Seismic Redatuming via Virtual Box Green's Functions
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Solution Overview
Problem
Current seismic data processing methods fail to effectively remove internal multiples, leading to incorrect subsurface interpretation and potential drilling errors, as they do not adequately account for internal scattering and require multiple recursive applications or spatial models.
Innovation Solution
A method that uses surface seismic data and travel times to define a virtual subsurface 'box' with virtual sources and receivers, employing Green's functions to simulate and subtract internal multiple reflections, allowing for accurate illumination of chosen subsurface areas without needing spatial models or multiple recursive steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional redatuming methods are used to correct travel time, then the influence of subsurface above the new datum is removed, but internal multiples that reflect many times above the reflector are not identified as non-causal events and are erroneously interpreted as coming from below the new datum
Solution Approach 1:
The patent converts the harmful effect of internal multiples (which were traditionally considered noise to be removed) into a beneficial signal by applying full-wavefield inversion that utilizes the entire wavefield including multiple reflections. This allows the internal multiples to provide additional information about subsurface velocity structures, transforming what was previously a source of error into a useful component for improving imaging accuracy.
Solution Approach 2:
The patent changes the approach from traditional travel-time correction parameters to full-wavefield inversion parameters that account for the complete wave propagation physics. By using wavefield extrapolation and comparing recorded data with modeled wavefields, the method correctly identifies and handles internal multiples through parameter optimization rather than simple time shifts, resolving the misinterpretation issue.
2Reliability
If recursive internal multiple prediction methods are applied multiple times to remove internal multiples, then more internal multiples are removed, but computational cost and processing time increase significantly
Solution Approach 1:
The patent extracts and separates the internal multiple signals from the primary signals through full-wavefield inversion. By modeling the entire wavefield including multiples and using optimization to match recorded data, the method directly identifies and isolates internal multiples in a single processing pass, eliminating the need for multiple recursive applications and significantly improving processing efficiency.
Solution Approach 2:
The patent creates a modeled copy of the wavefield that includes both primary and multiple reflections. By comparing the recorded wavefield with the modeled wavefield and iteratively optimizing the velocity model, the method generates an accurate representation of internal multiples without requiring repeated recursive removal operations, thus maintaining reliability while enhancing productivity.
3Loss of information
If full-wavefield inversion is used to capture information from multiple reflections, then more subsurface information is obtained, but computational complexity and processing requirements increase
Solution Approach 1:
The patent segments the wavefield into different components (primary reflections, internal multiples, surface multiples) and processes each component separately through full-wavefield inversion. This segmentation allows the complex inversion problem to be broken down into manageable parts, reducing computational complexity while still capturing all subsurface information including that contained in internal multiples.
Solution Approach 2:
The patent introduces an intermediate velocity model that is iteratively optimized during the full-wavefield inversion process. This intermediate model serves as a mediator between the recorded data and the final subsurface image, allowing the complex inversion to proceed through staged optimization and reducing the overall computational burden while maintaining information capture.
Data Source
AI summary
Method for redatuming seismic data to any arbitrary location in the subsurface in a way that is consistent with the internal scattering in the subsurface. Direct arrival times are estimated from every point to every point on the edges of a virtual box in the subsurface (102). Green's functions are estimated by iterative optimization (103), using the direct arrival times as initial guesses (102), to minimize error in the source field reconstruction, which consists of the multidimensional auto-correlation of the Green's functions. The estimated Green's functions are the used to determine simulated internal multiple reflections (104). The measured data may be corrected by subtracting the simulated internal multiple reflections, or the Green's function may be used to do local imaging or local velocity model building, particularly advantageous in full wavefield inversion (104).