A stochastic model for drilling optimization

Drilling optimization problems in oilfields are usually formulated and solved by using deterministic mathematical models, in which uncertain (indeterminate) factors or random issues are not taken into consideration. However, it has been widely experienced that random factors (such as those from soil layers, drill bits, and surface equipment) greatly affect the drilling performance. This paper introduces a new stochastic model for describing such random effects. This model, when used to optimization design, is more practical and provides a better characterization for real oilfield situations as compared with other deterministic models, and has been demonstrated to be more efficient in solving real design problems of drilling optimizations.