Well-Log Phase Image Analysis for Stratigraphic Correlation

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Solution Overview

Problem

Current automated well-log correlation techniques are limited in their ability to quantify complex geological information, relying on subjective expert knowledge and failing to integrate multiple data sources effectively, leading to inconsistent and labor-intensive manual processes.

Innovation Solution

The method involves obtaining a scale-depth or scale-time phase image of a continuous wavelet transform of well-log signals, extracting hierarchical multiscale intervals using techniques like watershed analysis or significance-of-cone methods, and characterizing curve shapes using beta distribution parameters to provide an objective and automated correlation of stratigraphic boundaries and rock properties.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated well-log correlation techniques based on single-curve-shape similarity and simple expert rules are used, then the processing speed is improved, but the interpretation accuracy and ability to handle complex geological variations deteriorate

Engineering Contradiction:

Improveprocessing speedVSAvoidinterpretation accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent transforms qualitative geological interpretations into quantitative parameters by using curve shape parameters (skewness, kurtosis, asymmetry coefficients) to objectively characterize well-log patterns. This allows automated correlation to maintain both speed and accuracy by replacing subjective expert judgment with measurable mathematical parameters that capture complex geological variations.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent extends traditional single-curve correlation by integrating multiple well-log curves and incorporating vertical stacking patterns as additional dimensions. This multi-dimensional approach uses composite curve shapes and stacking geometry to distinguish complex geological variations that single-curve methods cannot resolve, thereby improving interpretation accuracy while maintaining automation.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Measurement precision

If manual well-log correlation by stratigraphers is performed, then the interpretation accuracy is maintained through expert knowledge, but the processing time and labor intensity increase

Engineering Contradiction:

Improveinterpretation accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent creates a computational model that replicates expert stratigrapher interpretation by encoding geological knowledge into automated algorithms. The system copies the decision-making process of human experts by using curve shape parameter analysis and stacking pattern recognition to automatically identify and correlate stratigraphic boundaries, achieving expert-level accuracy without manual intervention.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent replaces the mechanical process of manual well-log correlation with an automated computational system. By substituting human expert analysis with computer-based curve shape characterization and pattern recognition algorithms, the system eliminates labor-intensive manual processing while preserving interpretation quality through objective, repeatable mathematical methods.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If subjective expert knowledge is used in well-log correlation, then the ability to handle complex geological concepts is improved, but the consistency and objectivity of interpretation deteriorate

Engineering Contradiction:

Improveability to handle complex geological conceptsVSAvoidinterpretation consistency

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent converts subjective geological concepts into objective mathematical parameters by quantizing curve shapes using skewness, kurtosis, and asymmetry coefficients. This parameterization allows the system to consistently handle complex geological variations without subjective bias, as the same mathematical operations are applied uniformly across all well-log data regardless of interpreter identity.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10578758B2Sequence pattern characterization

Publication Date: 2020.03.03 EXXONMOBIL UPSTREAM RESEARCH COMPANY(US)

AI summary

A method, including: obtaining a scale-depth or scale-time phase image of a continuous wavelet transform of an input signal, the scale-depth or scale-time phase image including oval-shaped circular patterns observed on the mirrored phase image; and extracting, with a computer, hierarchical multiscale intervals from the scale-depth or scale-time phase image, wherein the hierarchical multiscale intervals correspond to the oval-shaped circular patterns observed on the mirrored scale-depth or scale-time phase image of the continuous wavelet transform of the input signal. Another method includes: characterizing, with a computer, curve shapes of intervals of a signal using beta distribution; and visualizing and analyzing, with the computer, shape parameters of the curve shapes on a shape-parameter crossplot.