Seismic Phase Control Using Deterministic Shaping Filters
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Solution Overview
Problem
Existing seismic data processing methods assume a minimum phase spectrum, leading to errors when the data deviates from this assumption, particularly in predictive deconvolution and receiver consistent deconvolution, and fail to account for phase distortions caused by preceding processing steps.
Innovation Solution
A deterministic method that uses the measured or calculated source signature wavelet to construct shaping filters to convert seismic data to minimum phase and then to zero phase, ensuring phase consistency with processing assumptions and improving data interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If predictive deconvolution is applied to seismic data, then periodic multiples are attenuated and wavelet compression is achieved, but phase specification errors are introduced when data deviates from minimum phase assumption
Solution Approach 1:
The patent applies preliminary phase correction to convert the seismic wavelet to minimum phase before applying predictive deconvolution. This preliminary action ensures that the data meets the phase assumption required by the deconvolution algorithm, preventing phase specification errors while maintaining processing accuracy.
Solution Approach 2:
The patent changes the phase parameter of the seismic wavelet from its original phase to minimum phase using phase correction filters. This parameter transformation aligns the data with the assumptions of subsequent processing algorithms, resolving the contradiction between processing accuracy and phase specification accuracy.
2Manufacturing precision
If receiver consistent deconvolution is applied to correct wavelet shape, then receiver-related effects are corrected, but phase errors remain when data is not minimum phase
Solution Approach 1:
The patent performs preliminary phase correction to convert the wavelet to minimum phase before applying receiver consistent deconvolution. This ensures that the subsequent deconvolution operates on data that satisfies its phase assumptions, achieving accurate wavelet shape correction without introducing phase errors.
Solution Approach 2:
The patent transforms the phase parameter of the wavelet to minimum phase using phase correction filters before applying receiver consistent deconvolution. This parameter change enables accurate correction of receiver-related effects while maintaining phase accuracy throughout the processing chain.
3Reliability
If phase correction filters are applied to convert data to minimum phase, then processing assumptions are satisfied, but additional processing steps and complexity are introduced
Solution Approach 1:
The patent introduces phase correction filters as intermediary components that bridge the gap between the original seismic data and the minimum phase assumption required by subsequent algorithms. These filters act as mediators that transform the data without requiring fundamental changes to the overall processing architecture.
Solution Approach 2:
The patent changes the phase parameter of the seismic data to minimum phase using deterministic phase correction filters. This parameter transformation enables the data to satisfy processing assumptions while maintaining a relatively simple processing architecture through deterministic rather than statistical methods.
4Measurement precision
If statistical methods are used for phase correction, then phase errors are reduced, but deterministic accuracy and processing efficiency are compromised
Solution Approach 1:
The patent replaces statistical methods with deterministic methods for phase correction. Instead of using statistical inferences from seismic data, the invention uses deterministic phase correction filters based on the actual source wavelet signature, achieving both high accuracy and processing efficiency.
Solution Approach 2:
The patent uses the actual source wavelet signature (which is already known or can be measured) to create phase correction filters. This self-service approach leverages existing information about the source to correct phase errors directly, avoiding the need for complex statistical analysis and improving processing efficiency.
Data Source
AI summary
Method for controlling the phase spectrum of seismic data to match assumptions inherent in subsequent processing steps. The source signature, after processing with the same initial processing steps used on the data, is used to design a phase control filter that shapes the seismic data to have a minimum phase spectrum or whatever other phase spectrum the subsequent processing algorithms may assume. The processed data is then filtered with a second phase-control filter, also designed using the parallel-processed signature, to shape the data to zero phase or whatever other phase may be desired for interpretation of the data.