Interbed Multiple Prediction and Subtraction in Seismic Imaging
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Solution Overview
Problem
Seismic data processing often incorrectly handles seismic waves that have been reflected multiple times, leading to the creation of fictitious reflectors or masking of real ones in seismic images, due to the assumption that only primary reflections are present.
Innovation Solution
A method to determine and subtract interbed multiple signals from seismic datasets by generating multiple-generator traces and correlation traces, and convolving them to predict and remove interbed multiple traces, resulting in an attenuated pre-stack seismic dataset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If seismic data is processed assuming only primary reflections are present, then processing is simpler and faster, but fictitious reflectors appear and real reflectors are masked or blurred
Solution Approach 1:
The method performs preliminary identification and prediction of multiple signals before the main imaging process. By generating multiple predictions using different multiple-generation models and identifying actual multiples through correlation analysis, the system prepares multiple signal estimates in advance that can be subtracted from the seismic data, preventing imaging artifacts before they occur
Solution Approach 2:
The invention introduces multiple-generation models and correlation traces as intermediary tools. These intermediaries generate predicted multiple signals that serve as mediators between the raw seismic data and the final processed image, allowing the system to separate and remove multiple signals without directly processing the complex mixed signals
2Manufacturing precision
If multiple signals are removed from seismic data, then imaging accuracy improves, but processing complexity increases
Solution Approach 1:
The method segments the multiple signal removal process into distinct components: multiple prediction using different models, correlation analysis to identify actual multiples, and selective subtraction. This segmentation allows each component to be optimized independently and makes the overall complex process more manageable and systematic
Solution Approach 2:
The invention changes parameters by using different multiple-generation models with varying assumptions and parameters. By adjusting model parameters and selecting the most appropriate model based on correlation analysis, the system adapts to different seismic data characteristics without requiring a completely different processing approach
Data Source
AI summary
Methods and systems for determining an interbed multiple attenuated pre-stack seismic dataset are disclosed. The methods include forming a post-stack seismic image composed of post-stack traces from the pre-stack seismic dataset and identifying a first, second, and third post-stack horizon on each of the post-stack traces. The methods further include for each pre-stack trace, generating a first, second, and third multiple-generator trace based on the first, second and third post-stack horizon and determining a correlation trace based, at least in part, on a correlation between the first multiple-generator trace and the second multiple-generator trace. The methods still further include predicting an interbed multiple trace by convolving the correlation trace and the third multiple-generator trace, determining an interbed multiple attenuated trace by subtracting the interbed multiple trace from a corresponding pre-stack seismic trace, and determining the interbed multiple attenuated pre-stack seismic dataset by combining the interbed multiple attenuated traces.