Facies Recognition Using Multifractal Hurst Analysis: Applications to Well-Log Data
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Well-log (radioactivity, density and resistivity) analysis constitutes a standard approach for inferring lithology from wells. However, due to inherent complexity of the signals (such as highly heterogeneous deep-water sedimentary sequences) lithology recognition is not straightforward. We used a rescaled range analysis, calibrated with cores, to recognize lithological patterns from signal recorded along wireline logs. The detected intervals coincide with zones of visual electro-facies associations proposed by geologist well-log interpreters. In addition, we propose a rescaled range multifractal analysis to identify ranges of well-log signal complexities, which could be related to sedimentary process variations at specific stratigraphic order cycles.
KeywordsWell-log data Electro-facies associations R/S analysis Multifractal analysis Deep-water sequences Cyclostratigraphy
The work was supported by the Mexican Petroleum Institute (IMP) and Y.00114 Sener-Conacyt Project. We are particularly grateful to Honorio Ramirez and Miguel Angel Alarcon for fruitful discussions.
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