Stochastic adaptive learning rate in an identification method: An approach for on-line drilling processes monitoring

On-line drilling processes monitoring is an essential task in enhancing their performances. In oil field industry, dysfunctions that might occur have to be detected at the earliest possible stage in order to preserve drilling efficiency. This paper deals with a methodology for drilling processes monitoring by identifying time varying parameters. The basic idea behind the proposed algorithm is to improve the tracking ability of parameters change by means of an identification method using a new approach to adjust the forgetting factor. The effectiveness of the developed method is highlighted through experimental data obtained from tests campaign.