Porosity prediction based on conventional and geostatistical image computation, Lower to Middle Eocene siliciclastics in the Tuz Go?l? Basin (Central Anatolia, Turkey)


Kirkayak Y., AYYILDIZ T.

MARINE AND PETROLEUM GEOLOGY, cilt.143, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 143
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1016/j.marpetgeo.2022.105821
  • Dergi Adı: MARINE AND PETROLEUM GEOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, Communication Abstracts, INSPEC, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: Geostatistical image analysis, Geostatistical methods, Empirical image - porosity analysis method, Theoretical logic, Tuz G'o'lii Basin, GRAIN-SIZE DISTRIBUTION, ROCK PROPERTIES, FORE-ARC, PERMEABILITY, EVOLUTION, RESERVOIR, SANDSTONE, CLASSIFICATION, STATISTICS, MODELS
  • Ankara Üniversitesi Adresli: Evet

Özet

The study area is located at the east of Tuz Go??lii Basin, one of the sedimentary basins in the Central Anatolia basins between S Kochisar and Karapinar town. The main subject of study is based on the Boyali Formation consisting of braided river deltas and submarine fan deposits with shelf carbonates blocks of the Lower to Middle Eocene. Laboratory analysis showed that porosity and permeability values are between % 1.40-19.40 (average % 9.15) and 0.01-43.95 mD (average 5.07 mD), respectively. The conventional method is compared with the geostatistical image analysis method by rock plug samples parallel to layering for porosity prediction. These samples were saturated with blue resin and made thin sections. The boundaries of the blue areas (mean pores) were lined for pore volume calculation to create solid objects. A proposed empirical mathematical method, geostatistical based, was used to gain porosity values to converge to the laboratory values. Also, in the scope of this study, an architectural, mathematical logic called geostatistical first-order logic architecture (GFOLA) was generated. The geostatistical based programme "GeoST Porosity v.1.0" has been developed for numerical analysis. The empirical approach has been used to transform the areal measurement into volumetric measurement, eliminate the conditions that could not be measured in the 3rd dimension, and positively affects the porosity approach ratio, which is the ratio of empirical to laboratory porosity. In the empirical approach, the porosity is the function of grain size (x), sorting (y) and skewness (z) ??? = g(x,y,z). To obtain the deviation from the ???ideal condition (??)???, the yielded result has been modelled as an attenuation relation ??eGf ?? which is a function of grain texture factor (Gf). A correlation graph of the grain texture factor and porosity approach ratio obtained by the empirical approach has been determined to be applied to siliciclastics. For practical purposes, a geostatistical modelling study proved that an empirical approach could be proposed as a better method instead of conventional laboratory porosity measurement.