Q-Compensated Full Wavefield Inversion for Gas Anomaly Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional seismic prospecting methods fail to accurately image subsurface structures due to energy diffusion caused by acoustic impedance anomalies, leading to incorrect representation of subsurface features and inability to recover amplitude and bandwidth loss beneath gas anomalies.
Innovation Solution
A method combining ray-based pseudo-Q migration with visco-acoustic full wavefield inversion, where a variable Q model is generated and fixed throughout the inversion process to compensate for Q effects, preventing energy leakage and improving subsurface imaging fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional acoustic full wavefield inversion is used, then the inversion process is computationally simpler and faster, but the subsurface imaging accuracy deteriorates due to energy diffusion caused by acoustic impedance anomalies
Solution Approach 1:
The patent changes the physical parameters of the wave equation by introducing visco-acoustic effects with frequency-dependent attenuation coefficients. The quality factor Q is introduced to characterize energy dissipation, transforming the standard acoustic wave equation into a visco-acoustic wave equation that accounts for anelastic attenuation. This parameter change enables accurate modeling of energy diffusion while maintaining computational feasibility through efficient Q-compensation algorithms.
Solution Approach 2:
The patent introduces Q-compensation as an intermediary mechanism between the acoustic wave equation and the visco-acoustic wave equation. By applying Q-compensation operators that model energy dissipation and frequency-dependent attenuation, the method bridges the gap between simple acoustic modeling and complex visco-acoustic behavior, enabling accurate subsurface imaging without requiring full visco-acoustic inversion complexity.
2Measurement precision
If Q-compensated visco-acoustic full wavefield inversion is implemented, then the accuracy of subsurface representation improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent applies Q-compensation preliminarily during the forward modeling and adjoint modeling stages before the actual inversion process. By pre-compensating for Q effects in the wavefield simulations, the inversion algorithm receives already-corrected data, reducing the complexity of the inversion itself. This preliminary Q-compensation separates the computationally intensive attenuation correction from the parameter optimization process.
Solution Approach 2:
The patent segments the inversion process into distinct modules: (1) acoustic full wavefield inversion for initial velocity model building, (2) Q-factor estimation from the initial model, and (3) visco-acoustic full wavefield inversion with Q-compensation for final high-accuracy imaging. This segmentation allows each module to be optimized independently and enables iterative refinement without requiring simultaneous optimization of all parameters.
3Use of energy by moving object
If seismic energy is transmitted vertically into the earth, then the energy efficiently reflects off subsurface reflectors providing meaningful information, but the energy is undesirably diffused by acoustic impedance anomalies in the subsurface
Solution Approach 1:
The patent converts the harmful effect of Q-anomalies (energy diffusion and attenuation) into a beneficial imaging tool. By measuring the frequency-dependent attenuation characteristics of seismic waves as they propagate through the subsurface, the method uses the very same Q-effects that cause image degradation to generate Q-factor maps that highlight subsurface anomalies. These Q-anomaly maps then guide targeted Q-compensation in the inversion process, turning the harmful diffusion into useful diagnostic information.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively compensates for Q effects, resulting in improved structural representation and reliable velocity models, especially in areas with gas anomalies, enhancing geological interpretation and hydrocarbon detection.
Implementation Method 1
Seismic waves attenuate for a variety of reasons as they travel in a subsurface environment. A quality metric (sometimes referred to a quality factor) Q is typically used to represent attenuation characteristics of underground formations.
Implementation Method 2
As waves travel, they lose energy with distance and time due to spherical divergence and absorption.
Implementation Method 3
During Q migration, a seismic data value representing travel of seismic energy through a subsurface structure having a relatively low Q value may be amplified and broadened in spectrum to a greater degree than a data value representing travel of seismic energy through a subsurface structure having a relatively high Q value.
Implementation Method 4
Altering the amplitude and phase of data associated with low Q values takes into account the larger signal attenuation that occurs when seismic energy travels through structures having a relatively low Q value.
Implementation Method 5
FWI is a partial-differential-equation-constrained optimization method which iteratively minimizes a norm of the misfit between measured and computed wavefields.
Data Source
AI summary
A method, including: obtaining a velocity model generated by an acoustic full wavefield inversion process; generating, with a computer, a variable Q model by applying pseudo-Q migration on processed seismic data of a subsurface region, wherein the velocity model is used as a guided constraint in the pseudo-Q migration; and generating, with a computer, a final subsurface velocity model that recovers amplitude attenuation caused by gas anomalies in the subsurface region by performing a visco-acoustic full wavefield inversion process, wherein the variable Q model is fixed in the visco-acoustic full wavefield inversion process.