scholarly journals Comparison robust data smoothing algorithms with wavelet filter for denoising sonic log signals

Author(s):  
Saeed Aftab ◽  
Rasoul Hamidzadeh Moghadam

Abstract Well logging is an essential approach to making geophysical surveys and petrophysical measurements and plays a key role to interpret downhole conditions. But, well logging signals usually contain noise that distorts results and causes ambiguous interpretations. In this paper, the wavelet filter and robust data smoothing algorithms are tested for denoising synthetic sonic log and field sonic log data. Robust data smoothing algorithms include Gaussian, RLOESS (Robust locally estimating scatterplot smoothing), and RLOWESS (Robust locally weighted scatterplot smoothing) methods. Uniform and normal distribution noise applied to synthetic model and results revealed that the wavelet filter performs better than data smoothing algorithms for denoising uniform distribution noise. However, the RLOESS removed uniform noise acceptably. But, for normal distribution noise, the wavelet filter disrupts and data smoothing algorithms, specifically RLOESS attenuated noise perfectly. Due to the noise nature of field sonic log data, wavelet filter completely disrupts, but data smoothing algorithms removed the noise of field data more efficiently, particularly RLOESS. So, we can express that RLOESS is a perfect algorithm for denoising sonic log signals, regardless of noise nature.

2021 ◽  
pp. 1-15
Author(s):  
Amit Govil ◽  
Harald Nevøy ◽  
Lars Hovda ◽  
Guillermo A. Obando Palacio ◽  
Geir Kjeldaas

Summary As part of plug and abandonment (P&A) operations, several acceptance criteria need to be considered by operators to qualify barrier elements. In casing annuli, highly bonded material is occasionally found far above the theoretical top of cement. This paper aims to describe how the highly bonded material can be identified using a combination of ultrasonic logging data, validated with measurements in laboratory experiments using reference cells and how this, in combination with data from the well construction records, can contribute to lowering the costly toll of P&A operations. Ultrasonic and sonic log data were acquired in several wells to assess the bond quality behind multiple casing sizes in an abandonment campaign. Data obtained from pulse-echo and flexural sensors were interactively analyzed with a crossplotting technique to distinguish gas, liquid, barite, cement, and formation in the annular space. Within the methodology used, historical data on each well were considered as an integral part of the analysis. During the original well construction, either water-based mud (WBM) or synthetic oil-based mud (OBM) was used for drilling and cementing operations, and some formation intervals consistently showed high bonding signatures under specific conditions, giving clear evidence of formation creep. Log data from multiple wells confirm that formation behavior is influenced by the type of mud used during well construction. The log data provided information of annulus material with a detailed map of the axial and azimuthal variations of the annulus contents. In some cases, log response showed a clear indication of formation creep, evidenced by a high bond quality around the production casing where cement cannot be present. Based on observations from multiple fields in the Norwegian continental shelf, a crossplot workflow has been designed to distinguish formation from cement as the potential barrier element. NORSOK Standard D-010 (2013) has initial verification acceptance criteria both for annulus cement and creeping formation as a well barrier element, both involving bond logs; however, in the case of creeping formation, it is more stringent stating that “two independent logging measurements/tools shall be applied.” This paper aims to demonstrate how this can be done with confidence using ultrasonic and sonic log data, validated against reference barrier cells (Govil et al. 2020). Logging responses like those gathered during full-scale experiments of reference barrier cells with known defects were observed in multiple wells in the field. Understanding the phenomenon of formation creep and its associated casing bond signature could have a massive impact on P&A operations. With a successful qualification of formation as an annulus barrier, significant cost and time savings can be achieved.


2012 ◽  
Vol 516-517 ◽  
pp. 530-535
Author(s):  
Xin Jie Deng ◽  
Yang Sheng You ◽  
Yan Ying Chen ◽  
Xue Mei Yang

The homogeneity test is the first stage to revise the climate records. Its accuracy will directly affect the follow-up work. The classic method SNHT (Standard Normal Homogeneity Test) can only be applied in climatic sequences obey normal distribution, but lots of non-normality climate sequences need to be examined. In this paper, the Smirnov Test was introduced to test the homogeneity of the temperature series, which is a classical method for distribution test, and it can apply for the temperature sequences obey any distribution. The homogeneity test results by testing Chongqing Municipality's temperature sequences show that: the Smirnov Test is better than SNHT


Author(s):  
Nicolás D. Barbosa ◽  
Andrew Greenwood ◽  
Eva Caspari ◽  
Nathan Dutler ◽  
Klaus Holliger
Keyword(s):  
Log Data ◽  

