Uncertainty Catalog for Oil and Gas Risk Assessment
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Solution Overview
Problem
The oil and gas industry lacks tools capable of recording and analyzing both qualitative and quantitative assessments of uncertainty and risk over time, which hinders effective risk management and reserve knowledge improvement during hydrocarbon development.
Innovation Solution
A method and system for assessing uncertainty, including creating and updating uncertainty catalogs, capturing and establishing dependencies, associating risks and action plans, creating realization trees, and tracking changes over time, using a computer program to manage uncertainties and risks during reservoir development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional uncertainty assessment methods are used, then qualitative and quantitative assessments can be performed separately, but the ability to record and visualize both types of assessments simultaneously is lost
Solution Approach 1:
The patent merges qualitative and quantitative uncertainty assessments into a unified catalog structure. The uncertainty catalog integrates both assessment types with standardized attributes, allowing simultaneous recording and visualization of multiple uncertainty dimensions without requiring separate systems.
Solution Approach 2:
The uncertainty catalog serves multiple functions: it stores qualitative descriptions, quantitative ranges, dependencies between uncertainties, associated risks, and action plans. This multi-functional design consolidates what would otherwise require separate tools into a single universal platform.
2Reliability
If comprehensive uncertainty tracking is implemented, then risk evolution over time can be analyzed, but the complexity of data management increases
Solution Approach 1:
The system establishes uncertainty catalogs, dependencies, and risk associations in advance before formal risk assessment begins. This preliminary structuring of data relationships enables automated tracking and analysis of risk evolution over time without requiring complex manual data management during the assessment process.
Solution Approach 2:
The system provides feedback mechanisms that automatically update uncertainty status and risk levels based on changing conditions. This automated feedback loop maintains data consistency and enables continuous monitoring of risk evolution without increasing manual data management complexity.
3Loss of information
If detailed uncertainty catalogs are created, then comprehensive risk information can be captured, but the time required to establish and maintain the catalog increases
Solution Approach 1:
The uncertainty catalog is segmented into standardized components: uncertainty identifiers, qualitative descriptions, quantitative ranges, dependency relationships, associated risks, and action plans. This segmentation allows the catalog to be built incrementally by populating discrete elements rather than requiring complete simultaneous documentation.
Solution Approach 2:
The system uses parameter-based uncertainty representation with standardized attributes and data types. This parameterization enables automated data validation, consistency checking, and efficient storage, reducing the time required to establish and maintain comprehensive uncertainty catalogs.
Data Source
AI summary
A method is disclosed for assessing uncertainty comprising: creating a catalog for uncertainty areas; capturing quantitative and qualitative uncertainty data; establishing dependencies between uncertainties; associating risks to uncertainties; associating action plans and tasks to risks; creating a realization tree from uncertainty ranges; and tracking changes to uncertainties and realizations over time.