Passive Seismic Imaging via Virtual Shot Records
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Solution Overview
Problem
Existing seismic imaging techniques face challenges in generating high-resolution images of near-surface hydrocarbon deposits due to the limitations of active seismic sources, which produce high-frequency waves difficult to image at depths below 500m and are resource-intensive, while passive seismic sources offer lower frequencies and lower signal-to-noise ratios, making it hard to achieve accurate subsurface imaging without manual time picking and potential human error.
Innovation Solution
The method involves computing virtual seismic shot records from passive seismic data using seismic interferometry and cross-correlation, determining frequency bandwidth, applying phase shifts, and generating a first velocity model to extract depth slices, which can be combined with active seismic data to create a higher resolution image, reducing the need for manual time picking and improving signal-to-noise ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If active seismic sources are used to generate high-frequency waves for subsurface imaging, then imaging resolution is improved, but resource consumption and operational costs increase
Solution Approach 1:
The patent combines passive seismic data with active seismic data to create a hybrid imaging approach. The passive data provides cost-effective coverage while the active data supplements critical high-frequency information, merging the advantages of both sources to achieve high resolution without proportional resource consumption
Solution Approach 2:
The velocity model serves multiple functions: it is used for imaging, for signal processing, and for integrating different data types (passive and active). This multi-functional use maximizes the value extracted from the acquired data, reducing the need for additional resource-intensive surveys
2Use of energy by moving object
If passive seismic sources are used to reduce operational costs, then resource consumption is reduced, but signal-to-noise ratio deteriorates
Solution Approach 1:
The patent uses a velocity model as an intermediary to process and enhance passive seismic data. This velocity model, derived from both passive and active data, acts as a mediator that improves the signal-to-noise ratio of the passive data through proper signal processing and imaging algorithms
Solution Approach 2:
The patent merges passive and active seismic data to create a composite dataset that leverages the low operational cost of passive sources while using the high signal-to-noise ratio characteristics of active sources to enhance overall data quality through combined processing
3Measurement precision
If manual time picking is performed to process passive seismic data, then measurement precision may be improved, but human error increases
Solution Approach 1:
The patent replaces manual time picking (mechanical human operation) with automated signal processing algorithms and imaging techniques. These computational methods objectively analyze the seismic data to derive velocity models and imaging results, eliminating human error while maintaining or improving measurement precision through consistent, repeatable processes
Solution Approach 2:
The imaging system performs self-service by using the seismic data itself to automatically determine velocity models and generate images through algorithmic processing. The data processing pipeline is self-correcting and self-optimizing, reducing reliance on manual intervention and associated human errors
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 allows for more stable and cost-effective generation of high-resolution seismic images, particularly for near-surface layers, by leveraging passive seismic data to supplement active data, reducing human error and improving imaging quality with lower operational costs.
Implementation Method 1
computing virtual seismic shot records from passive seismic data using seismic interferometry
Implementation Method 2
cross-correlation of the passive seismic data
Implementation Method 3
a phase shift is applied and a first velocity model is computed
Data Source
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AI summary
A virtual seismic shot record is generated based at least in part on seismic interferometry of the passive seismic data. Then, a frequency bandwidth of the virtual seismic shot record is determined, wherein the frequency bandwidth comprises a plurality of frequencies. The virtual seismic shot record is transformed into a frequency- dependent seismic shot record based on a first frequency of the plurality of frequencies. Further, a phase shift is applied to the frequency-dependent seismic shot record. A first velocity model is generated from the phase shifted frequency-dependent seismic shot record. A second velocity model may be generated using full-waveform inversion (FWI). One or more depth slices are identified from the second velocity model. A seismic image is generated based on the one or more depth slices for use with seismic exploration above a region of subsurface including a hydrocarbon reservoir and containing structural features conducive to a presence, migration, or accumulation of hydrocarbons.