Sage Journals: Discover world-class research

Abstract

Downstream transmission of the drilling-oriented parameters means that the drilling control parameter information at the surface is transmitted to the down-hole drill bit, and the drill bit is controlled to perform the construction according to the predetermined wellbore trajectory. It not only interrupts the normal drilling operation but also transfers the ground information to the underground pulse system in real time. The biggest problem affecting signal processing and signal decoding is noise interferences. Effective signal processing methods can improve the correctness and reliability of the received signal analysis and processing. To this end, a drilling fluid pulse signal processing method based on Kalman filter is proposed. First, according to the relationship between the noise of the drilling pump and the pump impulse, the harmonic frequency of the pump noise and the corresponding amplitude phase are obtained to realize the reconstruction of the pump noise, thereby achieving the removal of the pump noise. For removing the signal after the pump noise, the remaining noise can be treated as additive noise, and then the Kalman filter is used to achieve real-time signal filtering. The experimental results show that the pump noise is the main source of disturbance of the drilling fluid pulse signal. The Kalman filtering method proposed is practical and effective for filtering the drilling fluid pulse signal. The efficient and accurate real-time transmission of information is a key factor in improving drilling safety, reliability, and maximizing drilling cost.

Keywords

Drilling-oriented parameters noise processing noise characteristics

Get full access to this article

View all access options for this article.

References

Ahmadi

Khayatian

and Karimaghaee

, Attitude estimation by divided difference filter in quaternion space, Acta Astronautica 75 (2012), 95–107.

Shao

Yan

Han

Gao

and Wei

, Differential signal extraction for continuous wave mud pulse telemetry, Journal of Petroleum Science and Engineering 148 (2017), 127–130.

Borga

Stoffel

Marchi

Marra

and Jakob

, Hydrogeomorphic response to extreme rainfall in headwater systems: Flash floods and debris flows, Journal of Hydrology 518 (2014), 194–205.

Das

D.M.

Gupta

Srivastava

Vidwans

Ahmad

Shelke

Kale

Ananthapadmanabhan

Sharma

D.K.

and Baghini

M.S.

, A pulse oximeter system, OxiSense, with embedded signal processing using an ultra-low power ASIC designed for testability, Microelectronics Journal 72 (2018), 1–10.

Jarrot

and Jeffryes

, Wideband mud pump noise cancelation method for wellbore telemetry, US (2013).

Karlgaard

C.D.

, Robust state estimation using desensitized divided difference filter, ISA Transactions 52 (2013), 629–637.

Luca

M.B.

Azou

Burel

and Serbanescu

, On exact Kalman filtering of polynomial systems, IEEE Transactions on Circuits and Systems I Regular Papers 53 (2006), 1329–1340.

Mandal

and Song

Y.Q.

, Methods and apparatus for oil sample analysis using J-edit nuclear magnetic resonance, 2018.

Musoff

and Zarchan

, Polynomial Kalman Filters , 2015.

10.

Shi

Zhao

Jing

Zhao

and Gao

, Research on noise reduction of weak signals in grounding reliability testing of aircraft cable shield, Journal of Computational Methods in Sciences and Engineering 15(3) (2015), 405–414.

11.

Chen

Liao

Yang

and Cai

, HEVC and 3D dual-tree discrete wavelet transform based multiple description video coding, Journal of Computational Methods in Sciences and Engineering 16(4) (2016), 955–965.

12.

Song

Liu

Deng

and Zhang

, Super resolution reconstruction of medical image based on adaptive quad-tree decomposition, Journal of Computational Methods in Sciences and Engineering 17(3) (2017), 411–422.

13.

Zhang

Wang

and Wu

, Adaptive dual-sensor noise cancellation method for continuous wave mud pulse telemetry, Journal of Petroleum Science and Engineering 162 (2018), 386–393.

14.

Sarmavuori

and Sarkka

, Fourier-Hermite Kalman Filter, IEEE Transactions on Automatic Control 57 (2012), 1511–1515.

15.

Schindler

Ess

Leibe

and Gool

L.V.

, Automatic detection and tracking of pedestrians from a moving stereo rig, Isprs Journal of Photogrammetry and Remote Sensing 65 (2010), 523–537.

16.

Shi

Brady

Tennent

and Reyes

S.D.

, Digital signal receiver for measurement while drilling system having noise cancellation, EP (2004).

17.

Tang

and Zeng

, Application of digital signal processing tools for the detection of voltage sag/swell, International Journal of Electrical Engineering Education 55(2) (2018), 002072091875483.

18.

Xie

Huang

Chen

and Gong

, Improving defect visibility in square pulse thermography of metallic components using correlation analysis, Mechanical Systems and Signal Processing 103 (2018), 162–173.

19.

Zhang

Song

Yao

and Kos

, A sensor-based wrist pulse signal processing and lung cancer recognition, Journal of Biomedical Informatics (2018).

20.

Zhang

Z.W.

and Sun

, Mud pulse signal processing method based on Kalman filtering, China Petroleum Machinery (2015).

21.

Rönnow

Amin

Alizadeh

and Zenteno

, Phase noise coherence of two continuous wave radio frequency signals of different frequency, Iet Science Measurement and Technology 11 (2017), 77–85.

De-noising processing method in the process of drilling-oriented parameters transfer

Abstract

Keywords

Get full access to this article

References