Author(s):  
Tomio Inazaki ◽  
Toshiyuki Kurahashi ◽  
Shiro Watanabe
Keyword(s):  
Log Data ◽  

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Chun Lv ◽  
Peilin Zhang ◽  
Dinghai Wu ◽  
Bing Li ◽  
Yunqiang Zhang

Bearing fault signal analysis is an important means of bearing fault diagnosis. To effectively eliminate noise in a fault signal, an adaptive multiscale combined morphological filter is proposed based on the theory of mathematical morphology. Both simulation and experimental results show that the adaptive multiscale combined morphological filter can remove noise more thoroughly and retain details of the fault signal better than the dual-tree complex wavelet filter, traditional morphological filter, adaptive singular value decomposition method (ASVD), and improved switching Kalman filter (ISKF). The adaptive multiscale combined morphological filter considers both positive and negative impulses in the signal; therefore, it has strong adaptability to complex noise in the environment, making it an effective new method for bearing fault diagnosis.


2010 ◽  
Vol 439-440 ◽  
pp. 481-485
Author(s):  
Li Xia Liu ◽  
Yi Qi Zhuang

Clustering techniques are often used in Web log mining to analyze user’s interest on the web pages. Based on the analysis of advantages and disadvantages of the application of classic clustering algorithm in Web log data mining, the paper brought out a kind of hierarchical K-means Web log clustering algorithm, which integrated K-means clustering algorithm and cohesion-based hierarchical clustering algorithm and overcame shortcoming of high time complexity of hierarchical clustering algorithm. The clustering effect of the algorithm is better than K-means clustering and fit for clustering process of large amount data. The result analysis of practical Web log data clustering also proves the validity of the algorithm.


2011 ◽  
Vol 314-316 ◽  
pp. 2482-2485 ◽  
Author(s):  
Shu Guang He ◽  
Chuan Yan Zhang

A SVDD (Support Vector Data Description) based MCUSUM (Multivariate Cumulative Sum) chart is proposed and referred as S-MCUSUM chart, which has an advantage of distribution free. Numerical experiments on the performance of the S-MCUSUM chart is compared to the COT (Cumulative of T) chart. The results show that the COT chart is somewhat better than the S-MCUSUM chart for multivariate normally distributed data. However, the S-MCUSUM chart is much better than the COT chart for banana-shaped distributed data which is a typical non-normal distribution.


2019 ◽  
Vol 412 (5) ◽  
pp. 1129-1136 ◽  
Author(s):  
Wim Broothaerts ◽  
Fernando Cordeiro ◽  
Philippe Corbisier ◽  
Piotr Robouch ◽  
Hendrik Emons

AbstractThe outcome of proficiency tests (PTs) is influenced, among others, by the evaluation procedure chosen by the PT provider. In particular for PTs on GMO testing a log-data transformation is often applied to fit skewed data distributions into a normal distribution. The study presented here has challenged this commonly applied approach. The 56 data populations from proficiency testing rounds organised since 2010 by the European Union Reference Laboratory for Genetically Modified Food and Feed (EURL GMFF) were used to investigate the assumption of a normal distribution of reported results within a PT. Statistical evaluation of the data distributions, composed of 3178 reported results, revealed that 41 of the 56 datasets showed indeed a normal distribution. For 10 datasets, the deviation from normality was not statistically significant at the raw or log scale, indicating that the normality assumption cannot be rejected. The normality of the five remaining datasets was statistically significant after log-data transformation. These datasets, however, appeared to be multimodal as a result of technical/experimental issues with the applied methods. On the basis of the real datasets analysed herein, it is concluded that the log transformation of reported data in proficiency testing rounds is often not necessary and should be cautiously applied. It is further shown that the log-data transformation, when applied to PT results, favours the positive performance scoring for overestimated results and strongly penalises underestimated results. The evaluation of the participants’ performance without prior transformation of their results may highlight rather than hide relevant underlying analytical problems and is recommended as an outcome of this study.


1997 ◽  
Vol 47 (3-4) ◽  
pp. 167-180 ◽  
Author(s):  
Nabendu Pal ◽  
Jyh-Jiuan Lin

Assume i.i.d. observations are available from a p-dimensional multivariate normal distribution with an unknown mean vector μ and an unknown p .d. diaper- . sion matrix ∑. Here we address the problem of mean estimation in a decision theoretic setup. It is well known that the unbiased as well as the maximum likelihood estimator of μ is inadmissible when p ≤ 3 and is dominated by the famous James-Stein estimator (JSE). There are a few estimators which are better than the JSE reported in the literature, but in this paper we derive wide classes of estimators uniformly better than the JSE. We use some of these estimators for further risk study.


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