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2 Acta Geophysica

2 2011

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Shale volume estimation based on the factor analysis of well-logging data

Szabó N.P.

Acta Geophysica

2011

Vol. 59, no. 5

935-953

In the paper factor analysis is applied to well-logging data in order to extract petrophysical information about sedimentary structures. Statistical processing of well logs used in hydrocarbon exploration results in a factor log, which correlates with shale volume of the formations. The so-called factor index is defined analogously with natural gamma ray index for describing a linear relationship between one special factor and shale content. Then a general formula valid for a longer depth interval is introduced to express a nonlinear relationship between the above quantities. The method can be considered as an independent source of shale volume estimation, which exploits information inherent in all types of well logs being sensitive to the presence of shale. For demonstration, two wellbore data sets originated from different areas of the Pannonian Basin of Central Europe are processed, after which the shale volume is computed and compared to estimations coming from independent inverse modeling.

Interval inversion of well-logging data for objective determination of textural parameters

Dobróka M., Szabó N.P.

Acta Geophysica

2011

Vol. 59, no. 5

907-934

A joint inversion method for the evaluation of well-logging data is presented, which is applicable to determine textural parameters, i.e., cementation exponent, saturation exponent and tortuosity factor, simultaneously with conventional petrophysical properties. The inversion techniques used today perform local interpretation. Since the number of unknowns is slightly lower than that of the data estimated locally to one depth-point, a set of marginally overdetermined inverse problems has to be solved. For preserving the overdetermination, textural parameters must be kept constant for longer depth intervals (i.e., 200-300 m), despite the fact that they seem to be varying faster with depth according to field experiences. An inversion method was developed, which inverts data of a greater depth interval jointly in a highly overdetermined inversion procedure and gives a better resolution (10 m or less) estimate for the textural parameters. In the paper, a set of inversion tests on synthetic data as well as a field example prove the feasibility of the method.