Developing a Saturation Height Function (SHF) for the classified Hydraulic Flow Unit, a case study from the Middle Miocene Carbonate reservoir in the Song Hong Basin, Vietnam

Tóm tắt

The Middle Miocene carbonate is the main gas bearing reservoir in the
southern part ofthe Song Hong basin. Carbonate reservoirs present challenges
for engineers and geologists to characterize because of their complexity due to
depositional and diagenetic processes. The log based calculated water
saturation Sw for this complex carbonate reservoir bears a lot of uncertainties
due to its heterogeneity that strongly affects to m and n values in the water
saturation equation. As the calculated Sw strongly affects the Hydrocarbon
Initially In Place (HIIP) estimation, the production performance prediction,etc.,
the alternative method using the Saturation Height Function (SHF) based on
the capillary pressure was introduced. The SHF building process uses the
combination of the result of HFU classification and permeability prediction
given by machine learning methods, which have become a very useful tool for
complex reservoir characterization such as carbonate reservoir for decades.
Our obtained results allowed us to subdivide the carbonate reservoir into 5
Hydraulic Flow Unit (HFU) by using unsupervised machine learning methods,
and then the capillary pressure (Pc) curves were classified and a proper
saturation-height function using Skelt Harrison equation was assigned to
individual HFU after testing with common SHF equations.The HFU number for
each individual point was predicted based on the log data measured along the
borehole using the supervised machine learning techniques while the Sw was
calculated using the chosen SHF model and the FWL defined on log curves and
pressure data from RCI measurement. The Sw computed from the SHF model
is reliable and can be used for water saturation estimation for the whole field
for known FWL and predicted HFU numbers