Synthesized Block Model Generation for Geologic Formations
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Solution Overview
Problem
Modeling large physical formations, such as geologic formations, requires significant computational resources due to the large number of blocks, and existing methods like re-blocking result in data loss by reducing the number of blocks, leading to a loss of resolution.
Innovation Solution
A method that generates a synthesized block model from a reference model by mapping reference blocks to synthesized blocks and assigning fractional attributes based on physical parameters, allowing for a reduced number of blocks while maintaining data integrity through the use of rectangular prism-shaped synthesized blocks defined by six spatial elements stored in separate file streams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If re-blocking is used to reduce the number of blocks in a model, then computing power required to manipulate the model is reduced, but resolution is lost and data loss occurs
Solution Approach 1:
Multiple reference blocks are merged into a single synthesized block, combining their attributes through fractional attribute calculations. This merging process reduces the total number of blocks (improving computing power requirements) while preserving the original data through weighted attribute aggregation, thus resolving the contradiction between model simplification and data preservation.
Solution Approach 2:
The patent transforms discrete block attributes into continuous fractional attributes that represent proportions of original blocks within synthesized blocks. By changing the parameter representation from discrete to continuous fractional values, the system maintains higher resolution information while working with fewer blocks, thereby reducing computing power requirements without losing data.
2Quantity of substance
If the number of blocks in a model is reduced, then storage requirements are decreased, but data accuracy is compromised
Solution Approach 1:
The patent changes the parameter representation by introducing fractional attributes that store proportional information from multiple reference blocks. This parameter transformation allows the model to use fewer blocks while maintaining data accuracy through the fractional representation of original block contributions, thus resolving the contradiction between reducing block quantity and preserving measurement precision.
Solution Approach 2:
Instead of physically storing all original blocks, the patent creates synthesized blocks that copy and aggregate the essential attributes of multiple reference blocks through fractional representations. This copying approach reduces the number of stored blocks while preserving data accuracy by maintaining the proportional relationships of original block attributes.
3Productivity
If re-blocking is performed to decrease the total number of blocks, then processing efficiency is improved, but resolution is lost
Solution Approach 1:
The patent merges multiple reference blocks into synthesized blocks while combining their attributes through fractional calculations. This merging improves processing efficiency by reducing the number of blocks to manipulate, while the fractional attribute system preserves resolution by maintaining the proportional contribution of each original block, thus resolving the contradiction between processing efficiency and model resolution.
Solution Approach 2:
By transforming block attributes into fractional parameters that represent proportions, the patent enables processing of fewer blocks with improved efficiency while maintaining resolution. The fractional parameter system allows the model to retain detailed information about original block contributions even as the total block count decreases, resolving the efficiency-resolution trade-off.
Data Source
AI summary
A system and method for modeling a physical formation is provided. The method comprises a model retrieval module obtaining a reference model of the physical formation with at least one physical parameter, the reference model comprising reference blocks. A re-blocking module generates a synthesized model comprising one or more synthesized blocks. The re-blocking module then maps the reference blocks to the synthesized blocks and generates one or more fractional attributes for one or more of the synthesized blocks based on at least one physical parameter of the one or more corresponding reference blocks.