Digital Rock Physics Upscaling Heterogeneity Trends
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Solution Overview
Problem
Existing methods for determining petrophysical trends in rocks are hindered by scatter and deviation in data, experimental errors, and the inability to account for heterogeneities, making it difficult to discern meaningful trends, especially at large scales due to the high degree of structural heterogeneity in reservoir rocks.
Innovation Solution
A statistical analysis method applied to digital rock representations that identifies heterogeneous regions and extracts multiple trends, enabling a recursive upscaling method to transform small-scale trend information into larger scales, allowing for accurate reservoir evaluation and production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional experimental approaches are used to establish petrophysical trends, then a large amount of data can be collected, but the data has large scatter and deviation making it difficult to discern meaningful trends
Solution Approach 1:
The patent segments the rock sample into multiple subsamples and identifies heterogeneous regions within each subsample. By analyzing trends within each homogeneous region separately rather than treating the entire sample as uniform, the method reduces scatter and deviation in the data, making meaningful trends discernible despite the large amount of data collected.
Solution Approach 2:
The patent applies local quality by recognizing that different regions of the rock sample have different properties (heterogeneity). It identifies and separates heterogeneous regions with distinct petrophysical characteristics, allowing trend analysis to be performed locally within homogeneous regions rather than globally across the entire sample, thereby improving trend clarity.
2Reliability
If numerous samples are used to establish statistically meaningful trends, then trend reliability improves, but experimental time and resources increase significantly
Solution Approach 1:
The patent segments a single rock sample into multiple subsamples and further divides each subsample into heterogeneous regions. This segmentation allows the method to extract multiple trends from one sample, achieving statistical significance without needing to test numerous separate samples, thereby reducing experimental time while maintaining reliability.
Solution Approach 2:
The patent creates digital representations (copies) of the rock sample using advanced imaging technologies. These digital copies allow for repeated analysis and trend extraction without physical experimentation, enabling statistical analysis to be performed on multiple virtual subsamples from a single physical sample, thus reducing both time and resource requirements.
3Reliability
If digital rock physics is used to construct digital representations, then experimental errors are eliminated, but existing analysis techniques fail to account for heterogeneities
Solution Approach 1:
The patent enhances the analysis technique by implementing local quality assessment through heterogeneous region identification. The system analyzes each subsample to identify regions with distinct petrophysical properties, allowing the digital representation to capture and account for heterogeneities at different locations within the sample, thereby maintaining data accuracy while improving analytical capability.
Solution Approach 2:
The patent applies segmentation by dividing the digital rock representation into multiple subsamples and further segmenting each subsample into heterogeneous regions. This multi-level segmentation enables the analysis technique to account for heterogeneities by treating different regions separately, transforming the digital representation into a heterogeneous model that reflects the actual rock structure.
4Ease of manufacture
If small scale samples are used for analysis, then imaging and measurement are feasible, but the results cannot be directly applied to large scale reservoirs
Solution Approach 1:
The patent uses segmentation to divide the large-scale reservoir into multiple smaller subsamples that can be imaged and analyzed individually. By identifying heterogeneous regions within each subsample and establishing trends locally, the method creates a hierarchical structure where small-scale measurements can be systematically combined to represent large-scale reservoir properties, thereby bridging the scale gap.
Solution Approach 2:
The patent implements a nested structure where heterogeneous regions are nested within subsamples, which are nested within the larger rock sample, which represents the reservoir. This nested hierarchy allows trend information to be extracted at multiple scales and integrated systematically, enabling small-scale imaging results to be scaled up to reservoir-level predictions through the nested framework.
Data Source
AI summary
An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes selecting a subsample within the digital images. The method also includes deriving a trend or petrophysical property for the subsample. The method also includes applying the trend or petrophysical property to a larger-scale portion of the digital images.