Crossline Energy Measurement for Adaptive Survey Processing
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Solution Overview
Problem
Operators face challenges in selecting the appropriate data processing techniques (2D, 2.5D, or 3D) for subsurface structure surveys due to difficulties in determining the optimal processing method based on measured crossline energy, which affects the quality and computational efficiency of the survey data.
Innovation Solution
The method involves using crossline measurement data to determine the amount of crossline energy, allowing for the selection of the appropriate data processing technique (2D, 2.5D, or 3D) and adjusting acquisition parameters such as lateral spacing and vessel speed based on the detected energy levels, enabling quality control and superior survey data acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If 3D data processing technique is used, then the quality of subsurface structure characterization is improved, but the computational burden increases
Solution Approach 1:
The patent applies parameter changes by using crossline energy measurements to dynamically select between different data processing techniques (2D, 2.5D, or 3D). When crossline energy is low, simpler 2D processing is used; when crossline energy is high, more computationally intensive 3D processing is applied. This adaptive parameter selection optimizes the balance between characterization quality and computational burden based on actual subsurface conditions.
2Manufacturing precision
If appropriate data processing technique is selected based on crossline energy, then the quality of survey data is improved, but the complexity of determining the optimal processing method increases
Solution Approach 1:
The patent implements preliminary action by measuring crossline energy before selecting the data processing technique. This pre-assessment of crossline energy levels allows the system to determine the appropriate processing method (2D, 2.5D, or 3D) in advance, simplifying the decision-making process and improving data quality without requiring complex real-time analysis.
Solution Approach 2:
The system uses parameter changes by establishing threshold-based decision criteria for crossline energy levels. When crossline energy exceeds certain thresholds, specific processing techniques are automatically selected. This parameter-driven approach converts the complex decision-making process into a straightforward parameter comparison, reducing operational complexity while maintaining data quality.
3Manufacturing precision
If acquisition parameters such as lateral spacing and vessel speed are adjusted based on crossline energy, then the quality of survey data acquisition is improved, but the complexity of the survey operation increases
Solution Approach 1:
The patent applies feedback by continuously monitoring crossline energy levels and using this information to adjust acquisition parameters such as lateral spacing between streamers and vessel speed. The system provides feedback loops where measured crossline energy directly influences operational parameter adjustments, automatically optimizing data acquisition quality without requiring manual intervention or complex operational procedures.
Data Source
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AI summary
Methods and systems for survey operations are provided. In some embodiments, crossline measurement data measured by at least one survey receiver is received. Based at least in part on a characteristic of the crossline measurement data, an option from among a plurality of candidate options is selected, where the selected option is for use in an action relating to survey of a target structure.