Seismic Sensor Gain Segmentation for Clipping and Noise
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Solution Overview
Problem
Seismic sensors often experience data clipping when close to the source and struggle to distinguish seismic data from noise when far away, leading to inaccurate interpretations during seismic surveys.
Innovation Solution
Deploying a plurality of seismic sensors with multiple gain configurations and dynamic ranges, allowing each sensor to select from various gains to prevent clipping and distinguish data from noise, and processing seismic data to combine signals into a higher dynamic range for accurate interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single gain configuration is used for all seismic sensors, then device complexity is reduced, but measurement precision deteriorates due to clipping near the source and noise interference far from the source
Solution Approach 1:
The sensor array is segmented into multiple groups, each equipped with a specific gain configuration. This segmentation allows different regions of the survey area to be monitored by sensors optimized for their specific distance from the source, thereby improving measurement precision without requiring every individual sensor to have multiple gain settings.
Solution Approach 2:
Different gain configurations are assigned to different sensor groups based on their local conditions (distance from source). Sensors closer to the source use lower gain to avoid clipping, while sensors farther away use higher gain to overcome noise interference. This local optimization of gain settings improves overall measurement precision while maintaining manageable device complexity.
2Reliability
If seismic sensors are placed close to the source to capture strong signals, then signal strength is improved, but data quality deteriorates due to clipping
Solution Approach 1:
The gain parameter is changed based on the sensor's distance from the source. By adjusting the gain configuration according to location, the system maintains signal strength while preventing clipping. Sensors closer to the source use lower gain settings, while those farther away use higher gain settings, ensuring optimal data quality across all positions.
3Measurement precision
If seismic sensors are placed far from the source to avoid clipping, then data quality is improved, but measurement precision deteriorates due to noise interference
Solution Approach 1:
The gain parameter is increased for sensors located farther from the source to amplify weak seismic signals. This parameter adjustment compensates for the reduced signal strength at greater distances, allowing these sensors to maintain measurement precision despite the increased relative level of noise interference.
4Adaptability or versatility
If multiple gain configurations are deployed across the sensor array, then adaptability is improved, but device complexity increases
Solution Approach 1:
The sensor array is divided into discrete groups, each with a specific gain configuration. This segmentation provides adaptability to different survey conditions while limiting the complexity of individual sensor units. Each group is assigned a gain setting appropriate for its distance from the source, achieving system-level adaptability without requiring complex multi-configuration sensors.
Solution Approach 2:
Multiple sensor groups with different gain configurations work together as a unified system to handle various survey conditions. This multi-functional approach allows the same sensor hardware design to serve multiple purposes by being deployed in different gain configurations, achieving adaptability without increasing individual sensor complexity.
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
Enables accurate interpretation of seismic data by preventing clipping and noise interference, ensuring comprehensive data capture regardless of sensor location, resulting in improved subsurface imaging.
Implementation Method 1
Each time the source is activated, the source generates seismic (e.g., sound wave) energy that travels downward through the Earth, is reflected, and, upon its return, is recorded using one or more seismic sensors
Data Source
AI summary
In some examples, the disclosure provides a method for deploying a plurality N of seismic sensors, wherein each seismic sensor is adapted to measure seismic energy with at least one gain, within a survey area, the method comprising: obtaining a plurality M of gains from which the at least one gain may be selected; configuring the plurality N of seismic sensors such that, for each given gain of the obtained plurality M of gains, at least N/M seismic sensors are adapted to measure the seismic energy with at least one corresponding gain; and deploying the plurality N of configured seismic sensors on the survey area.