Full Wavefield Inversion for Pore Pressure Prediction
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Solution Overview
Problem
Conventional seismic methods, such as tomography, are inadequate for accurately predicting pore pressure in subsurface sand reservoirs and assessing seal integrity, as they provide smooth velocity profiles that fail to detect embedded sand reservoirs, leading to uncertainties in drilling and hydrocarbon trapping.
Innovation Solution
The method employs Full Wavefield Inversion (FWI) to generate high-resolution velocity and impedance models, integrating them with velocity-based pore pressure estimation to predict pore pressure and characterize seal integrity, using lithology-dependent pressure-velocity relations and data-driven seal strength analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tomography methods are used to obtain velocity profiles, then the processing is simple and computationally efficient, but the velocity profiles are too smooth to detect embedded sand reservoirs and provide inaccurate pore pressure predictions
Solution Approach 1:
The inversion process is segmented into multiple stages: initial velocity model generation, impedance model generation, and pore pressure estimation. The velocity model is further segmented into background shale velocity and sand body velocity components, allowing separate optimization for each lithology type to achieve higher precision without excessive computational complexity
Solution Approach 2:
Acoustic impedance serves as an intermediary parameter between seismic velocity and pore pressure. By generating an impedance model from the velocity model and combining it with lithology-dependent pressure-velocity relations, the method achieves more accurate pore pressure predictions while maintaining manageable computational complexity through the intermediary transformation
2Measurement precision
If full wavefield inversion is used to generate high-resolution velocity models, then pore pressure prediction accuracy improves, but computational time and processing complexity increase
Solution Approach 1:
The method performs preliminary actions by generating a background velocity model and impedance model before final pore pressure estimation. The background shale velocity model is generated first as a starting point, then refined with sand body corrections. This staged approach allows computational resources to be allocated efficiently across multiple processing steps rather than requiring a single complex inversion
Solution Approach 2:
The inversion process applies local quality by generating lithology-specific velocity models (shale and sand) rather than a single uniform model. The method separately optimizes velocity parameters for different lithologies and combines them with lithology-dependent pressure-velocity relations, achieving high resolution where needed while maintaining computational efficiency through localized processing
3Loss of information
If smooth velocity profiles from tomography are used, then the velocity model is simple and easy to interpret, but embedded sand reservoirs cannot be detected and seal integrity cannot be assessed
Solution Approach 1:
The velocity model is segmented into distinct components: background shale velocity and sand body velocity. This segmentation allows the model to capture embedded sand reservoirs as distinct features within the shale matrix, providing the information loss recovery capability while maintaining a structured, interpretable model format
Solution Approach 2:
The method replaces conventional tomography mechanics with full wavefield inversion mechanics. By using wavefield simulation and inversion rather than traditional tomographic ray tracing, the method achieves higher resolution velocity models that can detect embedded features while maintaining computational manageability through modern numerical methods
Data Source
AI summary
A method, including: generating a velocity model for a subsurface region of the Earth by using a full wavefield inversion process; generating an impedance model for the subsurface region of the Earth by using a full wavefield inversion process; and estimating pore pressure at a prediction site in the subsurface region by integrating the velocity model and the impedance model with a velocity-based pore pressure estimation process.