3D Porous Media Modeling with Multi-Point Statistics

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Solution Overview

Problem

Existing methods for constructing 3D digital models of porous media face challenges in accurately visualizing and segmenting pores, especially when a fraction of the pores are smaller than the resolution of the CT acquisition system, leading to difficulties in porosity and permeability calculations.

Innovation Solution

A method that combines low-resolution image data with high-resolution data using multi-point statistical methods, such as discrete or continuous variable geostatistics, to distribute characterizations of pore aspects from a smaller sample into the low-resolution data, generating an enhanced model of porous media, utilizing techniques like laser scanning fluorescence microscopy and CT scans.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If high resolution measurement is used to characterize small pores, then measurement precision is improved, but the sample size is limited and cannot represent the entire formation

Engineering Contradiction:

Improvepore characterization accuracyVSAvoidsample volume

Core Design Contradiction:

Measurement precisionVSVolume of stationary object

Solution Approach 1:

The formation is divided into multiple zones based on lithology and pore characteristics. High-resolution measurements are performed on representative samples from each zone, and the results are distributed to corresponding zones in the low-resolution model, creating a segmented approach to resolution enhancement.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different resolution levels are applied to different regions of the formation model. High-resolution pore characterizations are applied locally to zones where they were measured, while maintaining appropriate resolution levels in other zones, creating a spatially varying quality model.

Inventive Principle:

Principle #3Local quality

2Volume of stationary object

If low resolution CT scans are used to cover large sample volumes, then the sample volume is increased, but measurement precision deteriorates and small pores cannot be resolved

Engineering Contradiction:

Improvesample volumeVSAvoidpore segmentation accuracy

Core Design Contradiction:

Volume of stationary objectVSMeasurement precision

Solution Approach 1:

A low-resolution CT scan serves as an intermediary framework that provides the overall geometric structure and zone distribution. High-resolution measurements from small samples act as mediators that transfer detailed pore characterization information to the appropriate zones in the low-resolution model, bridging the resolution gap.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The high-resolution pore structure data from small samples is nested within the low-resolution CT scan framework. The detailed characterizations are distributed into and integrated with the larger-scale geometric model, creating a multi-scale nested structure where fine details are embedded within the coarse framework.

Inventive Principle:

Principle #7Nested doll (Nesting)

3Measurement precision

If multi-point statistical methods are used to distribute high resolution data into low resolution data, then porosity and permeability calculation accuracy is improved, but device complexity increases

Engineering Contradiction:

Improvepetrophysical calculation accuracyVSAvoidprocessing system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The method transforms the problem from direct image processing to statistical parameter distribution. Instead of attempting to enhance the low-resolution images directly, the system changes parameters by distributing statistical moments (mean, variance, skewness) of pore characteristics from high-resolution samples to the low-resolution model zones, simplifying the enhancement process.

Inventive Principle:

Principle #35Parameter changes

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach effectively addresses the segmentation problem by creating a composite 3D model that captures both large and small pores, improving the accuracy of porosity and permeability calculations, and is applicable to hydrocarbon-bearing subterranean rock formations.

Implementation Method 1

laser scanning fluorescence microscopy

Methodology Applied

Scientific EffectFluorescence microscopy: Fluorescence

Implementation Method 2

transmitted laser scanning confocal microscopy

Methodology Applied

Scientific EffectConfocal microscopy:

Implementation Method 3

CT scans are 2-dimensional (2D) cross sections generated by an X-ray source that either rotates around the sample

Methodology Applied

Scientific EffectX-ray attenuation: X-Ray

Data Source

PatentUS8908925B2Methods to build 3D digital models of porous media using a combination of high- and low-resolution data and multi-point statistics

Publication Date: 2014.12.09 SCHLUMBERGER TECH CORP

AI summary

This subject disclosure describes methods to build and/or enhance 3D digital models of porous media by combining high- and low-resolution data to capture large and small pores in single models. High-resolution data includes laser scanning fluorescence microscopy (LSFM), nano computed tomography (CT) scans, and focused ion beam-scanning electron microscopy (FIB-SEM). Low-resolution data includes conventional CT scans, micro computed tomography scans, and synchrotron computed tomography scans.