﻿ 基于形态学的滤波消除泥浆脉冲信号基线漂移 Removing Baseline Drifting in Mud Pulse Signals Based on Morphological Filtering

Journal of Oil and Gas Technology
Vol. 41  No. 04 ( 2019 ), Article ID: 32035 , 6 pages
10.12677/JOGT.2019.414049

Removing Baseline Drifting in Mud Pulse Signals Based on Morphological Filtering

Chaoyang Xu, Xianghui Ren, Qiang Xue, Qianhong Cao

Directional Drilling Service Company, CNPC Bohai Drilling Engineering Company Limited, Tianjin

Received: Mar. 20th, 2019; accepted: Apr. 18th, 2019; published: Aug. 15th, 2019

ABSTRACT

A morphological filter for removing mud pulse baseline drifting was established. The baseline drifting of simulated PPM encoding signal of mud pulse was processed by least-square polynomial fitting, median filtering and morphological filtering methods, respectively. The results were quantitatively analyzed by using signal to noise ratio (SNR), root mean square error (Erms) and normalized correlation coefficient (Cncc). The analysis result shows that the morphological filtering method proposed is the best for removing the baseline drift of mud pulse signal.

Keywords:MWD, Mud Pulse Signal, Baseline Drift, Morphological Filtering

Copyright © 2019 by authors, Yangtze University and Hans Publishers Inc.

1. 引言

2. 泥浆脉冲信号噪声干扰

Figure 1. The field acquisition of mud pressure pulse signal and frequency domain analysis of pulse signal

3. 形态学滤波

3.1. 形态学运算

f(n)关于g(m)腐蚀的关系式如下：

$\left(f\Theta g\right)\left(n\right)=\mathrm{min}\left\{f\left(n+m\right)-g\left(m\right)\right\}$$n=0,\text{1},\cdots ,N-M$ (1)

f(n)关于g(m)膨胀的关系式如下：

$\left(f\oplus g\right)\left(n\right)=\mathrm{max}\left\{f\left(n-m\right)+g\left(m\right)\right\}$$n=0,\text{1},\cdots ,N+M-\text{2}$ (2)

$\left(f\circ g\right)\left(n\right)=\left(f\Theta g\oplus g\right)\left(n\right)$ (3)

$\left(f•g\right)\left(n\right)=\left(f\oplus g\Theta g\right)\left(n\right)$ (4)

3.2. 形态学滤波器设计

${f}_{1}=\frac{1}{2}\left({f}_{0}\circ {g}_{1}•{g}_{1}+{f}_{0}•{g}_{1}\circ {g}_{1}\right)$ (5)

${f}_{2}=\frac{1}{2}\left({f}_{1}\circ {g}_{2}•{g}_{2}+{f}_{1}•{g}_{2}\circ {g}_{2}\right)$ (5)

${f}_{3}={f}_{0}-{f}_{2}$ (6)

4. 试验分析

4.1. 试验样本

Figure 2. The signals of test samples

4.2. 结果分析

4.2.1. 定性分析

Figure 3. The modified results of strong nonlinear baseline drift at high duty cycle of analog signals

Figure 4. The modified results of strong nonlinear baseline drift at low duty cycle of analog signals

4.2.2. 定量分析

Table 1. The comparison of modified results of strong nonlinear baseline drift at high duty cycle of analog signals

Table 2. The evaluation of modified results of strong nonlinear baseline drift at low duty cycle of analog signals

5. 结论

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