Prediction of sand production onset in petroleum reservoirs using a reliable classification approach

Controlling sand production in the petroleum industry has been a long-standing problem for more than 70 years. To provide technical support for sand control strategy, it is necessary to predict the conditions at which sanding occurs. To this end, for the first time, least square support machine (LSSVM) classification approach, as a novel technique, is applied to identify the conditions under which sand production occurs. The model presented in this communication takes into account different parameters that may play a role in sanding. The performance of proposed LSSVM model is examined using field data reported in open literature.It is shown that the developed model can accurately predict the sand production in a real field. The results of this study indicates that implementation of LSSVM modeling can effectively help completion designers to make an on time sand control plan with least deterioration of production.