The Mathematical Approach to the Identification of Trouble-Free Functioning of Mining Facilities

Author:

Abu-Abed Fares

Abstract

Modern drilling rigs are complexes of high-tech equipment operated in difficult climatic and technological conditions, characterized by sudden spasmodic changes in the process of drilling a well, which contributes to increased wear of drilling components and increases the likelihood of pre-emergency and emergency situations. Drilling equipment has a wide range of characteristics and technological parameters, the values of which are available during drilling due to the use of modern software and hardware systems for processing geological and technological information. In order to single out the most frequent pre-emergency situations in practice and to preliminarily determine the set of signs necessary for their recognition, a corresponding analysis of the complications arising during well drilling has been carried out.

Publisher

EDP Sciences

Reference21 articles.

1. Drilling Rig Operation Mode Recognition by an Artificial Neuronet

2. Duda R.O., Hart P.E., Stork D.G., Pattern Classification (Wiley, New York, 2001)

3. Gallant S.I., Neural Network Learning and Expert Systems (MIT Press, Boston, 1993)

4. Rotary Foundation Drilling Rig Safety (OAFS, Paris, 2016)

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