Multi-Horizon Seismic Tracking Using Quality-Based Switching
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Solution Overview
Problem
Existing seismic data interpretation methods struggle to accurately track and model multiple horizons in a subsurface region, leading to challenges in constructing precise models for hydrocarbon reservoirs, which affects the accuracy of drilling operations and resource extraction.
Innovation Solution
A method and system for receiving and processing three-dimensional seismic data, determining an order of points based on data quality metrics, and serially tracking multiple horizons using switching criteria to output a three-dimensional model of the subsurface region, utilizing computational frameworks like DRILLPLAN, PETREL, TECHLOG, PETROMOD, ECLIPSE, and INTERSECT for enhanced interpretation and modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional seismic data interpretation methods are used to track multiple horizons, then the process is simpler, but the accuracy of subsurface modeling deteriorates
Solution Approach 1:
The patent segments the horizon tracking process into discrete steps: identifying seed points on horizons, determining tracking order based on data quality metrics, and serially tracking each horizon in sequence. This segmentation allows complex multi-horizon tracking to be broken down into manageable, accurate individual operations while maintaining overall system manageability
Solution Approach 2:
The patent performs preliminary actions by first determining the optimal tracking order of multiple horizons based on data quality metric values before actually executing the tracking. Seed points are identified and ranked in advance, allowing the system to prioritize tracking high-quality horizons first, thereby improving overall modeling accuracy while maintaining systematic control over the complex process
2Productivity
If multiple horizons are tracked simultaneously, then the process is faster, but the accuracy of individual horizon tracking deteriorates
Solution Approach 1:
The patent implements periodic action by tracking horizons in a serial, sequential manner rather than simultaneously. Each horizon is tracked in discrete periods or steps according to a predetermined order based on data quality metrics. This periodic approach ensures that each horizon receives dedicated processing attention, maintaining high accuracy while the overall systematic process maintains good efficiency
Solution Approach 2:
The system performs preliminary ordering of horizons based on data quality metrics before tracking begins. This preliminary classification allows the system to prepare an optimal tracking sequence in advance, ensuring that high-quality horizons are tracked first with full computational resources dedicated to each, thereby maintaining both efficiency and accuracy
3Reliability
If data quality metrics are not considered in tracking order, then the process is simpler, but the reliability of the three-dimensional model deteriorates
Solution Approach 1:
The patent changes the parameter used to determine tracking order from a simple sequential approach to one based on data quality metric values. By using quality metrics as the ordering parameter, the system dynamically adjusts the tracking sequence to prioritize reliable data, thereby improving model reliability while the automated metric-based system keeps the added complexity manageable
Solution Approach 2:
The system performs self-service by automatically evaluating data quality metrics and determining the optimal tracking order without requiring manual intervention. The framework autonomously ranks horizons based on their quality metrics and executes tracking in the determined sequence, improving reliability through objective quality-based ordering while avoiding the complexity of manual quality assessment processes
Data Source
AI summary
A method can include receiving seismic data from a three-dimensional seismic survey of a subsurface region that includes multiple horizons; determining an order of a set of points according to data quality metric values of the seismic data, where each point in the set of points is associated with one of the multiple horizons; tracking the multiple horizons serially, where one or more switching criteria cause the tracking to switch from one of the multiple horizons to another one of the multiple horizons according to the order of the set of points; and, based on the tracking, outputting a three-dimensional model of the multiple horizons in the subsurface region.