Array processing—a new method to detect and correct errors on array resistivity logging tool measurements

Philip D. Rabinowitz; Zhiqiang Zhou

doi:10.1007/s00343-007-0051-7

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Array processing—a new method to detect and correct errors on array resistivity logging tool measurements

Updated：2023-05-16

- Array processing—a new method to detect and correct errors on array resistivity logging tool measurements
- Journal of Oceanology and Limnology Vol. 25, Issue 1, Pages: 51-58(2007)
- Affiliations：
  
  Department of Geology and Geophysics Texas A&M University
- Author bio：
- Funds：
- DOI：10.1007/s00343-007-0051-7
  CLC：
- Published：2007
- Accepted：
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Rabinowitz, P.D., Zhou, Z. Array processing—a new method to detect and correct errors on array resistivity logging tool measurements., Chin. J. Ocean. Limnol. 25, 51–58 (2007). https://doi.org/10.1007/s00343-007-0051-7
DOI：

Rabinowitz, P.D., Zhou, Z. Array processing—a new method to detect and correct errors on array resistivity logging tool measurements., Chin. J. Ocean. Limnol. 25, 51–58 (2007). https://doi.org/10.1007/s00343-007-0051-7 DOI：

摘要

Abstract

In recent years more and more multi-array logging tools

such as the array induction and the array lateralog

are applied in place of conventional logging tools resulting in increased resolution

better radial and vertical sounding capability and other features. Multi-array logging tools acquire several times more individual measurements than conventional logging tools. In addition to new information contained in these data

there is a certain redundancy among the measurements. The sum of the measurements actually composes a large matrix. Providing the measurements are error-free

the elements of this matrix show certain consistencies. Taking advantage of these consistencies

an innovative method is developed to detect and correct errors in the array resistivity logging tool raw measurements

and evaluate the quality of the data. The method can be described in several steps. First

data consistency patterns are identified based on the physics of the measurements. Second

the measurements are compared against the consistency patterns for error and bad data detection. Third

the erroneous data are eliminated and the measurements are re-constructed according to the consistency patterns. Finally

the data quality is evaluated by comparing the raw measurements with the re-constructed measurements. The method can be applied to all array type logging tools

such as array induction tool and array resistivity tool. This paper describes the method and illustrates its application with the High Definition Lateral Log (HDLL

Baker Atlas) instrument. To demonstrate the efficiency of the method

several field examples are shown and discussed.

关键词

Keywords

references

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