4D Seismic Inversion Convergence via Regional Segmentation
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Solution Overview
Problem
Current 4D seismic full wavefield inversion methods face challenges in determining convergence, leading to potential model 'underfitting' or 'overfitting', which affects the accuracy of subsurface property changes and increases computing costs due to reliance on arbitrary convergence criteria.
Innovation Solution
The method analyzes model differences between target reservoir and background regions to generate a convergence criterion, allowing for iterative refinement based on specific transformations and comparisons, such as RMS ratios and cross-correlation coefficients, to determine when to stop iterations and achieve accurate subsurface property models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If arbitrary convergence criteria are used in 4D seismic full wavefield inversion, then the inversion process can be terminated, but the accuracy of subsurface property changes deteriorates due to model underfitting or overfitting
Solution Approach 1:
The patent segments the subsurface region into multiple zones (e.g., target reservoir zones and background zones) and applies different convergence criteria to each zone. This allows the inversion to terminate when sufficient accuracy is achieved in critical regions without requiring excessive iterations in less critical areas, thus resolving the contradiction between computational efficiency and accuracy.
Solution Approach 2:
The patent implements local convergence criteria that are specific to different subsurface zones rather than applying a uniform global criterion. By setting zone-specific thresholds based on local geological characteristics and inversion objectives, the method achieves high accuracy where needed while avoiding overfitting in other regions, balancing accuracy and computational cost.
2Measurement precision
If iterative inversion is continued to improve model accuracy, then the precision of subsurface property models improves, but computing costs increase
Solution Approach 1:
The patent implements a feedback mechanism where convergence criteria are continuously evaluated during iterative inversion based on model differences between zones. When the criteria indicate sufficient convergence in all zones, the inversion automatically terminates, preventing unnecessary continued iterations that would waste computational resources while ensuring adequate precision is achieved.
Solution Approach 2:
The patent applies partial action by terminating the inversion process when sufficient accuracy is achieved in critical zones rather than requiring complete convergence across the entire subsurface volume. This allows the method to achieve the necessary precision for the inversion objective without performing excessive iterations that would consume additional computational energy.
3Ease of operation
If uniform convergence criteria are applied across the entire subsurface model, then the inversion process is simple to implement, but the accuracy deteriorates due to inability to account for regional variations
Solution Approach 1:
The patent divides the subsurface model into multiple zones with distinct convergence criteria tailored to each zone's characteristics. This segmentation approach maintains relative simplicity in implementation while significantly improving accuracy by accounting for regional variations in geological properties and inversion behavior across different subsurface areas.
Data Source
AI summary
Provided is a method for determining convergence in full wavefield inversion (FWI) of 4D seismic (time-lapse seismic: 3D seismic surveys acquired at different times with the first survey termed as the baseline and subsequent surveys termed as monitors). FWI applied to field seismic data includes iteratively solving for subsurface property models and model difference between monitor and baseline. Iteration occurs until the model difference is sufficiently converged. Rather than determining convergence by examining an entire subsurface region of the models and/or the model difference, subparts of the subsurface region models and/or the model difference are examined in order to determine convergence. For example, different regions behave differently, include the target reservoir region (where hydrocarbon is present) and the background region that is outside the target reservoir region. Thus, transforming the subregions of the models and/or the model difference and analyzing the transformations may indicate convergence of the overall model difference.