Uncertainty assessment of onset sand prediction model for reservoir applications

Abstract

Modeling physical systems in engineering always comes with uncertainties in terms of the model’s input parameters. These uncertainties are also present in modeling the onset of sand production, even though considerable effort may be required in incorporating uncertainties into the process of modeling, because getting it right will definitely provide important knowledge about the input parameters for predicting the onset of sanding which provides useful hints that inform apt decision-making for sand control. In this study, a Monte Carlo simulation of some parametric input variables alongside the incorporation of the Hoek–Brown material constants was investigated using a predictive model for sand production anchored on Hoek–Brown failure criterion, so as to rank some key input uncertainties in order of the effect their magnitudinal disparities on the model output. The key inputs in the model are reservoir pressure, rock strength (uniaxial compressive strength, UCS), minimum horizontal stress, Poisson’s ratio and Hoek–Brown material constants M and S. Different diagnostic Tornado and spider plots were generated and interpreted for two wells and it was observed that the predicted well pressure is most sensitive to rock strength and generally has an inverse relationship with the rock strength. The parametric study on Hoek–Brown material constants shows that higher values of M and S correspond to lower minimum well pressure at which sanding is expected. The model is a useful tool for a quick assessment of the onset of sanding in reservoir rocks and can also be used to evaluate the effect of different rock mechanical properties.

Keywords

• sanding
• failure criterion
• uncertainty assessment
• hoek–brown