Establishment and Application of Sand Prediction Model Based on Monte Carlo Method in Offshore Oil-gas Field

Abstract

Accurate assessment of reservoir sanding risk is a key link in the optimization design of offshore oil-gas fields. Based on the Monte Carlo risk probability assessment method, three factors affecting sand production, such as rock Poisson’s ratio, rock density and acoustic time difference, are considered. At the same time, combined with the existing sand production index prediction theory, the probability distribution calculation model of sand risk is established and analyzed. The established prediction model is used to analyze the sand production case. The model was combined with the logging data and seismic data of some layers in Oilfield HZ 32-5 to form the probability distribution map of the sand production index of the J22, J50 and K08 horizons in HZ 32-5 Oilfield. The probability of different sand production levels of the three reservoir rock horizons is predicted, and the corresponding sand control risk prevention and control plan is formulated. Through the on-site application of HZ 32-5 Oilfield, it is proved that the model can more accurately assess the sand production risk in offshore oilfields, and has a good guiding significance for the design of oil-gas well completion schemes.