Prevention and elimination of complications that occur during production drilling

2018

Today complications during drilling and operation of oil and gas wells are unavoidable. Most of them are the result of violation of technological discipline (technology), some are due to insufficient knowledge of geological and physical conditions (especially in exploratory drilling), a lack of understanding of the causes of the phenomena preceding the complication. Sometimes performers in performing complex technological operations go to the so-called “justified” risk, as a result of which complications and accidents occur. It should be taken into account that the failure of the well even for a short time - the loss of oil and gas production. Therefore, the development of modern methods for their detection, prevention (prevention) and methods to combat their consequences is an urgent task.

Section: Resultsmentioning

confidence: 99%

“…After learning the neural network, the recognition error was 4.89% and 7.26%. Thus, for all three pre-emergency situations considered, the average recognition error was about 6% [12].…”

Section: Nomentioning

confidence: 88%

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Development of Tools for the Analysis of Pre-Emergency Situations on the Drilling Rig Based on Neural Network Technologies

2018

“…The main types of emergency situations are given in [20]. For the study, real data of geological technology information containing information on the occurrence of the following pre-emergency situations were selected:…”

Section: Definition Of a Set Of Signs For Recognition Of Emergency Situationsmentioning

confidence: 99%

“…where: QN -is the value of the criterion for choosing a feature in step N; TN -is the set of already selected features in step N; Ki C -is the correlation coefficient of attribute i with the target attribute; Kij -is the value of the correlation coefficient of attribute i with attribute j. The results of the algorithm for the pre-emergency situation "gas and oil occurrences" are given in [20]…”

Section: Definition Of a Set Of Signs For Recognition Of Emergency Situationsmentioning

confidence: 99%

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

2020

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.

Investigation of the Effectiveness of the Method for Recognizing Pre-Emergency Situations at Mining Facilities

2020

In previous reports, an analysis of the basic mathematical methods used to solve the pattern recognition problem was carried out. The inappropriateness of applying the Bayesian classification and cluster analysis to solve the problem of recognizing pre-emergency situations in the process of drilling a well is shown. As a mathematical apparatus for solving the problem of determining the current state of an object of research by a given set of features, a pattern recognition method based on an artificial neural network is selected. In this paper, an analysis is made of existing approaches to improving the quality of education aimed at improving the efficiency of its functioning. The results obtained in this paper will improve the quality of work of the previously developed modified algorithm for training the pre-emergency classifier based on the back propagation method, which differs from the classical one by the procedure for finding the global minimum of the error function, and its software implementation has been implemented. The work is an integral part of previously published developments presented in the materials of articles in 2-nd, 3-rd and 4-th International innovative mining symposiums (2017-2019).