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Intelligent filtering of field data

https://doi.org/10.31660/0445-0108-2024-5-132-147

Abstract

   In the oil and gas industry, the measured parameters during oil and gas production are often affected by noise, which contributes to complex and non-monotonic dynamics. This makes manual analysis and interpretation extremely difficult.

   Therefore, this article aims to develop an algorithm capable of identifying and removing noise (signal changes without a clear cause) in the production parameters of well operation.

   The article examines data smoothing methods, including moving average, exponential smoothing, Kalman filter, Wiener filter, Savitzky-Golay filter, Fourier transform, and wavelet transform. The authors identified advantages and limitations. An alternative approach is proposed, combining machine learning methods with standard data filtering tools. The developed algorithm restores the true dynamics of well performance metrics and filters out and smooths noise related to technical malfunctions. The novelty of the algorithm lies in using an LSTM neural network to extract the trend component from noisy dynamics, taking into account events occurring at the well itself as well as events happening at surrounding wells.

Keywords


2.8.4. Development and operation of oil and gas fields (technical sciences)

About the Authors

R. Y. Ponomarev
Tyumen Petroleum Research Center LLC
Russian Federation

Roman Y. Ponomarev, Manager

Tyumen



A. A. Leshchenko
Tyumen Petroleum Research Center LLC
Russian Federation

Anton A. Leshchenko, Chef Specialist

Tyumen



R. R. Ziazev
Tyumen Petroleum Research Center LLC
Russian Federation

Ramil R. Ziazev, Deputy Head of the Department

Tyumen



M. M. Galiullin
Tyumen Petroleum Research Center LLC
Russian Federation

Marat M. Galiullin, Director of Field Development of Khanty-Mansiysk Autonomous Okrug

Tyumen



R. R. Migmanov
Tyumen Petroleum Research Center LLC
Russian Federation

Ruslan R. Migmanov, Chef Specialist

Tyumen



M. I. Ivlev
Tyumen Petroleum Research Center LLC
Russian Federation

Mikhail I. Ivlev, Chef Specialist

Tyumen



References

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Review

For citations:


Ponomarev R.Y., Leshchenko A.A., Ziazev R.R., Galiullin M.M., Migmanov R.R., Ivlev M.I. Intelligent filtering of field data. Oil and Gas Studies. 2024;(5):132-147. (In Russ.) https://doi.org/10.31660/0445-0108-2024-5-132-147

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ISSN 0445-0108 (Print)