Seismic Analysis System for Hydrocarbon Trap Detection
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Solution Overview
Problem
Current seismic data interpretation methods for detecting hydrocarbon opportunities are labor-intensive and often miss subtle or hidden indications due to noise and time constraints, leading to late or undiscovered hydrocarbon accumulations.
Innovation Solution
A computer-implemented method that computes multi-scale, structure-oriented seismic attributes related to hydrocarbon system elements (reservoir, seal, trap, source, maturation, and migration) and correlates them with a catalogue of hydrocarbon trap configurations to determine potential hydrocarbon traps and estimate their confidence of existence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard interpretation practices are used to identify potential traps, then interpreters can focus on areas with obvious indications, but labor intensity increases and subtle or hidden indications are missed
Solution Approach 1:
The system performs self-service by automatically detecting and ranking hydrocarbon prospects without requiring continuous human intervention. The automated algorithm processes seismic data, identifies trap configurations, and ranks prospects based on predefined criteria, freeing interpreters from routine analysis while maintaining detection reliability through consistent application of objective criteria.
Solution Approach 2:
The patent replaces the mechanical human interpretation process with an automated computational system. The algorithm substitutes for human interpreters by processing seismic data, identifying geometric patterns, and ranking prospects based on quantitative criteria, thereby eliminating labor intensity while improving both reliability and productivity.
2Loss of time
If interpreters focus on areas with obvious indications, then time constraints are managed, but subtle or hidden indications remain undetected
Solution Approach 1:
The system performs preliminary action by automatically scanning the entire seismic dataset beforehand to identify and rank all potential prospects. This preliminary automated screening ensures that no subtle or hidden indications are missed, as the algorithm systematically evaluates all areas according to the criteria, before human interpreters focus on the top-ranked prospects.
Solution Approach 2:
The system incorporates feedback mechanisms where the automated detection results are reviewed and validated by human interpreters. The ranking and annotation of prospects provide feedback that guides further interpretation, ensuring that both obvious and subtle indications are captured while managing time constraints through prioritization.
3Productivity
If automated detection is implemented, then productivity increases, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex detection task into separate functional modules: data processing, geometric pattern recognition, trap configuration identification, and ranking. Each module handles a specific aspect of the analysis, making the overall system more manageable and easier to implement while maintaining high productivity through automation.
4Loss of information
If comprehensive analysis of all seismic data is performed, then detection completeness improves, but time constraints are exceeded
Solution Approach 1:
The system implements partial action by performing comprehensive automated screening across the entire dataset to ensure detection completeness, then applying selective focus to the top-ranked prospects for detailed human review. This approach ensures that all potential indications are captured through the automated pass while managing time constraints by not requiring exhaustive manual analysis of every area.
Data Source
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AI summary
Method for analyzing seismic data representing a subsurface region for presence of a hydrocarbon system or a particular play. Seismic attributes are computed, the attributes being selected to relate to the classical elements of a hydrocarbon system, namely reservoir, seal, trap, source, maturation, and migration. Preferably, the attributes are computed along structural fabrics (1) of the subsurface region, and are smoothed over at least tens or hundreds of data voxels. The resulting geologic attributes (2) are used to analyze the data for elements of the hydrocarbon system and/or recognition of specific plays, and for ranking and annotating partitioned regions (3) of the data volume based on size, quality, and confidence in the prospectivity prediction (5). A catalogue (8) of hydrocarbon trap configurations may be created and used to identify potential presence of hydrocarbon traps and/or aid in scoring (4) and ranking partitioned regions as hydrocarbon prospects.