Geophysical Inversion Using Pre-Stack Data and Rock Physics Trends
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Solution Overview
Problem
Current inversion methods in geophysical prospecting for hydrocarbon exploration fail to accurately and efficiently determine subsurface properties due to lack of statistical description of model errors, loss of information through data stacking, and inability to provide error statistics, leading to uncertainties in fluid and reservoir property predictions.
Innovation Solution
A method that determines rock type trends, selects appropriate rock physics and geophysical forward models, accounts for uncertainty in these models, and uses error metrics to minimize misfit between measured and predicted data, thereby estimating subsurface properties and their uncertainties, and assessing commercial potential of reservoirs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data stacking is performed to reduce data volume, then processing efficiency is improved, but information loss occurs leading to reduced accuracy in subsurface property estimation
Solution Approach 1:
The patent applies preliminary action by performing the inversion process on pre-stack seismic data before any stacking operations are conducted. This allows the full information content of the pre-stack gathers to be utilized in the inversion algorithm, and only after the inversion is complete are stacked sections generated for visualization and interpretation purposes. This sequence ensures that no information is lost during stacking while still achieving efficient processing through the use of pre-computed stacked sections for display.
2Measurement precision
If inversion methods are used to directly estimate reservoir properties, then prediction accuracy is improved, but computational complexity increases and error statistics cannot be provided
Solution Approach 1:
The patent segments the inversion process into distinct computational stages: (1) forward modeling of pre-stack seismic data using a rock physics model, (2) optimization of subsurface properties to minimize misfit between observed and modeled data, (3) separate computation of error statistics through perturbation analysis, and (4) generation of uncertainty estimates. This segmentation allows the complex inversion to be managed through modular computation while providing both accurate property estimates and quantitative error statistics.
Solution Approach 2:
The patent introduces a rock physics model as an intermediary between the seismic data and the reservoir properties. This rock physics model provides the physical relationship connecting seismic observables to subsurface rock and fluid properties, enabling the inversion to proceed through a well-defined forward model while maintaining computational tractability and providing a basis for error propagation analysis.
3Measurement precision
If multiple rock type trends are considered in the inversion, then estimation accuracy is improved, but model uncertainty increases
Solution Approach 1:
The patent applies parameter changes by allowing the rock type classification to vary spatially throughout the subsurface model rather than assuming a single rock type. The inversion determines optimal rock type assignments for different spatial locations based on the seismic data, with each location potentially having different rock type parameters. This spatially varying parameter approach improves estimation accuracy while the statistical framework quantifies the uncertainty associated with these variations.
Data Source
AI summary
A hydrocarbon exploration method for determining subsurface properties from geophysical survey data. Rock physics trends are identified and for each trend a rock physics model is determined that relates the subsurface property to geophysical properties (103). The uncertainty in the rock physics trends is also estimated (104). A geophysical forward model is selected (105), and its uncertainty is estimated (106). These quantities are used in an optimization process (107) resulting in an estimate of the subsurface property and its uncertainty.