Abstract:
The agenda of this dissertation is to draw a comparison between the reservoir
properties generated using conventional petrophysics and neural networks. Based on
the geographical location, the study area lies in Khairpur, Sindh Province, Pakistan.
Stratigraphic cum structural traps are found in this area. Wireline logs and a 3D seismic
cube has been used to conduct this research. Target horizon is sand of C Interval of
Lower Goru Formation. Probabilistic Neural Network (PNN) and Multilayer Feed
Forward Network (MLFN) has been used to estimate porosities along with
conventional petrophysical analysis. Results generated by both the methods are similar.
However, PNN produces more reliable results whereas the MLFN overestimates values
at some points. Average hydrocarbon saturation within the wells lies in between 50-
70%. Effective porosity ranges between 4-11% which is ideal in the case of sandstones.
