Edge-Preserving Gaussian Grid Smoothing for Subsurface Geological Maps
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Solution Overview
Problem
Existing methods for generating geological maps of subsurface formations often result in noisy grids due to band-limited seismic data and computational artifacts, which can lead to undesired smoothing of critical geological boundaries like faults, making it challenging to accurately interpret hydrocarbon resources.
Innovation Solution
A technique that uses seismic attributes to generate a weighting grid, allowing for iterative local averaging with a spatially varying weight function to filter noise while preserving geological boundaries, thereby improving the accuracy of subsurface maps by controlling which edges are preserved during the smoothing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard filtering methods are applied to reduce noise in subsurface grids, then noise reduction is improved, but geological boundaries such as faults are smoothed out and lost
Solution Approach 1:
The patent applies different filtering strengths to different regions of the subsurface grid by using a weight map derived from seismic attributes. Areas with high seismic attribute values (indicating potential faults or boundaries) receive lower filtering weights to preserve edges, while areas with low attribute values receive higher weights for more aggressive noise filtering. This local differentiation resolves the contradiction by making the filtering process spatially adaptive rather than uniform.
Solution Approach 2:
The patent performs preliminary identification of geological boundaries using seismic attributes (such as coherence, curvature, or fault detection algorithms) before applying the filtering process. This preliminary action creates a weight map that guides the subsequent filtering operation, ensuring that boundaries are protected from smoothing before the noise reduction process begins. This sequence of operations resolves the contradiction by preparing the filtering strategy in advance based on boundary locations.
2Measurement precision
If aggressive noise filtering is applied to subsurface grids, then noise components are reduced, but the accuracy of geological interpretations decreases due to loss of boundary information
Solution Approach 1:
The patent introduces a weight map as an intermediary element between the noise filtering process and the subsurface grid. This weight map, generated from seismic attributes, acts as a mediator that controls the filtering operation - it allows noise filtering to proceed in regions without boundaries while protecting boundary regions from excessive smoothing. The intermediary weight map thus enables the system to achieve both noise reduction and boundary preservation simultaneously.
Solution Approach 2:
The patent dynamically changes the filtering parameter (filtering strength or kernel size) based on the local seismic attribute values. In regions where seismic attributes indicate the presence of faults or boundaries, the filtering parameters are adjusted to be more conservative. In regions without such features, more aggressive filtering parameters are applied. This parameter adaptation resolves the contradiction by making the filtering process responsive to local geological conditions.
3Manufacturing precision
If manual interpretation of faults is performed to preserve boundaries, then boundary accuracy is improved, but the time required for map generation increases significantly
Solution Approach 1:
The patent enables the filtering system to automatically identify and protect geological boundaries using seismic attributes without requiring manual intervention. The system self-determines which areas contain boundaries through automated seismic attribute analysis and automatically adjusts filtering weights accordingly. This self-service capability resolves the contradiction by replacing time-consuming manual interpretation with automated algorithms that achieve comparable or superior boundary preservation while significantly reducing processing time.
Solution Approach 2:
The patent replaces the mechanical process of manual fault interpretation and boundary tracing with an automated computational system based on seismic attribute analysis. Instead of geologists manually identifying and protecting boundaries, the system uses algorithms to detect boundaries through seismic attributes and automatically applies appropriate filtering weights. This substitution of manual mechanical work with automated computational processes resolves the contradiction by maintaining boundary accuracy while dramatically improving productivity.
Data Source
AI summary
Methods and systems, including computer programs encoded on a computer storage medium can be used to preserve edges while performing Gaussian grid smoothing of noise components in subsurface grids to generate geological maps. A subsurface grid is generated from data indicating properties of subsurface formations. A weighting grid is generated by: i) receiving seismic data representing the subsurface formations; ii) generating seismic attributes associated with discontinuities in the subsurface formations; and iii) assigning a particular weight value to weighting grid points that the seismic attributes associated with discontinuities in the subsurface formations indicate the presence of a discontinuity. The subsurface grid is processed by iteratively computing local averages of grid points in the subsurface grid using a compact Gaussian filter weighted by values in the weighting grid. A geological map of subsurface formations is generated based on the filtered subsurface grid.