Akademik Veri Yönetim Sistemi
Türkiye 21. Uluslararası Petrol ve Doğal Gaz Kongre ve Sergisi, Ankara, Türkiye, 27 - 29 Eylül 2023, ss.1-1223
In this study; using the post-stack seismic data (up
to 1900 m) and well log (four wells) within the Pliocene aged units of the
North Sea Dutch Sector area; the combination of neural network and genetic
algorithm methods which is called as a genetic inversion (GI) method was used
as the main seismic attribute from the volume attributes of the Schlumberger
patented Petrel software. This attribute is more effective than classical
inversion methods in terms of both data input and run time for the process.
Acoustic impedance log created for all wells in study
area, then the correlation coefficient between acoustic impedance log and
effective porosity logs checked. The results show that there is a relationship
between acoustic impedance and effective porosity. Therefore, acoustic
impedance cube created using genetic inversion. Genetic inverted acoustic
impedance cube then used an input to create genetic inverted effective porosity
cube. The result shows correlation = 0.8478655 and
F02-01
(Correlation = 0.916886, Samples = 144)
F03-02
(Correlation = 0.877023, Samples = 112)
F06-01
(Correlation = 0.7763297, Samples = 147)
F03-04
(Correlation = 0.7061655, Samples = 119)
Further, seismic attributes such as; Root Mean Square
amplitude (RMS) (high amplitude values), Relative Acoustic Impedance (RAI), Instantaneous
Frequency (IF), Envelope and Sweetness were applied to identify possible
prospective areas. High amplitude values from RMS, polarity change of RAI, low
values of IF, high values of Envelope and Sweetness represents a good reservoir
quality.
As a result, applied seismic attributes and genetic
inversion combination can be used to delineate possible good reservoir quality
areas that can be considered as a new prospect.
Keywords; Genetic Inversion, Seismic Attributes