Seismic Horizon Assignment via Patch Volume Tracking
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Solution Overview
Problem
The time-consuming process of analyzing seismic data to identify subsurface horizons of interest in hydrocarbon exploration, which can take days or weeks, hinders efficient hydrocarbon discovery and exploration.
Innovation Solution
A method and system that applies a horizon tracking algorithm to seismic data volumes to identify and differentiate potential horizons, storing identified regions as 'patches' in a patch volume for subsequent analysis, allowing for faster correlation and assignment of horizons of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a geologist manually analyzes seismic data to identify subsurface horizons, then measurement precision and reliability are improved, but loss of time increases significantly
Solution Approach 1:
The patent introduces an automated horizon tracking algorithm as an intermediary tool between the geologist and the seismic data. The algorithm pre-identifies potential horizon patches and presents them to the geologist for verification, reducing the geologist's manual analysis time while maintaining accuracy through human oversight of automated results.
Solution Approach 2:
The system performs preliminary automated analysis to identify and store potential horizon patches before the geologist begins detailed examination. This preliminary action filters and organizes data in advance, allowing the geologist to focus only on verifying and refining the pre-identified patches rather than analyzing raw seismic data from scratch.
2Measurement precision
If multiple seismic surveys and post-processing variations are conducted, then measurement precision is improved, but loss of time increases enormously
Solution Approach 1:
The patent creates a simplified copy or representation of the complex seismic data by extracting and storing key horizon features as discrete patches. This copying approach allows rapid reuse and comparison of identified horizons across different survey variations without reprocessing the entire datasets, significantly reducing analysis time while preserving essential information.
3Productivity
If automated horizon tracking algorithms are used, then productivity is improved, but measurement precision may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where the automated algorithm's patch identification results are presented to the geologist for verification and correction. The geologist's expert judgment serves as feedback to validate or adjust the automated results, ensuring measurement precision is maintained while still benefiting from the productivity gains of automation.
Data Source
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AI summary
Subsurface horizon assignment. At least some of the illustrative embodiments are methods including: obtaining, by a computer system, a seismic data volume; identifying, by the computer system, a plurality of patches in the seismic data volume, and the identifying thereby creating a patch volume; displaying, on a display device, at least a portion of the seismic data volume and the plurality of patches of the patch volume; and assigning a patch of the plurality of patches to a subsurface horizon of the seismic data volume.