Least-Squares Reverse Time Migration with Threshold Shrinkage

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Solution Overview

Problem

Migration algorithms for seismic data inversion are computationally intensive and struggle with blurring due to random noise and migration artifacts, leading to slow convergence and low-resolution images, especially in complex subsurface geologies.

Innovation Solution

The implementation of a least-squares reverse time migration method using an adjoint migration operator and a threshold shrinkage function, which includes a sign function and a maximum function, to update the property model and improve image resolution by attenuating noise and artifacts.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If migration algorithms are used to convert time-based seismic data into depth representation, then subsurface imaging is achieved, but computational cost and processing time increase significantly

Engineering Contradiction:

Improveseismic image resolutionVSAvoidcomputational processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent applies least-squares optimization to update the property model iteratively, changing the mathematical approach from conventional migration to a physics-based inversion framework. This transforms the problem parameters and convergence characteristics, achieving higher resolution while managing computational load through efficient update schemes

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent segments the seismic inversion process into distinct stages: initial property model creation, iterative least-squares updates using conjugate gradient solver, and threshold shrinkage refinement. This segmentation allows each stage to be optimized independently, reducing overall computational time while maintaining image quality

Inventive Principle:

Principle #1Segmentation

2Reliability

If conventional migration algorithms are used, then subsurface imaging is performed, but image quality deteriorates due to blurring from random noise and migration artifacts

Engineering Contradiction:

Improveimage qualityVSAvoidnoise and artifacts

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent converts the harmful effects of noise and artifacts by using the threshold shrinkage function to identify and attenuate these features. The least-squares inversion framework transforms random noise into structured updates that can be systematically reduced, converting what was previously harmful into a controllable aspect of the inversion process

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Solution Approach 2:

The patent introduces an intermediate property model that acts as a mediator between the raw seismic data and the final migrated image. This property model undergoes iterative refinement through least-squares updates and threshold shrinkage, serving as an intermediary that filters out noise and artifacts while preserving genuine subsurface features

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If complete migration-wavefield inversion is performed, then accurate subsurface representation is achieved, but the number of iterations required increases computational intensity

Engineering Contradiction:

Improvesubsurface representation accuracyVSAvoidprocessing efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent applies partial action by performing least-squares updates only on the property model rather than complete wavefield inversion at each step. The conjugate gradient solver is used iteratively with a limited number of inner iterations, providing sufficient accuracy without the full computational burden of complete inversion at every outer iteration step

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent performs preliminary action by first creating an initial property model using conventional migration, then using this as the starting point for least-squares refinement. This preliminary model provides a reasonable initial guess that reduces the number of iterative updates needed to achieve convergence, improving overall processing efficiency

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11733413B2Method and system for super resolution least-squares reverse time migration

Publication Date: 2023.08.22 SAUDI ARABIAN OIL CO

AI summary

A method may include obtaining seismic data regarding a geological region of interest. The method may further include obtaining a property model regarding the geological region of interest. The method may further include determining an adjoint migration operator based on the property model. The method may further include updating the property model using the seismic data and a conjugate gradient solver in a least-squares reverse time migration to produce a first updated property model. The conjugate gradient solver is based on the adjoint migration operator. The method may further include updating the first updated property model using a threshold shrinkage function to produce a second updated property model. The threshold shrinkage function comprises a sign function and a maximum function that are applied to the first updated property model. The method may further include generating a seismic image of the geological region of interest using the second updated property model.