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Application of stochastic inversion to casing effect correction in through casing induction logging (CROSBI ID 181153)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Vasić, Darko ; Bilas, Vedran Application of stochastic inversion to casing effect correction in through casing induction logging // IEEE transactions on instrumentation and measurement, 61 (2012), 5; 1458-1465. doi: 10.1109/TIM.2012.2183432

Podaci o odgovornosti

Vasić, Darko ; Bilas, Vedran

engleski

Application of stochastic inversion to casing effect correction in through casing induction logging

Electromagnetic induction logging is routinely used for the measurement of the electrical conductivity of rock formations from within an uncased borehole in order to determine producibility of the hydrocarbons. Because of its usefulness in the open-hole environment, it was proposed to use this method inside steel cased wells. The casings are magnetic and for five or six orders of magnitude more conductive than a typical rock formation. Thus, the measurements in the through casing induction logging must be corrected for the variations in casing properties. It was suggested to employ the existing casing inspection tools for this purpose. In this paper we develop a stochastic approach to the inverse problem of determination of the casing properties using these tools. We numerically analyze the application of the inversion procedure to the model of a typical casing inspection measurement and investigate if the information obtained from the modeled data is applicable to the correction of the rock conductivity measurement for the casing effect. We conclude that the measurement uncertainty of the tool cannot exceed 1000 ppm if it is to be used for the casing effect correction.

induction well logging; rock conductivity; cased well; casing inspection; inverse problems; Monte Carlo methods; Markov chains

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Podaci o izdanju

61 (5)

2012.

1458-1465

objavljeno

0018-9456

10.1109/TIM.2012.2183432

Povezanost rada

Elektrotehnika

Poveznice
Indeksiranost