- Tytuł:
- Multiscale evaluation of a thin-bed reservoir
- Autorzy:
- Lis-Śledziona, Anita
- Powiązania:
- https://bibliotekanauki.pl/articles/1841759.pdf
- Data publikacji:
- 2021
- Wydawca:
- Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
- Tematy:
-
thin beds
high resolution well logs prediction
horizontal resistivity
unsupervised neural network
self-organizing maps (SOM)
electrofacies
low resistivity pay - Opis:
- A thin-bed laminated shaly-sand reservoir of the Miocene formation was evaluated using two methods: high resolution microresistivity data from the XRMI tool and conventional well logs. Based on high resolution data, the Earth model of the reservoir was defined in a way that allowed the analyzed interval to be subdivided into thin layers of sandstones, mudstones, and claystones. Theoretical logs of gamma ray, bulk density, horizontal and vertical resistivity were calculated based on the forward modeling method to describe the petrophysical properties of individual beds and calculate the clay volume, porosity, and water saturation. The relationships amongst the contents of minerals were established based on the XRD data from the neighboring wells; hence, the high-resolution lithological model was evaluated. Predicted curves and estimated volumes of minerals were used as an input in multimineral solver and based on the assumed petrophysical model the input data were recalculated, reconstructed and compared with the predicted curves. The volumes of minerals and input curves were adjusted during several runs to minimalize the error between predicted and recalculated variables. Another approach was based on electrofacies modeling using unsupervised self-organizing maps. As an input, conventional well logs were used. Then, the evaluated facies model was used during forward modeling of the effective porosity, horizontal resistivity and water saturation. The obtained results were compared and, finally, the effective thickness of the reservoir was established based on the results from the two methods.
- Źródło:
-
Geology, Geophysics and Environment; 2021, 47, 1; 5-20
2299-8004
2353-0790 - Pojawia się w:
- Geology, Geophysics and Environment
- Dostawca treści:
- Biblioteka Nauki
Artykuł