in reservoir characterization are limited by their reliance on linear relationships and user-intensive processes, impeding the use of quantitative and automated categorization methodologies, which are essential for accurate hydrocarbon production prediction and spatial characterization of multiphase flow behavior.

Innovation Solution

The method involves partitioning cross-plots using data frequency and sensitivity analysis to define non-linear petrofacies boundaries, allowing for automated and systematic identification of petrofacies by appearance and composition, enabling batch processing of multiple projects simultaneously.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If linear relationship methods are used for cross-plot analysis, then the analysis process is simple, but the accuracy of petrofacies identification is limited

Engineering Contradiction:

Improvepetrofacies identification accuracyVSAvoidanalysis method complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies non-linear boundary curves instead of straight lines to define petrofacies regions in cross-plots. This allows the classification boundaries to follow curved paths that better represent the actual geological relationships between petrophysical properties, thereby improving identification accuracy while maintaining automated processing capability

Inventive Principle:

Principle #14Spheroidality (Curvature)

Solution Approach 2:

The patent transforms the analysis from linear parameter relationships to non-linear parameter relationships by implementing automated algorithms that can detect and apply curved boundaries. This parameter transformation enables the system to capture complex geological patterns without requiring manual intervention, resolving the contradiction between accuracy and complexity

Inventive Principle:

Principle #35Parameter changes

2Productivity

If user-intensive selection processes are used for defining petrofacies, then flexibility in analysis is maintained, but automation and efficiency are reduced

Engineering Contradiction:

Improvebatch processing capabilityVSAvoiduser involvement requirement

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The patent implements self-service automation where the system automatically performs petrofacies identification without requiring user intervention. The automated algorithms independently analyze cross-plot data, define non-linear boundaries, and generate results, enabling batch processing of multiple projects while eliminating the need for manual user involvement in each analysis case

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of user-intensive selection with automated computational algorithms. The system uses computer-based methods to automatically detect patterns, define boundaries, and classify petrofacies, substituting human manual operations with automated mechanical computing processes that enable high-productivity batch processing

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10664635B2Determining non-linear petrofacies using cross-plot partitioning

Publication Date: 2020.05.26 LANDMARK GRAPHICS CORP

AI summary

Systems and methods for determining non-linear petrofacies using cross-plot partitioning to define petrofacies boundaries that distinguish the petrofacies by appearance and/or composition using systematic and automated data analysis techniques.