Fluid Migration Pathway Determination Using Level Set Algorithms
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Solution Overview
Problem
Current methods for determining subterranean fluid migration pathways in geological volumes are limited in accuracy and efficiency, particularly in identifying potential leakage risks and fluid flow paths, which can lead to reservoir pressure drops and environmental contamination.
Innovation Solution
A method that uses geological attributes, such as seismic and geometric attributes, to define and evolve the fluid boundary over iterations, allowing for the determination of migration pathways through a geological volume, employing a computer-based approach with level set algorithms to model fluid flow and potential leakage paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional seismic surveying methods are used to determine subsurface strata, then depth and orientation information can be obtained, but the accuracy in identifying fluid migration pathways is limited
Solution Approach 1:
The method segments the fluid migration pathway determination into distinct computational stages: defining initial fluid boundaries from seismic data, distributing data points through the geological volume, iteratively evolving the fluid boundary using level set equations, and extracting migration pathways. This segmentation allows each stage to be optimized independently, improving overall accuracy without proportionally increasing complexity.
Solution Approach 2:
The level set function serves as an intermediary mathematical construct that evolves over iterations to represent the fluid boundary. This intermediary allows the transformation of complex seismic attribute data into simplified migration pathway representations, bridging the gap between raw seismic data and interpretable migration paths with higher precision.
2Measurement precision
If comprehensive geological attributes are analyzed to improve migration pathway determination, then identification accuracy improves, but computational time increases
Solution Approach 1:
The method performs preliminary actions by pre-defining the level set function and pre-distributing data points through the geological volume before the iterative evolution process. This preliminary setup organizes the computational workload, allowing the iterative refinement to focus only on boundary evolution, thereby reducing total computational time while maintaining comprehensive attribute analysis.
Solution Approach 2:
The method applies partial action by focusing computational efforts primarily on the regions where the fluid boundary evolves, rather than uniformly processing the entire geological volume at each iteration. This selective refinement maintains high identification accuracy in critical areas while reducing unnecessary computations in stable regions.
3Measurement precision
If iterative evolution of fluid boundary is performed to determine migration pathways, then pathway accuracy improves, but processing efficiency decreases
Solution Approach 1:
The method employs periodic action through iterative evolution, where the fluid boundary is updated at discrete time steps according to the level set equation. This periodic updating allows the system to progressively refine the migration pathway representation, achieving high accuracy through multiple passes rather than a single complex computation, thereby balancing precision with processing efficiency.
4Measurement precision
If level set algorithms are used to model fluid flow, then migration pathway determination accuracy improves, but computational complexity increases
Solution Approach 1:
The method substitutes complex mechanical modeling of fluid flow with the level set mathematical framework. Instead of simulating detailed fluid dynamics, the level set equation evolves the boundary based on gradient information from seismic attributes, replacing computationally intensive mechanical simulations with a more efficient partial differential equation approach that maintains high boundary evolution accuracy.
Data Source
AI summary
A method of determining a migration pathway of a subterranean fluid through a geological volume is provided. The starting object is located within the geological volume. The starting object defines an initial fluid boundary. Data points are distributed through the geological volume. The data points are associated with values of one or more geological attributes. The method includes the steps of: defining an expression which determines a change in position of the fluid boundary at the data points over an iteration based on the values of the one or more attributes; and applying the expression at the data points for successive iterations to evolve the fluid boundary over the successive iterations. The migration pathway of the subterranean fluid through the geological volume can then be determined from the evolution of the fluid boundary.