- Tytuł:
- Digital rock models of Precambrian and Paleozoic tight formations from Poland
- Autorzy:
- Krakowska, P. I.
- Powiązania:
- https://bibliotekanauki.pl/articles/2060584.pdf
- Data publikacji:
- 2017
- Wydawca:
- Państwowy Instytut Geologiczny – Państwowy Instytut Badawczy
- Tematy:
-
digital rock models
Precambrian sedimentary rocks
Paleozoic sedimentary rocks
petrophysical parameters
statistical analysis
petrophysical data - Opis:
- Properties of selected Precambrian and Paleozoic sedimentary clastic rocks were analysed with respect to their reservoir potential. Multidimensional analysis of laboratory results and borehole logging data was used to construct digital models of pre-Mesozoic, deeply buried formations, present as tight, low-porosity and low-permeability rocks. This modern statistical and deterministic approach as applied to laboratory and borehole logging results worked to integrate data at different scales. The results obtained are useful not only in further scientific research but also found a use in industrial application. As a first step, statistical methods, including clustering and separation of homogeneous groups, enabled digital rock model creation on the basis of the results of such laboratory measurements as pycnometry, mercury porosimetry, nuclear magnetic resonance spectroscopy or computed X-ray tomography. Next, the models constructed were applied in borehole logging interpretation to find intervals with similar petrophysical properties within the group and different properties between the groups. This approach allowed implementation of upscaling procedures of laboratory experiments at micro- and nano-scale to borehole logging scale. High correlations were established between the log petrophysical parameters within the digital models. This approach can be used to divide the succession cored into intervals with different petrophysical parameters.
- Źródło:
-
Geological Quarterly; 2017, 61, 4; 896--907
1641-7291 - Pojawia się w:
- Geological Quarterly
- Dostawca treści:
- Biblioteka Nauki