Adaptive delta compression algorithm with a double edge for electric submersible pumps monitoring systems

UDK: 681.518:622:276.53

DOI: 10.24887/0028-2448-2025-12-133-139

Key words: well pad, electric submersible pump (ESP), telemetry system, data compression, sporadic transmission

Authors: A.N. Krasnov (Ufa State Petroleum Technological University, RF, Ufa); M.Yu. Prakhova (Ufa State Petroleum Technological University, RF, Ufa); Yu.V. Kalashnik (Ufa State Petroleum Technological University, RF, Ufa); V.A. Kupavykh (Ufa State Petroleum Technological University, RF, Ufa); S.V. Polyanskiy (Gazprom Neft Companу Group, RF, Saint Petersburg); D.V. Usikov (NEDRA LLC, RF, Saint Petersburg); V.E. Chernyshov (Association «Digital technologies in industry», RF, Saint Petersburg; Institute of Problems of Mechanical Engineering of the RAS, RF, Saint Petersburg); V.D. Gulyaev (Research and Education Center «Gazprom Neft-UGNTU», RF, Ufa); A.V. Ryzhikov (Isource JSC, RF, Moscow)

The article covers the issue of implementing adaptive delta compression algorithm with a double edge for electric submersible pumps (ESP) monitoring systems. Nowadays in the upstream oil and gas sector, as a consequence of rapid digitalization, there is a sharp increase in the volume of data transmitted both at production sites and between fields and higher-level systems. Since any communications link both wired and wireless has inherent limits on data rate and throughput, various data-compression algorithms are used to optimize traffic. The design of such algorithms is determined by many factors, in particular the physical nature and process criticality of the transmitted parameters. This paper proposes an adaptive dual-threshold delta-compression algorithm for ESP monitoring systems that partitions the incoming data stream into values that do and do not require transmission, depending on the magnitude of change relative to the previous value. The thresholds themselves are defined by the metrological characteristics of the sensors and the specifics of the technological process. As a result of the study it is shown that data transmission can be approximately 80 % more efficient than with the use of other algorithms. Furthermore, the proposed algorithm demonstrates high fault tolerance to data loss in the communication channel.

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