News Update on 3D Seismic Research: Dec – 2019

Volume texture extraction for 3D seismic visualization and interpretation

Visual inspection of poststack seismic picture styles is powerful in spotting huge‐scale seismic features; however, it isn’t effective in extracting quantitative information to visualize, detect, and map seismic functions in an automated and objective way. Although conventional seismic attributes have notably more advantageous interpreters’ ability to quantify seismic visualization and interpretation, only a few attributes are published to signify both intratrace and intertrace relationships of amplitudes from a 3‐dimensional (3D) attitude. These relationships are essential to the characterization and identity of certain geological capabilities. Here, I present a quantity texture extraction technique to conquer these limitations. In a two‐dimensional (2D) photograph area in which data samples are visualized by way of pixels (photograph factors), a texture has been generally characterized based on a planar texel (textural detail) the use of a gray stage co‐prevalence matrix. [1]

3D seismic technology: the geological ‘Hubble’

The proliferation of 3‐dimensional (3D) seismic generation is one of the most thrilling traits within the Earth Sciences over the past century. 3-D reflection seismic facts provide interpreters with the potential to map systems and stratigraphic capabilities in 3-D detail to a decision of a few tens of metres over heaps of square kilometres. It is a geological ‘Hubble’, whose resolving energy has already yielded some fascinating (and unexpected) insights and could hold to offer a major stimulus for research into geological strategies and products for many decades to return. Academic and other studies institutions have a first-rate function to play inside the use of this facts by way of exploiting the enormous extent of geological facts contained in three-D seismic surveys. This paper critiques some of the current advances in basin evaluation made using the medium of 3D seismic statistics, focusing on the fields of structural and sedimentary geology, fluid–rock interactions and igneous geology. [2]

A review of kinematic indicators from mass-transport complexes using 3D seismic data

Three-dimensional (3-d) seismic mirrored image facts have recently been proven to be an splendid device within the look at of submarine mass-transport complexes (MTCs), from which kinematic indicators can be recognized. Kinematic indicators are geological structures or capabilities which can be analysed to allow the direction, magnitude and mode of transport to be constrained. The numerous indicator sorts had been labeled in line with in which they may generally be discovered in the MTC frame – the headwall domain, translational domain and toe domain. Aspects in their formation, identity the usage of seismic information and their kinematic price are mentioned, and illustrated the use of examples taken from 3-D seismic records from the continental margin of Norway and the Levant Margin, each of that have been inspired with the aid of repetitive huge-scale slope failure inside the current past. [3]

New perspectives on Solid Earth Geology from Seismic Texture to Cooperative Inversion

Seismic and electromagnetic techniques are fundamental to Solid Earth research and subsurface exploration. Acquisition value discount is making dense 3-D software of those methods available to a extensive variety of geo-scientists. However, the assignment of extracting geological meaning stays. We increase the concept of “textural domaining” for 3D seismic reflectivity facts. Dip-recommended seismic texture attributes are mixed with unsupervised learning to generate units of extent rendered photographs observed by way of a seismic texture reference diagram. [4]

A Statistically Driven Spectral Method for Deriving Reservoir Properties Using 3D Seismic Data and Well Log Suites

A statistically driven spectral approach became executed on 3D seismic facts and well logs in ‘’VIC’’ Field within the Niger Delta with the goal of deriving reservoir residences and delineating stratigraphic features the usage of area detection attributes like coherence so that it will have a better and clearer view of subsurface structure of a reservoir c programming language that possesses hydrocarbon the usage of Spectral method. [5]

Reference

[1] Gao, D., 2003. Volume texture extraction for 3D seismic visualization and interpretation. Geophysics, 68(4), (Web Link)

[2] Cartwright, J. and Huuse, M., 2005. 3D seismic technology: the geological ‘Hubble’. Basin Research, 17(1), (Web Link)

[3] Bull, S., Cartwright, J. and Huuse, M., 2009. A review of kinematic indicators from mass-transport complexes using 3D seismic data. Marine and Petroleum Geology, 26(7), (Web Link)

[4] New perspectives on Solid Earth Geology from Seismic Texture to Cooperative Inversion
Cuong Van Anh Le, Brett D. Harris & Andrew M. Pethick
Scientific Reports volume 9, (Web Link)

[5] B. Olaseni, V., S. Onifade, Y., O. Airen, J. and Adeoti, L. (2018) “A Statistically Driven Spectral Method for Deriving Reservoir Properties Using 3D Seismic Data and Well Log Suites”, Asian Journal of Research and Reviews in Physics, 1(1), (Web Link)

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