Automated Core Sample Selection Using Monte Carlo Optimization

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Solution Overview

Problem

Current methods for selecting core samples from subsurface formations are prone to error and subjectivity, often resulting in incomplete or skewed data sets that fail to represent the statistical integrity of the formation, leading to inadequate petrophysical parameter measurements and fluid productivity predictions.

Innovation Solution

A computer-implemented method using Monte Carlo iterative calculations and data filtering to determine the optimal number and locations of core points, ensuring statistical integrity and reducing the number of samples required while preserving data quality, by analyzing petrophysical parameters and applying user-generated facies curves and exclusion criteria.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual or visual observation methods are used to select sample intervals, then the selection process is simple and quick, but the data set becomes subject to individual interpretation and may miss important statistical members

Engineering Contradiction:

Improvesample selection processVSAvoidstatistical representativeness

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The patent replaces manual visual observation and subjective judgment with an automated computer-implemented system that uses algorithms to objectively analyze petrophysical data and determine optimal sample intervals, eliminating human interpretation variability while maintaining operational simplicity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables the data itself to determine sample selection through automated analysis of petrophysical parameters, allowing the data set to self-identify statistically significant intervals without external human intervention, thereby improving both reliability and consistency

Inventive Principle:

Principle #25Self-service

2Reliability

If more core samples are taken to ensure statistical completeness, then data representativeness improves, but the number of samples required increases significantly

Engineering Contradiction:

Improvedata representativenessVSAvoidnumber of core samples

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent applies partial action by using automated algorithms to identify and select only the critical sample intervals that provide statistically sufficient representation, rather than requiring exhaustive sampling of all possible intervals, thus achieving reliable data with fewer samples

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system performs preliminary automated analysis of complete petrophysical data sets before physical coring begins, pre-identifying optimal sample locations to ensure statistical completeness while minimizing the total number of samples needed

Inventive Principle:

Principle #10Preliminary action

3Productivity

If subjective interpretation methods are used for sample selection, then the process is faster and requires less computational resources, but the results are prone to error and individual bias

Engineering Contradiction:

Improvesample selection speedVSAvoidsample selection accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent substitutes human subjective interpretation with automated computer algorithms that objectively process petrophysical data, maintaining fast processing speeds while dramatically improving selection accuracy by eliminating human error and bias

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system incorporates feedback mechanisms where the automated analysis continuously refines sample interval selections based on statistical validation of the data set, improving measurement precision through iterative optimization while maintaining efficient processing

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS9921329B2Automated method for selecting positions within formations from which to extract samples thereof

Publication Date: 2018.03.20 APACHE CORP

AI summary

A method for selecting core points in subsurface formations includes selecting a zone from at least one subsurface formation. At least one statistical measure of at least one petrophysical measurement with respect to position along the selected zone is calculated. A predetermined number of core points at randomly selected positions along the selected zone is selected The at least one statistical measure is calculated for the randomly selected positions. Using a Monte Carlo iteration, the positions along the selected zone are randomly reselected and the at least one statistical measure is recalculated for the randomly reselected points until the at least one statistical measure for the randomly selected points is a maximum for a user selected statistical criterion applied to the at least one statistical measure of at least one petrophysical measurement with respect to position along the selected zone.