4D Seismic Velocity Estimation Using Non-Zero Offset Ray Tracing

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Solution Overview

Problem

Current 4D seismic data processing methods face challenges in accurately estimating time shifts and velocity changes in subsurface volumes, particularly in regions like the overburden and underburden, due to weak signal amplitudes and non-linear inversion complexities, and often rely on zero-offset assumptions that discard direction-dependent information.

Innovation Solution

A method that uses non-zero offset pre-stack seismic data and ray tracing to determine seismic signal paths, allowing for the estimation of velocity changes without processing the data to zero-offset, and employs a linear tomographic system to link offset-dependent time shifts to model parameters, eliminating the need for zero-offset assumptions and enhancing the accuracy of time-lapse velocity anomaly detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If zero-offset assumptions are used in 4D seismic processing, then the processing complexity is reduced, but direction-dependent information is lost and measurement precision deteriorates

Engineering Contradiction:
Improveprocessing complexityVSAvoidmeasurement precision
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

Instead of converting non-zero offset data to zero-offset data (conventional approach), the invention inverts the approach by directly processing non-zero offset pre-stack data using ray tracing and tomographic inversion. This preserves direction-dependent information while avoiding the complexity of zero-offset conversion

Inventive Principle:
Principle #13The other way round (Inversion)

Solution Approach 2:

The invention adds the offset dimension back into the processing by using non-zero offset pre-stack data instead of stacked zero-offset data. Ray tracing operations incorporate offset-dependent time shifts, utilizing the additional dimensional information to improve measurement precision

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Measurement precision

If non-zero offset pre-stack data is used with ray tracing, then direction-dependent information is retained and measurement precision improves, but computational complexity increases

Engineering Contradiction:
Improvemeasurement precisionVSAvoidcomputational complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

Ray paths are determined once using ray tracing before the inversion process. These pre-computed ray paths are then reused in the tomographic inversion, avoiding the need to re-trace rays during each iteration and significantly reducing computational complexity

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The invention introduces a linear tomographic system as an intermediary between the non-zero offset pre-stack data and the velocity model updates. This linear system simplifies the inversion mathematics and reduces computational burden compared to fully non-linear inversion approaches

Inventive Principle:
Principle #24Intermediary (Mediator)

3Device complexity

If conventional 4D inversion is used, then processing is simpler, but accuracy in overburden and underburden regions deteriorates due to weak signal amplitudes

Engineering Contradiction:
Improveprocessing simplicityVSAvoidaccuracy
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The invention applies local quality by treating different subsurface regions (overburden, reservoir, underburden) with appropriate weighting in the objective function. This allows the processing to be more sensitive to weak signals in specific regions while maintaining overall processing efficiency

Inventive Principle:
Principle #3Local quality

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 enables more precise characterization of subsurface volume evolution over time by retaining direction-dependent information and improving the estimation of time shifts and velocity changes, even in structurally complex regions, without the computational expense of re-tracing ray paths for each iteration.

Implementation Method 1

one or several sources emit elastic waves in the form of pressure or ground motion modulation from specific locations (wavefield), at or below the land or sea surface or in a borehole. This wavefield propagates away from the source(s) through the subsurface.

Methodology Applied
Scientific EffectSeismic wave propagation: Sound

Implementation Method 2

Along with this propagation, a fraction of the incident wavefield is reflected from the heterogeneities in the elastic material properties of the subsurface (such as acoustic impedance).

Methodology Applied
Scientific EffectReflection: Reflection

Data Source

PatentEP3243089B1Method for obtaining estimates of a model parameter so as to characterise the evolution of a subsurface volume over a period of time
Publication Date: 2021.09.22 TOTALENERGIES ONETECH
  • EP3243089B1 patent drawingFigure 1(a)~1(b)
  • EP3243089B1 patent drawingFigure 2(a)~2(b)
  • EP3243089B1 patent drawingFigure 3

AI summary

< > 26 <<06/01/2015>> Abstract Disclosed is a method for characterising the evolution of a subsurface volume over time. Themethod comprises providing firstand secondsurveysof the subsurface volume. Each survey comprises seismic data acquired by transmitting seismic signals into thesubsurface volume and subsequently detecting some or all of the seismic signals after reflection within the subsurface.The first seismic data of the first survey correspondsto a first timeand thesecondseismic data of the second survey corresponds to a secondtime. At least some of the first seismic data and the second seismic data isobtained with a non-zero offset. An inversionis performedto obtain estimates of changes having occurred between the first time and the second time in terms of at least one model parameter;wherein for the inversion: the first seismic data and the second seismic data is not processed to be equivalent to zero-offset data prior to the inversion; andit is assumed that the path taken by each received seismic signal between its transmission and reception is the same for the first survey and the second survey