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Abstract

Summary

Subsurface channels usually contribute to the construction of hydrocarbon reservoirs and its identification may be useful in the planning of wells for field development. Spectral decomposition technique has been widely applied to seismic processing and interpretation. However, the current applications to the channel identification possibly suffer from low resolution, especially for thin bed interpretation. In this paper, we applied a novel time frequency analysis approach called sparse inverse spectral decomposition (spare-ISD) to extract isofrequency attributes and further detect the distribution of channels with a high resolution. The application on a tight sandstone reservoir with an area of 230 km2 in Northwest China exhibits its effectiveness in channel detection. The whole channel distribution with legible details can be clearly identified, and thereby sparse inverse spectral attributes have the potential to further guide the deployment of exploration wells in this region.

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/content/papers/10.3997/2214-4609.201801264
2018-06-11
2024-04-20

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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201801264
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Application of Sparse Inverse Spectral Attributes to Channels Detection
Conference Proceedings 2018, 1 (2018); https://doi.org/10.3997/2214-4609.201801264
/content/papers/10.3997/2214-4609.201801264
/content/papers/10.3997/2214-4609.201801264
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