Subsurface Modeling Using Layer Space Stratigraphy
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Solution Overview
Problem
Existing subsurface modeling technologies face challenges in accurately modeling small-scale continuous layers, such as thin shale and mud deposits, which are crucial for reservoir heterogeneity, as they are often volumetrically insignificant but significantly impact flow pathways and production efficiency, while existing methods struggle to honor conditioning characteristics and maintain realism on stratigraphic grids.
Innovation Solution
The approach involves performing modeling within the layer space using computational stratigraphy models, converting data from physical space to layer space, and then back to physical space to generate subsurface representations that capture small-scale continuous layers and maintain physically plausible continuities, while honoring conditioning characteristics by populating stratigraphic grids with appropriate properties and maintaining continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If Cartesian grids are used for subsurface simulations, then the modeling process is simplified and computationally efficient, but small-scale continuous layers cannot be accurately modeled
Solution Approach 1:
The patent transforms the subsurface modeling from physical space to layer space, where the vertical dimension is reparameterized based on stratigraphic layers rather than Cartesian coordinates. This dimensional transformation enables accurate representation of small-scale continuous layers while maintaining computational efficiency through the layered structure.
Solution Approach 2:
The patent changes the parameterization of the vertical dimension from fixed Cartesian grid intervals to stratigraphic layer-based parameters. By using layer thickness and layer properties as fundamental parameters, the model can accurately capture small-scale variations in continuous layers while simplifying the overall modeling process through the hierarchical layer structure.
2Reliability
If process-based approaches are used to honor conditioning subsurface characteristics, then geological realism is improved, but the complexity of the modeling process increases
Solution Approach 1:
The patent segments the subsurface into discrete stratigraphic layers, each with its own properties and characteristics. This segmentation allows process-based modeling to be applied layer-by-layer, honoring conditioning characteristics within each layer while reducing overall model complexity through the modular hierarchical structure. Each layer can be independently modeled and validated.
Solution Approach 2:
The patent performs preliminary classification and characterization of subsurface units into stratigraphic layers before detailed process-based modeling. By pre-defining the layer structure and properties based on available data, the subsequent modeling process becomes more straightforward and less complex, as the framework for honoring conditioning characteristics is already established.
3Manufacturing precision
If stratigraphic grids are directly simulated with conditioning characteristics, then small-scale continuous layers are captured, but maintaining physical continuity becomes difficult
Solution Approach 1:
The patent introduces layer space as an intermediary coordinate system between the discrete stratigraphic grid and the continuous physical space. In layer space, small-scale continuous layers can be accurately represented as distinct units, while the transformation back to physical space ensures physical continuity is maintained. The layer space acts as a mediator that reconciles the discrete nature of stratigraphic classification with the continuous nature of physical subsurface.
Data Source
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AI summary
Data in physical space may be converted to layer space before performing modeling to generate one or more subsurface representations. Computational stratigraphy model representations that define subsurface configurations as a function of depth in the physical space may be converted to the layer space so that the subsurface configurations are defined as a function of layers. Conditioning information that defines conditioning characteristics as the function of depth in the physical space may be converted to the layer space so that the conditioning characteristics are defined as the function of layers. Modeling may be performed in the layer space to generate subsurface representations within layer space, and the subsurface representations may be converted into the physical space.