Seismic Attribute Analysis Using Geobody Ensembles
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Solution Overview
Problem
Conventional seismic data interpretation methods fail to effectively capture and analyze the inherent uncertainty in geophysical data, leading to a single model outcome that does not account for multiple possible interpretations and their associated probabilities, which limits the accuracy of attribute analysis and risk assessment in hydrocarbon exploration.
Innovation Solution
The method generates an ensemble of geobodies based on measured uncertainty, allowing for the creation of an ensemble of attribute values and their associated probability distributions, enabling the visualization of multiple possible geobodies and their statistical analysis to provide a comprehensive understanding of subsurface structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional seismic data interpretation methods are used, then a single model outcome is produced, but the inherent uncertainty in geophysical data is not captured
Solution Approach 1:
The system transitions from a static single-model interpretation to a dynamic ensemble of multiple geobody models. Each model in the ensemble represents a possible interpretation consistent with the seismic data and measured uncertainty, allowing the system to adapt to the inherent ambiguity in geophysical data through probabilistic sampling
Solution Approach 2:
The method changes the parameter representation from deterministic single values to probability distributions. By sampling model space according to measured uncertainty, the system generates ensembles of geobodies with varying parameters (positions, shapes, orientations) that reflect the true uncertainty in the data, enabling statistical analysis of attribute values
2Loss of information
If a single model of geobodies is used, then attribute analysis is simplified, but multiple possible interpretations and their associated probabilities are ignored
Solution Approach 1:
Instead of analyzing a single geobody model, the system creates multiple copies (ensembles) of geobodies by sampling model space. Each copy represents a plausible interpretation, and the collection of copies preserves the variability and uncertainty inherent in the data while enabling robust statistical attribute analysis
Solution Approach 2:
The system performs preliminary sampling of model space to generate ensembles of geobodies before conducting attribute analysis. This preliminary action of creating multiple models with varying parameters ensures that uncertainty is captured upfront, allowing subsequent attribute analysis to efficiently evaluate probability distributions without losing interpretation variability
3Reliability
If conventional interpretation methods are used, then the workflow is straightforward, but the accuracy of risk assessment in hydrocarbon exploration is limited
Solution Approach 1:
The interpretation system becomes dynamic by generating ensembles of geobody models that reflect measured uncertainty. This dynamic approach allows risk assessment to consider multiple possible subsurface configurations and their probabilities, significantly improving reliability compared to static single-model interpretations
Solution Approach 2:
The system incorporates feedback loops where attribute values are calculated for each model in the ensemble, probability distributions are derived, and these results inform more accurate risk assessments. The feedback mechanism ensures that uncertainty information flows through the entire workflow, from interpretation to final decision-making
Data Source
AI summary
The present invention relates to a system mapping geological formations related to seismic studies comprising interrogation means for sampling information from geological features in a mapped area, e.g. through seismic sampling methods, the sampled information being stored in association with a position related to the sampled information providing a mapping of the area, wherein the system also comprises analyzing means for obtaining attribute information related to the sampled information in each position and storing said attribute information associated to said positions so as to provide an ensemble of attribute values related to the mapped area subject to the seismic studies.