Exploring the seismic expression of fault zones in 3D seismic volumes

D. Iacopini, R. W. H. Butler, S. Purves, N. McArdle, N. De Freslon

Research output: Contribution to journalArticle

20 Citations (Scopus)
6 Downloads (Pure)

Abstract

Mapping and understanding distributed deformation is a major challenge for the structural interpretation of seismic data. However, volumes of seismic signal disturbance with low signal/noise ratio are systematically observed within 3D seismic datasets around fault systems. These seismic disturbance zones (SDZ) are commonly characterized by complex perturbations of the signal and occur at the sub-seismic (10 s m) to seismic scale (100 s m). They may store important information on deformation distributed around those larger scale structures that may be readily interpreted in conventional amplitude displays of seismic data. We introduce a method to detect fault-related disturbance zones and to discriminate between this and other noise sources such as those associated with the seismic acquisition (footprint noise). Two case studies from the Taranaki basin and deep-water Niger delta are presented. These resolve SDZs using tensor and semblance attributes along with conventional seismic mapping. The tensor attribute is more efficient in tracking volumes containing structural displacements while structurally-oriented semblance coherency is commonly disturbed by small waveform variations around the fault throw. We propose a workflow to map and cross-plot seismic waveform signal properties extracted from the seismic disturbance zone as a tool to investigate the seismic signature and explore seismic facies of a SDZ.
Original languageEnglish
Pages (from-to)54-73
Number of pages20
JournalJournal of Structural Geology
Volume89
Early online date27 May 2016
DOIs
Publication statusPublished - Aug 2016

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fault zone
disturbance
seismic data
footprint
deep water
perturbation
basin
attribute

Keywords

  • Seismic interpretation
  • fault structure
  • rock deformation
  • image processing
  • seismic attributes

Cite this

Exploring the seismic expression of fault zones in 3D seismic volumes. / Iacopini, D.; Butler, R. W. H.; Purves, S.; McArdle, N.; De Freslon, N.

In: Journal of Structural Geology, Vol. 89, 08.2016, p. 54-73.

Research output: Contribution to journalArticle

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abstract = "Mapping and understanding distributed deformation is a major challenge for the structural interpretation of seismic data. However, volumes of seismic signal disturbance with low signal/noise ratio are systematically observed within 3D seismic datasets around fault systems. These seismic disturbance zones (SDZ) are commonly characterized by complex perturbations of the signal and occur at the sub-seismic (10 s m) to seismic scale (100 s m). They may store important information on deformation distributed around those larger scale structures that may be readily interpreted in conventional amplitude displays of seismic data. We introduce a method to detect fault-related disturbance zones and to discriminate between this and other noise sources such as those associated with the seismic acquisition (footprint noise). Two case studies from the Taranaki basin and deep-water Niger delta are presented. These resolve SDZs using tensor and semblance attributes along with conventional seismic mapping. The tensor attribute is more efficient in tracking volumes containing structural displacements while structurally-oriented semblance coherency is commonly disturbed by small waveform variations around the fault throw. We propose a workflow to map and cross-plot seismic waveform signal properties extracted from the seismic disturbance zone as a tool to investigate the seismic signature and explore seismic facies of a SDZ.",
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note = "Acknowledgments The seismic interpretation and image processing has been run in the SeisLab facilty at the University of Aberdeen (sponsored by BG, BP and Chevron) Seismic imaging analysis was performed in GeoTeric (ffA), and Mathematica (Wolfram research). Interpretation of seismic amplitudes was performed Petrel 2014 (Schlumberger). We thank Gaynor Paton (Geoteric) for in depth discussion on the facies analysis methodology and significant suggestions to improve the current paper. We thank the New Zealand government (Petroleum and Minerals ministry) and CGG for sharing the seismic dataset utilized in this research paper. Seismic images used here are available through the Virtual Seismic Atlas (www.seismicatlas.org). Nestor Cardozo and an anonymous reviewer are thanked for their constructive comments and suggestions that strongly improved the quality and organization of this paper.",
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AU - De Freslon, N.

N1 - Acknowledgments The seismic interpretation and image processing has been run in the SeisLab facilty at the University of Aberdeen (sponsored by BG, BP and Chevron) Seismic imaging analysis was performed in GeoTeric (ffA), and Mathematica (Wolfram research). Interpretation of seismic amplitudes was performed Petrel 2014 (Schlumberger). We thank Gaynor Paton (Geoteric) for in depth discussion on the facies analysis methodology and significant suggestions to improve the current paper. We thank the New Zealand government (Petroleum and Minerals ministry) and CGG for sharing the seismic dataset utilized in this research paper. Seismic images used here are available through the Virtual Seismic Atlas (www.seismicatlas.org). Nestor Cardozo and an anonymous reviewer are thanked for their constructive comments and suggestions that strongly improved the quality and organization of this paper.

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N2 - Mapping and understanding distributed deformation is a major challenge for the structural interpretation of seismic data. However, volumes of seismic signal disturbance with low signal/noise ratio are systematically observed within 3D seismic datasets around fault systems. These seismic disturbance zones (SDZ) are commonly characterized by complex perturbations of the signal and occur at the sub-seismic (10 s m) to seismic scale (100 s m). They may store important information on deformation distributed around those larger scale structures that may be readily interpreted in conventional amplitude displays of seismic data. We introduce a method to detect fault-related disturbance zones and to discriminate between this and other noise sources such as those associated with the seismic acquisition (footprint noise). Two case studies from the Taranaki basin and deep-water Niger delta are presented. These resolve SDZs using tensor and semblance attributes along with conventional seismic mapping. The tensor attribute is more efficient in tracking volumes containing structural displacements while structurally-oriented semblance coherency is commonly disturbed by small waveform variations around the fault throw. We propose a workflow to map and cross-plot seismic waveform signal properties extracted from the seismic disturbance zone as a tool to investigate the seismic signature and explore seismic facies of a SDZ.

AB - Mapping and understanding distributed deformation is a major challenge for the structural interpretation of seismic data. However, volumes of seismic signal disturbance with low signal/noise ratio are systematically observed within 3D seismic datasets around fault systems. These seismic disturbance zones (SDZ) are commonly characterized by complex perturbations of the signal and occur at the sub-seismic (10 s m) to seismic scale (100 s m). They may store important information on deformation distributed around those larger scale structures that may be readily interpreted in conventional amplitude displays of seismic data. We introduce a method to detect fault-related disturbance zones and to discriminate between this and other noise sources such as those associated with the seismic acquisition (footprint noise). Two case studies from the Taranaki basin and deep-water Niger delta are presented. These resolve SDZs using tensor and semblance attributes along with conventional seismic mapping. The tensor attribute is more efficient in tracking volumes containing structural displacements while structurally-oriented semblance coherency is commonly disturbed by small waveform variations around the fault throw. We propose a workflow to map and cross-plot seismic waveform signal properties extracted from the seismic disturbance zone as a tool to investigate the seismic signature and explore seismic facies of a SDZ.

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