The use of digital control techniques and statistical analysis to enhance the efficiency of well drilling

UDK: 622.24.05:681.5

DOI: 10.24887/0028-2448-2025-6-40-43

Key words: wells drilling, improving efficiency, digital methods, automated complex, optimization of time costs, increasing transparency, detailing the process of drilling wells and reconstruction of wells by branching

Authors: E.Yu. Pilipets (Rosneft Oil Company, RF, Moscow); R.Ya. Gazimov (Rosneft Oil Company, RF, Moscow); K.R. Davletov (SamaraNIPIneft LLC, RF, Samara); A.S. Zharkenev (SamaraNIPIneft LLC, RF, Samara); E.A. Lunin (SamaraNIPIneft LLC, RF, Samara)

The article discusses methods for improving the efficiency of well drilling and reconstruction using digital monitoring and statistical tools provided by an automated complex of geotechnical study station that does not require human intervention, as well as a module for determining hidden losses used in Rosneft Oil Company. These tools help to eliminate the human element from the creation of accounting documents, recognize and record operations on the wellsite, identify trends by increasing transparency in work, provide high-quality information for all participants of the process, and take over routine registration, compilation, initial analysis of work done, and notification of any discrepancies. The automated complex of geotechnical study station works by monitoring the progress of well construction autonomously using modern software and self-diagnostic equipment. Specialized software enables users to quickly compare actual time spent against standard time; record operations performed, and track deviations in work performance over a specified period. The Hidden Loss Detection module analyzes data from complex of geotechnical study station’s sensors and visualizes each operation using needle diagrams. It calculates the standard duration of each operation for each drilling rig based on the results achieved, regional characteristics, and the type of equipment used. This enables the module to identify potential opportunities to optimize time costs, such as excess and hidden unproductive time.

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