Seismic Multiple Attenuation via Joint Source-Receiver Modeling

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Solution Overview

Problem

Current seismic data processing techniques, such as SRME and deconvolution, face challenges in effectively attenuating multiples, especially in shallow water environments due to limitations in near offsets and amplitude errors, leading to incomplete removal of multiple reflections which affect the accuracy of subsurface imaging.

Innovation Solution

A method involving a joint source-side and receiver-side multiple model approach using wave-equation deconvolution to generate demultiple data, which subtracts source-side and receiver-side multiple models from seismic data to produce a clearer image of the subsurface, improving the accuracy of multiple attenuation and reducing residual multiple effects.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If traditional multiple attenuation techniques (SRME, deconvolution) are used, then processing complexity is reduced, but multiple removal accuracy deteriorates in shallow water environments

Engineering Contradiction:
Improveprocessing complexityVSAvoidmultiple removal accuracy
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The patent segments the multiple attenuation process into three distinct components: (1) predicting surface-related multiples using recorded seismic data, (2) imaging the multiple generator through inverse scattering, and (3) predicting interbed multiples using the imaged multiple generator. This segmentation allows each component to be optimized independently, improving overall accuracy while managing processing complexity.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediate step of imaging the multiple generator using inverse scattering between the prediction of surface-related multiples and the prediction of interbed multiples. This intermediary imaging process serves as a mediator that captures complex multiple interactions, thereby improving the accuracy of subsequent multiple removal without requiring complete redesign of the entire processing workflow.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Measurement precision

If adaptive subtraction is used to correct amplitude errors, then multiple attenuation improves, but processing time increases

Engineering Contradiction:
Improvemultiple attenuation qualityVSAvoidprocessing time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent performs preliminary imaging of the multiple generator using inverse scattering on a subset of the data before proceeding with full multiple prediction and attenuation. This preliminary action pre-characterizes the multiple generator, which accelerates subsequent processing steps and reduces the computational burden of adaptive subtraction, thereby improving the efficiency-time tradeoff.

Inventive Principle:
Principle #10Preliminary action

3Measurement precision

If dense source and receiver sampling is used, then multiple model accuracy improves, but acquisition cost increases

Engineering Contradiction:
Improvemultiple model accuracyVSAvoidacquisition resources
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent applies inverse scattering to image the multiple generator on a subset or representative portion of the seismic data rather than requiring processing of the entire dense dataset. This partial action approach captures the essential characteristics of the multiple generator with sufficient accuracy for multiple prediction, thereby reducing acquisition resource requirements while maintaining adequate multiple model accuracy.

Inventive Principle:
Principle #16Partial or excessive action

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 enhances the accuracy of subsurface imaging by effectively removing multiples, improving the signal-to-noise ratio and reducing cross-talk, thereby providing a more precise representation of the geological formation.

Implementation Method 1

Energy generated by a seismic source propagates as seismic waves downward into a geological formation, and part of the energy is reflected and/or refracted back up to the surface

Methodology Applied
Scientific EffectSeismic wave propagation: Sound

Implementation Method 2

when the energy reflected from the subsurface reaches the water surface 104, it will be reflected back downwards into the water column and subsurface

Methodology Applied
Scientific EffectReflection: Reflection

Implementation Method 3

forward propagating a recorded wavefield into the subsurface using a wave equation

Methodology Applied
Scientific EffectWave equation propagation: Sound

Data Source

PatentEP4080250A1Multiple attenuation and imaging processes for recorded seismic data
Publication Date: 2022.10.26 CGG SERVICES SAS
  • EP4080250A1 patent drawingFigure 1
  • EP4080250A1 patent drawingFigure 2A~2C
  • EP4080250A1 patent drawingFigure 3~5

AI summary

A method for multiple attenuation in seismic data associated with a subsurface includes receiving (900) seismic data D for a plurality of shots and a plurality of receivers, where the seismic data D include multiples M associated with a free surface; obtaining (902) a multiple generator (722), which is located within the subsurface and is responsible for generating the multiples M; calculating (904) a source-side multiple model MS based on the seismic data D and the multiple generator (722); estimating (906) an image r of the multiple generator (722) based on a multiple periodicity method applied to the seismic data D; calculating (908) a receiver-side multiple model MR; generating (910) demultiple data DD by subtracting from the seismic data D the source-side multiple model MS and the receiver-side multiple model MR; and generating (912) a final image of a geological formation based on the demultiple data DD.