Subsurface Structure Uncertainty Mapping for Fault and Horizon Interpretation
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Solution Overview
Problem
Existing subsurface resource and risk assessments fail to properly characterize structural uncertainty in structure contour maps due to unaccounted conceptual and interpretative uncertainties, leading to inaccurate decision-making in projects involving subsurface resource management.
Innovation Solution
A method that quantifies and communicates structural interpretation uncertainty by integrating seismic continuity attributes, horizon and fault uncertainties, and conceptual geological models using stochastic simulations and information entropy to generate probabilistic subsurface geometry scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional velocity uncertainty workflow is used, then processing is simple and well-defined, but structural uncertainty is incompletely characterized
Solution Approach 1:
The patent segments structural uncertainty into three distinct components: velocity uncertainty, interpretative uncertainty, and conceptual uncertainty. Each component is quantified separately through dedicated workflows, allowing comprehensive characterization while maintaining manageable complexity through modular processing stages.
Solution Approach 2:
The patent merges multiple uncertainty quantification workflows (velocity-based, interpretative, and conceptual) into a unified comprehensive uncertainty assessment. The individual uncertainty components are integrated to produce a holistic structural uncertainty characterization that captures all sources of uncertainty.
2Reliability
If multiple interpreters create maps from same seismic data, then interpretative diversity is captured, but uncertainty quantification becomes complex
Solution Approach 1:
The patent creates multiple copies of structure contour maps by different interpreters from the same seismic data. These multiple interpretations are then analyzed to quantify interpretative uncertainty, capturing the diversity of valid interpretations without requiring a single complex unified process.
Solution Approach 2:
The patent incorporates feedback loops where multiple interpreter interpretations are compared and analyzed. The discrepancies between different interpreter maps provide feedback that quantifies interpretative uncertainty, allowing the system to learn from and incorporate human expert variability.
3Adaptability or versatility
If poor seismic image quality is present, then multiple valid fault interpretations exist, but structural precision deteriorates
Solution Approach 1:
The patent applies dynamic uncertainty ranges to fault positions rather than fixed precise locations. When seismic image quality is poor, the system dynamically expands the uncertainty envelope to encompass multiple valid fault interpretations, allowing the precision representation to adapt to data quality conditions.
Solution Approach 2:
The patent changes the parameter representation from precise fault coordinates to probabilistic uncertainty distributions. By transforming the representation parameters, the system can accommodate multiple valid interpretations while maintaining rigorous quantitative uncertainty characterization.
Data Source
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AI summary
A method is described for assessing subsurface structure uncertainty based on at least one subsurface horizon. The method calculates seismic continuity attributes to determine a mappability of the subsurface horizon(s); determines horizontal uncertainty for each fault in vertical uncertainty for each horizon; generates probabilistic scenarios for a subsurface geometry for at least one conceptual model; and generates a map of geological model uncertainty based on the probabilistic scenarios. In some embodiments, the probabilistic scenarios are stochastic simulations. In some embodiments, generating a map of geological model uncertainty is based on information entropy. The method may be executed by a computer system.