Reconstructing In-Line Seismic Motion via Pressure and Cross-Line Data
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Solution Overview
Problem
Seismic data acquisition systems face challenges in accurately reconstructing the in-line component of the particle motion vector due to mechanical filtering and noise propagation in cables, leading to sub-optimal signal-to-noise ratios and aliasing issues, especially in 3C streamers.
Innovation Solution
The technique processes first data indicative of pressure measurements and cross-line and vertical components of the particle motion vector to reconstruct the in-line component, allowing for 4C-based geophysical processing without the need for explicit in-line particle motion sensors, effectively utilizing 3C or 4C streamer data to achieve 4C measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If in-line particle motion sensors are installed in 3C streamers to directly measure the in-line component, then measurement completeness is improved, but device complexity and susceptibility to mechanical filtering and noise increase
Solution Approach 1:
The patent uses pressure sensors and cross-line/vertical particle motion sensors as intermediary measurements to indirectly derive the in-line component through mathematical reconstruction. Instead of directly measuring the in-line component with dedicated sensors, the system uses available measurements from other sensors as intermediaries to compute the desired quantity, avoiding the complexity and noise issues of direct measurement
Solution Approach 2:
The patent replaces the mechanical measurement system (physical in-line particle motion sensors) with a computational approach. By substituting direct mechanical sensing with mathematical reconstruction algorithms that process pressure and other particle motion components, the system eliminates the need for additional mechanical sensors while achieving the same measurement objective
2Measurement precision
If explicit in-line particle motion sensors are used, then direct measurement capability is improved, but signal-to-noise ratio deteriorates due to mechanical filtering and noise propagation in cables
Solution Approach 1:
The patent extracts the in-line component information from indirect measurements (pressure and other particle motion components) rather than relying on direct sensor output. By separating the measurement function into multiple indirect sensors and using mathematical reconstruction, the system avoids extracting the signal through the noisy cable infrastructure that affects direct in-line sensors
Solution Approach 2:
The patent creates a computational copy of the in-line component measurement through mathematical reconstruction. Instead of relying on a physical sensor copy that suffers from cable noise, the system generates a virtual copy of the in-line measurement by processing and combining data from pressure and other particle motion sensors through reconstruction algorithms
3Measurement precision
If 3C streamer data is processed to achieve 4C measurements, then measurement completeness is improved, but processing complexity increases
Solution Approach 1:
The patent makes the processing system universal by creating a reconstruction framework that can derive 4C measurements from 3C data. The same processing operations can handle both 3C and 4C streamer data, providing multi-functionality where the system adapts to different sensor configurations without requiring separate processing pipelines for each case
Data Source
AI summary
A technique includes receiving first data indicative of a pressure measurement and measurements of components of a particle motion vector acquired by sensors disposed on at least one cable; and processing the first data to generate second data indicative of a constructed an in-line component of the particle motion vector. The technique includes processing the first and second data in a geophysical processing operation that relies on at least three components of the particle motion vector.