Seismic Deblending with Expanded Window Noise Attenuation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Simultaneous source seismic acquisition leads to blending noise interference, making it difficult to separate coherent signals from incoherent noise without affecting the integrity of blending noise, especially when dealing with weak amplitude signals, which are not addressed effectively by existing methods.
Innovation Solution
Enhanced deblending operations that include expanding the gather window to include seismic data before the time of seismic source excitation, allowing for noise attenuation during signal separation, and using iterative inversion-based techniques to recover weak primary signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If simultaneous source seismic acquisition is used to improve productivity, then data acquisition efficiency is improved, but blending noise interference increases making it difficult to separate coherent signals from incoherent noise
Solution Approach 1:
The patent applies segmentation by dividing the blended seismic signal into individual source components through iterative deblending operations. Each source signal is separated and reconstructed individually from the mixed recording, allowing coherent signals to be isolated from incoherent noise while maintaining the productivity benefits of simultaneous acquisition.
Solution Approach 2:
The patent introduces an intermediary approach by using predictive deconvolution and iterative inversion techniques as mediators between the blended recording and the separated source signals. These computational methods act as intermediaries that model and remove blending noise while preserving coherent seismic signals, resolving the contradiction between simultaneous acquisition benefits and noise interference.
2Object-affected harmful factors
If existing deblending methods are used to separate signals, then some noise reduction is achieved, but weak amplitude signals are not effectively recovered and signal integrity is compromised
Solution Approach 1:
The patent implements feedback through iterative deblending operations where the separated signals are continuously refined and re-injected into the processing loop. Each iteration uses the previous results to improve the separation of weak amplitude signals, with feedback mechanisms that preserve signal integrity while progressively reducing noise. This allows weak signals to be recovered without compromising their authenticity.
Solution Approach 2:
The patent applies preliminary action by performing predictive deconvolution and noise modeling before final signal separation. These preliminary operations prepare the data by pre-attenuating dominant noise components and preserving weak signal structures, making subsequent deblending more effective at recovering weak amplitude signals without compromising signal integrity.
3Object-affected harmful factors
If aggressive noise attenuation is applied to remove incoherent noise, then signal-to-noise ratio improves, but blending noise integrity is affected and coherent signals may be distorted
Solution Approach 1:
The patent applies local quality by treating different signal components with different processing strategies. Coherent signals receive preservation-focused processing while incoherent noise components receive targeted attenuation. This localized approach allows aggressive noise reduction in specific frequency and time domains while maintaining the integrity of blending noise that contains coherent signal information.
Solution Approach 2:
The patent uses parameter changes through iterative inversion where processing parameters such as prediction operators, regularization weights, and frequency thresholds are dynamically adjusted throughout the deblending process. These parameter changes enable progressive noise attenuation that improves signal-to-noise ratio while preserving blending noise integrity by adapting the processing strength to the local signal characteristics.
Data Source
AI summary
A tangible, non-transitory, machine-readable media, includes instructions configured to cause a processor to determine a residual associated with input seismic data received from a seismic source. The residual is indicative of a difference between expected input seismic data and the input seismic data, and wherein the input seismic data is configured to be combed with an expanded window such that the expanded window comprises data generated by an earlier seismic source excitation and received before a time of a seismic source excitation that generated an input seismic trace corresponding to the input seismic data. The instructions are also configured to cause the processor to determine a deblended output based at least in part on the residual. In addition, the instructions are configured to cause a processor to update the deblended output based at least in part on a result from performing one or more recovery operations configured to recover coherent signals from non-coherent signals of the deblended output. The coherent signals comprise a matching parameter. Further, the instructions are configured to cause a processor to filter the deblended output to remove a portion of the deblended output that is before the time of the seismic source excitation or before a predicted earliest arrival time of a seismic wave travelling from the seismic source to a receiver, to generate an improved deblended output comprising less noise than the deblended output. Still further, the instructions configured to cause a processor to transmit the filtered deblended output for use in generating a seismic image. The seismic image represents hydrocarbons in a subsurface region of Earth or subsurface drilling hazards.