PREDICTION OF GEOMECHANICAL PROPERTIES FROM SEISMIC ATTRIBUTES AND WELL LOGS DATA ANALYSIS USING ARTIFICIAL NEURAL NETWORK IN F3-BLOCK OF THE NORTH SEA BASIN, OFFSHORE NETHERLANDS

Abstract

Summary: This research aims to integrating seismic attributes and well data using supervised Artificial Neural Networks to identify Geomechanical Properties throughout F3-Block of the North Sea basin, Netherlands. This typically helps wellbore stability, drilling, and hydraulics fracturing. During the development, the engineers struggle to optimize drilling periods, reduce uncertainties and production costs, and make the best optimization of the use of available data. The verification analysis showed that property prediction achieved good results in Young’s modulus and Vp/Vs ratio but was marginal in Poisson’s ratio. Accordingly, results indicated a good potential of the proposed methodology in identifying geomechanical properties with accurate mapping and distribution throughout the pay zones and overlying sedimentary succession.