Seismic Survey Design Optimization via F-K Filtering
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Solution Overview
Problem
Current methods for analyzing the quality of 3D seismic surveys are flawed, being subjective and failing to account for variations in sampling and field implementation, leading to inadequate data quality and decision-making in oil and gas exploration.
Innovation Solution
The use of novel methods involving common mid-point (CMP) arrays and treating the entire survey as a single set of sources and receivers for F-K filtering, allowing for the analysis and optimization of seismic survey designs to minimize artifacts and improve sampling quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional subjective methods are used to analyze seismic survey quality, then the analysis process is simple, but the measurement precision and reliability of survey quality assessment deteriorate
Solution Approach 1:
The patent replaces subjective human visual inspection with automated F-K filtering and spectral analysis methods. The system uses computer-based frequency-wavenumber filtering to objectively analyze survey quality, substituting mechanical human judgment with automated computational analysis that provides precise, quantifiable measurements of sampling quality and artifacts.
Solution Approach 2:
The patent introduces F-K filtering as an intermediary analytical tool between the raw seismic data and the quality assessment. This intermediary process transforms the data into the frequency-wavenumber domain, allowing for objective identification of sampling patterns and artifacts that would be difficult to detect through direct visual inspection, thereby improving measurement precision.
2Reliability
If conventional survey design analysis is used, then the device complexity is low, but the reliability of data quality and decision-making deteriorates due to inadequate accounting for sampling variations
Solution Approach 1:
The patent performs preliminary F-K filtering and spectral analysis on survey designs before actual data acquisition. By analyzing the expected sampling patterns and potential artifacts in advance, the system allows for optimization of source and receiver positioning to ensure reliable data quality before field deployment, rather than discovering quality issues after acquisition.
Solution Approach 2:
The patent implements a feedback mechanism where the results of F-K filtering and artifact analysis are used to iteratively improve survey design. The system provides quantitative feedback on sampling quality and identified artifacts, allowing designers to adjust source and receiver positions to eliminate problematic sampling patterns, thereby enhancing the reliability of the final survey data.
3Measurement precision
If detailed F-K filtering and artifact correction is applied, then the measurement precision of survey quality analysis improves, but the loss of time in processing and analysis increases
Solution Approach 1:
The patent performs F-K filtering and spectral analysis during the survey design phase before actual data acquisition. By identifying and correcting sampling issues in advance through preliminary analysis, the system avoids the need for extensive post-processing corrections, thereby reducing overall processing time while maintaining high measurement precision in the final survey data.
4Manufacturing precision
If the survey area is expanded to include migration apron and fold taper zones, then the manufacturing precision of subsurface imaging improves, but the quantity of data and area to be processed increases
Solution Approach 1:
The patent applies F-K filtering and artifact analysis with local quality considerations, focusing computational resources on identifying and correcting sampling issues in specific problem areas rather than uniformly processing the entire expanded survey area. This allows for targeted optimization of imaging precision in critical zones while managing the overall data processing load.
Data Source
AI summary
Methods and systems of analyzing and optimizing a seismic survey design are described. A system includes a plurality of seismic receivers disposed in a survey area at a plurality of receiver locations. The system also includes a plurality of seismic sources disposed in the survey area at a plurality of source locations. The plurality of receiver locations and the plurality of source locations are specified by a seismic survey design minimizing any artifacts identified in a filtered spectrum obtained by applying a frequency-wavenumber filter to a central midpoint space summation. The plurality of receiver locations and the plurality of source locations are determined based on a comparison of the filtered spectrum to a second filtered spectrum. The second filtered spectrum is for a second central midpoint space summation.