Relationship between shear wave azimuthal anisotropy, sand-shale content and depth in the Exmouth Sub-Basin, Western Australia

Gavin, Lisa J.; Lumley, David

doi:10.1071/aseg2015ab080

Cited by 1 publication

(10 citation statements)

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“…Amplitude variation with offset (AVO) is often used as a direct hydrocarbon indicator (DHI); however SAA can have a significant impact on AVO gradients [Rüger, 1998]. Without properly taking SAA into account, AVO analysis can lead to incorrect interpretations of fluid content [Foster et al, 2010] and poor AVO well ties [Gavin and Lumley, 2015]. Gavin and Lumley [2015] showed the strong potential of using SAA as a predictor of clean sandstones; however, at that time it was unknown how widespread the SAA-Vshale trends held beyond their single fault block example (~100 km 2 ).…”

Section: Seismic Azimuthal Anisotropy In Sandstonesmentioning

confidence: 99%

“…Without properly taking SAA into account, AVO analysis can lead to incorrect interpretations of fluid content [Foster et al, 2010] and poor AVO well ties [Gavin and Lumley, 2015]. Gavin and Lumley [2015] showed the strong potential of using SAA as a predictor of clean sandstones; however, at that time it was unknown how widespread the SAA-Vshale trends held beyond their single fault block example (~100 km 2 ). This research shows that their model may be valid across many basins over the entire NW Shelf.…”

Section: Seismic Azimuthal Anisotropy In Sandstonesmentioning

confidence: 99%

“…[] observed SAA in vertical seismic profiling (VSP) data where the magnitudes were comparable to those observed in dipole shear log data down the same well. Gavin and Lumley [] show that the S wave SAA derived from dipole shear logs was more prominent in sand‐dominated sediments—reaching up to 15% shear wave velocity anisotropy—and was not observed in shale‐dominated sediments. They demonstrate that SAA can be accurately predicted using shale volume ( V sh ) log data; where V sh is the volumetric ratio of shale compared to sand, derived from gamma ray (GR) log data (sensitive to organic material).…”

Section: Geological Settingmentioning

confidence: 99%

“…Anecdotal reports suggest that SAA is not observable everywhere on the NSW in exploration data. Where it is observed, it appears to be caused by anomalous horizontal stress conditions, due to the similar orientation of observed ϕ and overall regional maximum horizontal stress direction ( σ H ) [ Pevzner et al ., ; Gavin and Lumley , ]. However, no published studies have examined this hypothesis in great detail.…”

Section: Introductionmentioning

confidence: 99%

“…However, within the last two decades exploration geophysicists have recognized the potential to use the Thomsen parameters and ϕ as additional information to improve geological interpretations [Tsvankin et al, 2010]. For example, SAA has been used for fracture strike and density estimations [Hall and Kendall, 2003;de Figueiredo et al, 2012] and predicting lithology type [Gavin and Lumley, 2015]. However, there are no published examples that we are aware of in which ϕ has been derived from numerous exploration data sets and mapped over multiple basins to examine regional azimuthal anisotropy trends.…”

Section: Introductionmentioning

confidence: 99%

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Stress‐induced seismic azimuthal anisotropy in the upper crust across the North West Shelf, Australia

Gavin

Lumley

2016

JGR Solid Earth

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Seismic azimuthal anisotropy (SAA) is observed in many areas of the Earth, and fast polarized directions (ϕ) have been mapped using earthquake surface waves and teleseismic S wave splitting over large regional and tectonic scales. Higher‐resolution petroleum exploration data, including 3‐D seismic surveys and dipole shear logs, often exhibit azimuthal anisotropy; however, we are unaware of any published studies mapping SAA from exploration‐scale data to study large‐scale regional and tectonic SAA trends. The physical mechanisms causing SAA in earthquake data are a subject of great interest; comparing regional ϕ trends to the higher‐resolution exploration trends may help understand these mechanisms. We present a SAA analysis using seismic exploration data across the North West Shelf (NWS) of Australia. We map the fast polarization directions ϕ from 34 dipole shear logs and two 3‐D seismic surveys and compare them to in situ maximum horizontal stress orientations (σH). Our results show that the ϕ and σH trends correlate across a geographical area spanning almost 2000 km and are similar to published results in the region from earthquake seismology. These results suggest that differential horizontal stress is the likely mechanism causing SAA at a wide range of spatial scales on the NWS of Australia. We also show that SAA is not observed at exploration scales in some areas of the NWS and propose a lithology‐dependent stress sensitivity model in which SAA is strongest in clean, unconsolidated quartz‐dominated sandstones and weaker or nonexistent in well‐consolidated cemented rocks and shale‐dominated sediments.

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