Far Field Signature Reconstruction via Multi-Field Sensor Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current seismic survey systems face challenges in accurately reconstructing the far field signature, which is crucial for subsurface geological structure analysis, due to limitations in data collection from near field and mid field sensors, leading to inferior data quality.
Innovation Solution
A method and system that combine seismic traces from near field, mid field, and surface field sensors to compute notional signatures, which are then linearly superimposed to determine a more accurate far field signature, utilizing position information and surface reflection coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data is collected only from near field and mid field sensors, then the device complexity is reduced, but the measurement precision of far field signature reconstruction deteriorates
Solution Approach 1:
The patent introduces surface field sensors as intermediary measurement points between near field and mid field sensors. These surface field sensors capture seismic data at the ocean surface, which serves as a mediator to bridge the gap between near field and mid field measurements, enabling more accurate far field signature reconstruction without requiring direct far field sensor deployment
Solution Approach 2:
The patent adds a new spatial dimension by deploying sensors at the ocean surface (surface field), creating a three-dimensional sensor distribution pattern. This dimensional addition allows the system to capture seismic waves from multiple angles and depths, improving reconstruction accuracy without proportionally increasing system complexity
2Measurement precision
If sensors are deployed in the far field to directly measure the signature, then the measurement precision is improved, but the device complexity and operational difficulty increase
Solution Approach 1:
The patent performs preliminary measurements in the near field, mid field, and surface field before reconstructing the far field signature. By collecting data from these accessible locations first and then computationally deriving the far field signature, the system avoids the complexity of direct far field sensor deployment while maintaining measurement accuracy
Solution Approach 2:
The patent creates a computational model (copy) of the far field signature based on measurements from near field, mid field, and surface field sensors. This computational copy allows the system to obtain far field signature data without physically placing sensors in the far field, thereby reducing deployment complexity and operational difficulty
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 a more accurate reconstruction of the far field signature, improving the quality of subsurface geological feature analysis by integrating data from multiple sensor fields.
Implementation Method 1
Each seismic sensor, or 'sensor,' may be a hydrophone, which detects variations in pressure below the ocean surface. The sensors transform the seismic waves into seismic traces suitable for analysis.
Implementation Method 2
The signal source generates a seismic signal, which is a series of seismic waves that travel in various directions including toward the ocean floor. The seismic waves penetrate the ocean floor and are at least partially reflected by interfaces between subsurface layers having different seismic wave propagation speeds.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A system and method for reconstructing a far field signature with data fusion from near field, mid field, and surface field hydrophone recordings is disclosed. The method includes receiving a first trace from a first sensor (e.g., hydrophone) and a second trace from a second sensor located in a different field from the first sensor. The method also includes receiving position information for the first and second sensors. The method further includes reconstructing a far field signature of the seismic signal based on the first trace, the second trace, and the position information.