Mathematical Modeling of Cycles to Failure for Submersible Technical Systems in the Oil Industry

Abstract

The state and operation quality of sets of submersible electrical equipment (SEE) at oil wells as a complex engineering system depends on the fault-free and reliable operation of downhole equipment components. Oil production SEE, especially submersible electric motors (SEM) are subjected to various external factors and impacts and they are used in various operating modes. To obtain the data on the state of SEE, we used statistics for the failures during operation. This valid method for the analysis of the conditions of the engineering facilities in the industry is, in most cases, the only suitable one for the mathematic functional and quantitative description of reliability, including the SEE cycles to failure parameter. We collected and analyzed the data on technological failures at oil production facilities and established a database for relevant statistics on the use of SEE (for 2014-2019). We present the results of the statistical analysis for the correct representation of the current conditions of the SEE (including SEM). We used them to produce a systematized assessment of the current state of SEM using smart analysis and probabilistic statistical modeling. We identified and ranked the factors resulting in technological failures, formulated a set of technical and organizational actions to minimize them, and improve the reliability and operation readiness of the SEE.