Abstract
Quantifying the uncertainty in the volumetric estimation of original oil in place (OOIP) is an important process in evaluating the field potential and hence in designing the proper and the most economical subsurface and surface facilities to produce the field reserves. This uncertainty in the OOIP estimate results from uncertainty in reservoir areal extent, net reservoir thickness, porosity, and hydrocarbon saturation. In this work, a methodology is presented to assess the uncertainty in the hydrocarbon saturation estimated from open hole logs using the commonly used empirical and theoretical shaly sand models.
This technique is based on development of water saturation error analysis charts for the commonly used water saturation models (Simandoux, Indonesian, Waxman & Smits, Dual Water, and Effective Medium) due to the uncertainty in the different input parameters to each model separately. Both analytical and numerical error analysis techniques were used to develop these charts and hence used as a forward tool to quantify the uncertainty in the hydrocarbon saturation due to the uncertainty in the petrophysical and electrical rock properties.
Fifteen wells with 1300 shaly sand points from Alam Bewab formation, in Western desert of Egypt, were used as our data base in generating these error analysis charts. The uncertainty in input data was assumed from ± 5 to ± 15%. The results showed a significant range of uncertainty in hydrocarbon saturation estimate from ± 0.3% reaching to ± 85% in some models.
General water saturation error analysis charts were developed, for each model, based on the above mentioned database and validated mathematically. These charts can be easily used to predict the uncertainty in hydrocarbon saturation estimate due to uncertainty in the input data. In addition, it can be considered as a useful screening tool to select the best saturation model to be used depending on the input data uncertainty.
