Faulted Seismic Horizon Mapping via Dynamic Time Warping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The interpretation of seismic horizons in subsurface formations is challenging due to the presence of faults, which create discontinuities that are difficult to traverse and require complex computational methods, making manual extraction time-consuming and costly, especially in structurally complex datasets.
Innovation Solution
The implementation of a method that estimates fault throw and incorporates discrete fault planes into a horizon optimization framework, allowing for iterative and interactive refinement of horizon surfaces, enabling efficient extraction of seismic horizons by separating operations into pre-processing, global sparse grid optimization, and local grid optimization, and using dynamic time warping for depth prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual extraction methods are used for seismic horizons in faulted formations, then interpretation accuracy can be maintained, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical interpretation with an automated computational system that uses objective functions, gradient calculations, and iterative optimization algorithms to extract seismic horizons, thereby eliminating the time-consuming manual process while maintaining interpretation accuracy
Solution Approach 2:
The system enables self-service by allowing the computational algorithm to automatically traverse fault discontinuities and optimize horizon surfaces without requiring manual intervention at each step, using pre-defined objective functions and iterative refinement processes
2Measurement precision
If complex computational methods are used to traverse fault discontinuities, then horizon extraction accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the computational process into distinct phases: pre-processing to identify fault discontinuities, main processing to traverse faults using optimized algorithms, and post-processing to refine horizon surfaces, thereby managing computational complexity through structured division of tasks
Solution Approach 2:
The system performs preliminary actions by pre-identifying fault discontinuities and preparing optimization parameters before the main horizon extraction process, which simplifies the subsequent computational tasks and reduces overall processing complexity
3Productivity
If traditional methods are used for horizon extraction in structurally complex datasets, then computational resources can be minimized, but extraction efficiency and scalability decrease
Solution Approach 1:
The patent implements dynamic computational resource allocation by adjusting the level of optimization and processing intensity based on the complexity of the seismic data and fault structures, allowing efficient use of computational resources while maintaining high extraction productivity
Solution Approach 2:
The system changes computational parameters dynamically during processing, adjusting grid resolution, optimization iterations, and algorithm selection based on local data characteristics, which improves extraction efficiency without proportionally increasing computational resource consumption
Data Source
AI summary
Disclosed herein are embodiments of a method, a non-transitory computer readable medium, and an apparatus for faulted seismic horizon mapping. In one example, a method comprises: obtaining seismic data for a seismic volume that corresponds to a subsurface formation; generating a map of at least one horizon in the subsurface formation based on the seismic volume; identifying at least one fault intersecting the at least one horizon; determining a throw of the at least one fault; and updating the map of the at least one horizon to incorporate the at least one fault based on the throw of the at least one fault.