Decision Tree Generation for Seismic Simulation Workflows
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Solution Overview
Problem
Seismic to simulation workflows in petro-technical applications are complex, making it difficult to visualize decision paths and understand the implications of decisions made during these processes, especially when dealing with uncertainty and probabilities.
Innovation Solution
The development of a Decision Tree Generation software that automatically generates decision trees from these workflows, allowing for clearer visualization of decisions, probabilities, and estimated values, enabling the computation of expected values and economic indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If seismic to simulation workflows are executed with multiple realizations, then comprehensive prospect evaluation is achieved, but the complexity and difficulty of visualizing decision paths increases
Solution Approach 1:
The patent segments the complex workflow into discrete decision nodes and branches, where each node represents a specific decision point and each branch represents a possible outcome. This segmentation transforms the complex continuous workflow into a structured hierarchical format that is easier to visualize and interpret, allowing users to navigate through multiple realizations systematically without being overwhelmed by the overall complexity.
Solution Approach 2:
The patent introduces a new dimensional representation by mapping workflow decisions onto a decision tree structure with hierarchical levels. This dimensional transformation organizes the complex decision paths into a multi-level tree where root nodes represent initial decisions, intermediate nodes represent subsequent decisions, and leaf nodes represent final outcomes. This structural reorganization provides a clearer visual dimension for understanding complex prospect evaluation across multiple realizations.
2Reliability
If multiple modeling scenarios are analyzed to evaluate economic value, then decision-making quality improves, but the time required for analysis increases
Solution Approach 1:
The patent implements preliminary action by pre-defining the decision tree structure, nodes, and branches before executing the full workflow analysis. The decision tree framework is established in advance with all possible decision points and outcomes mapped out, allowing subsequent workflow executions to simply populate the tree with actual data and calculate economic values without requiring time-consuming on-the-fly structural generation. This preliminary structuring enables rapid evaluation of multiple scenarios.
Solution Approach 2:
The patent incorporates feedback mechanisms that automatically update the decision tree with results from workflow executions and use these results to refine subsequent analyses. The system captures economic values and decision outcomes from each scenario, feeds this information back into the decision tree structure, and uses it to update probability assessments and economic indicators. This feedback loop enables iterative improvement of decision-making quality while reducing overall analysis time by learning from previous scenarios.
3Adaptability or versatility
If decision trees are manually constructed from workflows, then customization flexibility is achieved, but productivity and efficiency decrease
Solution Approach 1:
The patent implements self-service by enabling the system to automatically generate decision trees from workflow definitions without requiring manual intervention for each tree construction. The workflow system itself serves the dual purpose of executing simulations and constructing the decision tree structure, with the decision tree generator automatically extracting decision points, outcomes, and economic values from the workflow execution results. This self-service approach maintains customization flexibility while dramatically improving productivity by eliminating manual tree construction tasks.
Solution Approach 2:
The patent uses copying by automatically replicating the workflow structure onto the decision tree format. The system copies decision points, outcomes, and data flows from the workflow execution into corresponding decision tree nodes and branches. This automated copying process preserves the customization and flexibility of the original workflow while rapidly generating the decision tree structure, eliminating the need for manual reconstruction and significantly improving generation efficiency.
Data Source
AI summary
A method of generating a decision tree for a seismic to simulation workflow, including: identifying a plurality of elements of the seismic to simulation workflow; receiving a plurality of modeling scenarios for each of the plurality of elements, where each of the plurality of modeling scenarios is associated with a realization of the seismic to simulation workflow; receiving a plurality of probabilities for the plurality of modeling scenarios; and generating a decision tree comprising a plurality of nodes and a plurality of branches in response to said plurality of modeling scenarios, where each level of the decision tree is associated with one of the plurality of elements, where the plurality of nodes are associated with the plurality of modeling scenarios, and where the plurality of branches are based on the plurality of probabilities.