Reserves Estimation from 3D CSEM Inversion for Prospect Risk Analysis

Net rock volume is the main uncertainty affecting the evaluation of recoverable reserves for prospect risk analysis. We present a Monte Carlo method for estimating a net rock volume probability distribution from an anisotropic 3D CSEM inversion result. Given a CSEM favourable exploration setting, the method can significantly reduce the uncertainty in net rock volume, especially for stratigraphic traps. The method relies on the sensitivity of CSEM to the volume of resistive rock and on the transverse resistance equivalence principle for relating the low resolution inversion result to possible reservoir scenarios at the well log scale. We demonstrate the performance of the method using unconstrained inversion results from a full-azimuth 3D CSEM survey over a known oil field. No prior information in terms of well data or field geometry was assumed to simulate an exploration case. The uncertainty associated with the resulting net rock volume probability distribution as measured by the P10/P90 ratio is less than 6, which is considered low by common industry practice. The actual net rock volume defined by the reservoir top and the oil-water contact coincides with the 60th percentile of the distribution, i.e. the predicted range of possible net rock volumes is very reasonable.