Broadband Single-Sensor Seismic Data Processing Workflow

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Solution Overview

Problem

Existing seismic data processing workflows for broadband single-sensor single-source land seismic data fail to restore received signals to desired broadband zero-phase wavelets, particularly struggling with signal smearing and noise impact, which hampers the recovery of low and high-frequency signals and structural interpretation.

Innovation Solution

The approach involves deterministic differential filtering to convert seismic traces from receiver-measured particle motion to source-represented motion, followed by deterministic inverse-Q filtering to correct for earth absorption, and iterative derivation of surface-consistent filters and attributes for noise removal and deconvolution, enhancing temporal resolution and signal recovery.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If traditional seismic processing workflows are used, then processing simplicity is maintained, but signal recovery quality deteriorates due to inability to restore broadband zero-phase wavelets

Engineering Contradiction:

Improvesignal recovery qualityVSAvoidprocessing workflow complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The processing workflow is segmented into distinct functional modules: deterministic differential filtering module, deterministic inverse-Q filtering module, and iterative surface-consistent filtering module. Each module addresses specific signal degradation aspects, allowing complex processing to be broken down into manageable, targeted operations that collectively restore broadband zero-phase wavelets

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Deterministic differential filtering is applied as a preliminary step to convert particle motion measurements before subsequent processing. This preliminary action prepares the signal in the correct form for inverse-Q filtering, enabling more effective signal recovery in later stages without requiring complete reprocessing

Inventive Principle:

Principle #10Preliminary action

2Manufacturing precision

If deterministic differential filtering and inverse-Q filtering are applied, then low and high-frequency signal recovery is improved, but processing computational load increases

Engineering Contradiction:

Improvefrequency signal recoveryVSAvoidprocessing computational load

Core Design Contradiction:

Manufacturing precisionVSPower

Solution Approach 1:

The iterative surface-consistent filtering module dynamically adjusts filter parameters based on statistical analysis of the seismic data. Rather than using fixed computational parameters, the system adapts filtering strength and characteristics to the actual signal properties, optimizing computational efficiency while maintaining frequency recovery quality

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

Deterministic inverse-Q filtering applies parameter changes to compensate for frequency-dependent attenuation. By modeling and reversing the effects of earth absorption with specific Q-values, the process restores both low and high-frequency components that would otherwise be lost, achieving comprehensive frequency spectrum recovery

Inventive Principle:

Principle #35Parameter changes

3Manufacturing precision

If iterative surface-consistent filtering is used, then noise removal and deconvolution effectiveness is enhanced, but processing time increases

Engineering Contradiction:

Improvenoise removal effectivenessVSAvoidprocessing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The iterative surface-consistent filtering module uses feedback from statistical analysis of filtered traces to continuously refine filter parameters. Each iteration uses the results of previous filtering to adjust subsequent filtering operations, progressively improving noise removal effectiveness while converging to an optimal solution that balances quality and processing time

Inventive Principle:

Principle #23Feedback

4Measurement precision

If broadband zero-phase wavelet restoration is achieved, then structural interpretation accuracy is improved, but processing complexity increases

Engineering Contradiction:

Improvestructural interpretation accuracyVSAvoidprocessing module complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The deterministic filtering modules serve multiple functions: they correct particle motion representations, compensate for frequency attenuation, and prepare signals for subsequent imaging. This multi-functionality reduces the need for separate dedicated processing steps, achieving wavelet restoration without proportionally increasing overall system complexity

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10288755B2Seismic processing workflow for broadband single-sensor single-source land seismic data

Publication Date: 2019.05.14 SAUDI ARABIAN OIL CO

AI summary

A method for processing broadband single-sensor single-source land seismic data includes receiving seismic traces, the seismic traces generated using at least one source and at least one receiver; converting the seismic traces from particle motion measured by the at least one receiver to particle motion represented by the at least one source by applying a deterministic differential filtering operation; applying a deterministic inverse-Q filtering operation on the converted seismic traces; processing the inverse-Q filtered seismic traces using a set of surface-consistent filter and attribute corrections; and generating a seismic image based on the processed seismic traces.