2018_EJRNL_PP_FOROOGH_FARROKHNIA_1.pdf
Terbatas  
» Gedung UPT Perpustakaan
Terbatas  
» Gedung UPT Perpustakaan
Accurate detection of geo-structures in automatic geological interpretation of seismic data is a challenging task
especially in complex media. Solution to this problemgoes through integration of advanced seismic pattern recognition
methods, image analysis and image classification strategies, applied on seismic image obtained by appropriate
seismic imaging method. Accuracy of these approaches mostly depends on the quality of seismic
attributes used for subsequent image analysis, seismic data classification and seismic pattern recognition. In
this study, we initially analyze the effect of using the common reflection surface (CRS) method on obtaining appropriate
data for attribute analysis, in comparison with the conventional NMO/DMO/Stack imaging method.
Subsequently, we introduce an automatic salt dome detection method fromseismic image based on the intrinsic
geological unit (IGU) concept used in sequential mineral exploration. The IGU consists of areas with indexes or
critical genetic factors (CGF) related to the target of exploration which is defined itself by several critical recognition
criteria (CRC). The CRCs defined as the value of attributes and seismic patterns selected by the interpreter
for salt detection. These CRCs were extracted froma large informative database build only for salt domedetection
from various seismic data and different geological setting. The CRCs were weighted by the interpreter according
to the percentage of success in using selected CRCs for salt identification. Afterwards, probability value of pixels to
be considered as salt was calculated by defining a linear relationship between CRCs. Then, matrix of characteristicswas
defined for CRCs followed by a matrix that shows CRCs score. The final score for each pixel will define the
area of the IGU, or salt dome in seismic image, if they were above a predefined threshold. The presented strategy
was applied on a field data example from Kazakhstan containing a huge salt dome. The proposed strategy could
detect the salt boundary in a fully automatic manner with some befits, such as defining internal reflections and
less human interaction. Application of the proposedmethod on the CRS result showed that it could be considered
as an alternative to the other present automatic salt dome detection and classification approaches. However, the
presented method still requires of using advanced method in scoring and building matrix of characteristics, especially
for salt area detection in seismic image.