1887
Volume 50, Issue 4
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

In this study, a linear programming (l-norm) sparse spike inversion (LPSSI) technique is used to estimate acoustic impedance distribution in the subsurface of the Blackfoot Field, Alberta, Canada. The aim of study is to determine high-resolution subsurface rock properties from the low-resolution seismic data and characterise the clastic Glauconitic channel. There are many traditional post-stack seismic inversion techniques available to estimate rock properties from seismic data, but LPSSI is a relatively simple and quick to compute subsurface model that can be used for qualitative as well as quantitative interpretation. The technique is applied in two steps; first, composite traces near to well locations are extracted and inverted for acoustic impedance, and comparison with well log impedance is used to optimise the LPSSI parameters. Analysis of the composite traces indicates that the algorithm has good performance with high correlation (0.97). In the second step, LPSSI is applied to the Blackfoot seismic data to estimate the distribution of acoustic impedance in the subsurface. Analysis of inverted acoustic impedance shows a low impedance anomaly ranging from 6500 to 8500 m/s*g/cc at the 1060–1075 ms time interval, which is characterised as a clastic Glauconitic sand channel. Thereafter, to confirm the sand channel, another important rock property, porosity, is estimated in the inter-well region using multi-attribute analysis. Analysis of the porosity shows the presence of a high porosity (15–22%) zone in the 1060–1075 ms time interval which coincides with the low impedance zone and confirms the presence of the sand channel.

© 2019 Australian Society of Exploration Geophysics
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2019-07-04
2026-01-13

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/content/journals/10.1080/08123985.2019.1606206
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Characterising sand channel from seismic data using linear programming (l1-norm) sparse spike inversion technique: a case study from offshore, Canada
Exploration Geophysics 50, 449 (2019); https://doi.org/10.1080/08123985.2019.1606206
/content/journals/10.1080/08123985.2019.1606206
/content/journals/10.1080/08123985.2019.1606206
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  • Article Type: Research Article
Keyword(s): linear programming; multi-attribute analysis; sand channel; Seismic inversion; sparse spike inversion

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