Seismic Multiple Attenuation Using Structure-Oriented Matching Filters
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Solution Overview
Problem
Conventional seismic processing methods fail to accurately remove multiple events from seismic data, leading to erroneous seismic images and masking of real reflectors, as they assume primary events only, resulting in flawed matching filters that either remove primary energy or leave multiple energy intact, especially in areas of overlap.
Innovation Solution
The method employs structurally-oriented matching filters constrained by structural smoothing to enhance the adaptive subtraction process, improving the subtraction of multiple energy while preserving primary energy, using a predicted multiple model and a tensor field to generate a multiple-attenuated seismic dataset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional seismic processing methods assume data contains only primary events, then processing simplicity is maintained, but multiple events cause masking or blurring of real reflectors and creation of fictitious reflectors
Solution Approach 1:
The patent extracts multiple events from the seismic data by generating a predicted multiple model and using matching filters to separate multiples from primaries. This extraction process removes the harmful multiple events while preserving the primary events, thereby improving seismic image accuracy without significantly complicating the overall processing workflow
Solution Approach 2:
The patent performs preliminary multiple prediction and filter estimation before the main seismic processing. By generating the predicted multiple model and determining matching filters in advance, the method prepares the data for accurate multiple removal, improving reliability while maintaining processing efficiency through pre-computation
2Productivity
If multiple events are not removed from seismic data, then processing workflow remains simple, but fictitious reflectors appear and real reflectors are masked in the seismic image
Solution Approach 1:
The patent uses an iterative feedback process where matching filters are estimated and applied to attenuate multiples, then the results are evaluated and filters are refined. This feedback loop continuously improves multiple attenuation while preserving primary events, maintaining processing efficiency through automated iteration while preventing information loss
Solution Approach 2:
The patent introduces matching filters as an intermediary element between the predicted multiple model and the actual multiple removal process. These filters act as a mediator that adapts the predicted multiples to match the actual multiples in the data, enabling accurate multiple attenuation while preserving primary event information
Data Source
AI summary
A system and methods are disclosed. The method includes obtaining a seismic dataset including a plurality of recorded multiple events, generating a predicted multiple model using a multiple prediction method and the seismic dataset, and estimating a set of initial matching filters using a matching method, to match the plurality of estimated and recorded multiple events. The method further includes generating a tensor field based on the predicted multiple model, determining a set of structure-oriented matching filters based on the set of initial matching filters and the tensor field, generating a filtered multiple model based on the predicted multiple model and the set of structure-oriented matching filters, and generating a multiple-attenuated seismic dataset based on the filtered multiple model and the seismic dataset, forming a seismic image based, at least in part, on the multiple-attenuated seismic dataset, and determining a location of a hydrocarbon reservoir based on the seismic image.