Geophysical Vector Volume Refinement for Dip Estimate Accuracy
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Solution Overview
Problem
Current methods for modeling subsurface volumes in the oil and gas industry, such as seismic data interpretation, face challenges in enhancing dip estimates and volume flattening, particularly in areas with poor data quality, which affects the accuracy of hydrocarbon resource localization.
Innovation Solution
A method involving the computation of initial vector estimates, error estimation, and iterative refinement to generate a stratigraphic model of the subsurface, utilizing a vector volume to enhance dip estimates and improve volume flattening, allowing for the localization of hydrocarbons and subsequent drilling operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional dip estimation methods are used, then the process is simple and fast, but the accuracy of dip estimates deteriorates in areas with poor data quality
Solution Approach 1:
The patent implements an iterative feedback mechanism where dip estimates are continuously refined by comparing predicted data with actual measured data. The process computes residuals between observed and predicted measurements, then updates dip estimates based on these errors until convergence criteria are met, thereby improving accuracy in poor data quality areas through systematic error correction
Solution Approach 2:
The patent performs preliminary flattening of seismic data based on initial dip estimates before conducting the final dip estimation. This preliminary action removes the dominant effect of dip on the data, allowing subsequent dip estimation to focus on residual errors and achieve higher precision without being confounded by large-scale structural variations
2Measurement precision
If iterative refinement is performed to improve dip estimates, then accuracy improves, but computation time increases
Solution Approach 1:
The patent implements a convergence-based stopping criterion that performs iterative refinement only until a predetermined accuracy threshold is met or maximum iterations are reached. This partial action approach avoids unnecessary computations after the desired precision is achieved, balancing accuracy improvement with computation time by stopping the iterative process at the point of diminishing returns
3Area of stationary object
If poor quality data areas are included in the model, then the complete subsurface volume is covered, but the overall model quality deteriorates
Solution Approach 1:
The patent applies different processing strategies to different regions of the subsurface volume based on local data quality characteristics. In areas with poor data quality, the iterative refinement process places greater emphasis on minimizing residuals in those specific locations, while maintaining appropriate weighting to prevent these regions from dominating the overall solution and degrading the quality of regions with better data
Data Source
AI summary
Method and system are described for modeling one or more geophysical properties of a subsurface volume. The method includes computing vector volumes to enhance subsurface modeling and update these vector volumes. The vectors are estimated (106) from the data, for example dip or azimuth, and then the vector volume may be updated by an optimization process (808). Flattening the original data (802) may assist the vector estimation, and associating data traces and samples of traces with labels (108) may assist the flattening. The vector volume may then be used to extract horizons (110) and generate a stratigraphic model (112) to enhance the process of producing hydrocarbons (114).