Subsurface Structural Model Construction Using Implicit Functions
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Solution Overview
Problem
Current methods for constructing structural models of the subsurface are inefficient and non-interactive, requiring manual rebuilding and re-computation of entire frameworks for minor changes, making it difficult to explore uncertainty and update models effectively.
Innovation Solution
The method involves representing subsurface features with implicit functions, allowing for easy updating and perturbation of surfaces, such as faults and horizons, and constructing structural models by tessellating these surfaces to form a three-dimensional grid, enabling interactive exploration of scenarios and reducing computational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual rebuilding and re-computation of entire frameworks is performed for minor changes, then model accuracy can be maintained, but time consumption and computational cost increase significantly
Solution Approach 1:
The structural model is divided into discrete surface segments that can be independently modified. Each segment is represented by control points and mathematical functions, allowing localized changes without affecting the entire model. This segmentation enables selective updating of only the affected portions when modifications are needed.
Solution Approach 2:
The model transitions from a static, fixed framework to a dynamic, parameterizable system. Surface segments are defined by control points and mathematical functions that can be easily adjusted and updated. This dynamic representation allows the model to adapt to new data and conditions without requiring complete rebuilding.
2Reliability
If entire frameworks are rebuilt for minor changes, then consistency can be maintained, but productivity decreases due to repeated re-computation
Solution Approach 1:
The model framework is pre-configured with modular surface segments and mathematical functions that are ready for easy modification. This preliminary structuring allows for rapid updates by simply adjusting control points or parameters without requiring complete re-computation, thus maintaining both consistency and productivity.
Solution Approach 2:
The model uses parameterizable surface representations where changes are made by modifying mathematical parameters and control points rather than rebuilding the entire structure. This parameter-based approach maintains model consistency while dramatically improving updating efficiency, as only the affected parameters need to be recalculated.
3Adaptability or versatility
If interactive manipulation of the model is allowed, then adaptability and scenario exploration improve, but computational complexity and artifacts increase
Solution Approach 1:
The model is segmented into independent surface patches with their own control points and mathematical representations. This segmentation allows interactive manipulation of individual segments without propagating complexity throughout the entire model, enabling scenario exploration while controlling computational demands.
Solution Approach 2:
The model uses mathematical function representations that can be copied and applied consistently across different surface segments. This functional copying approach maintains computational efficiency by reusing proven mathematical operations rather than performing unique complex calculations for each modification.
4Shape
If surfaces are extended or extrapolated to touch, then geometric completeness is achieved, but computational cost increases due to artifacts and re-computation
Solution Approach 1:
Surface segments are pre-defined with mathematical functions and control points that inherently ensure geometric completeness. This preliminary mathematical formulation eliminates the need for post-hoc extension or extrapolation operations, achieving geometric completeness without the associated computational cost of artifacts and re-computation.
Data Source
AI summary
Method and systems are provided for building a structural model of the subsurface. The method may comprise obtaining discretized data that includes surfaces, polylines, points, or combinations thereof. The surfaces in the discretized data are segmented by other surfaces to form a number of segments. Each of the segments are fit to an implicit function. The implicit function for each of the segments is thresholded to create a number of implicit surfaces. The implicit surfaces are intersected to create a number of model surfaces. The structural model is then constructed from the model surfaces.