NDLI: Geostatistical Simulation of Acoustic Log Data for Seismic Depth Conversion

Content Provider	Springer Nature Link
Author	Koppe, Vanessa Cerqueira Costa, João Felipe Coimbra Leite Koppe, Jair Carlos Gambin, Fernando Fallon, Gary Davies, Nick
Copyright Year	2007
Abstract	Seismic reflection methods measure the time a seismic wave takes to travel through the ground, from the user defined source to a series of signal monitoring sensors known as geophones. The measured times need to be depth converted to allow for integration with other geological data. In order to convert from time to depth, an estimate of the rock volume velocity field must be made. The velocity field estimate can be made by assignment of velocity estimates to a geological model independent of the seismic processing. This article presents the results of using the acoustic geophysical log data extrapolated via sequential Gaussian simulation to derive the velocity field. The uncertainties associated with the velocity estimates were significant and provided the means to assess confidence limits for the actual depth determination. The technique is assessed by application to a major coal deposit, approximately 2.1 m thick and 210 m deep. Considering only the uncertainty associated with estimating the velocity field, half of the confidence interval values showed approximately 1 m of uncertainty in depth. The application of sequential Gaussian simulation to model the 3D distribution of acoustic velocity can be extended to other geophysical log parameters or derived estimates.
Starting Page	293
Ending Page	303
Page Count	11
File Format	PDF
ISSN	15207439
Journal	Natural Resources Research
Volume Number	16
Issue Number	4
e-ISSN	15738981
Language	English
Publisher	Springer US
Publisher Date	2007-11-08
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Geostatistic acoustic modeling coal seam Hydrogeology Sedimentology Economic Geology Math. Applications in Geosciences
Content Type	Text
Resource Type	Article
Subject	Environmental Science

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