Integration of seismic and well data to characterize facies variation in a carbonate reservoir-the tau model revisited

M. Elahi Naraghi, S. Srinivasan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


In this paper, we present a novel method of data integration based on the permanence of ratio hypothesis. In order to model the conditional probability, it would be convenient if the information from each data source can be assessed independently in order to find P(A|B) and P(A|C), and then these joint probabilities are merged to calculate P(A|B,C) accounting for the redundancy between different data sources. We propose a methodology for calculating the redundancy between different sources of information. Our formulation is based on the information from each data modeled using a mixture of Gaussian assumption indicative of the multiple facies or categories of rock properties observed in the reservoir. We implemented the proposed methodology to characterize a carbonate reservior in the Gulf of Mexico. The available data sets were drill cutting data, core data, well log measurements and 3D seismic volume. We used core data to calibrate log measurements to lithofacies. Then, we merged the probability maps of lithofacies using permanence of ratio hypothesis and generated multiple realization by Monte-Carlo sampling from the probability maps. The modeling resulted in identification of reservoir regions that have higher proportion of dolomitized grainstones that might be suitable drilling targets.

Original languageEnglish (US)
Title of host publicationPetroleum Geostatistics 2015
PublisherEuropean Association of Geoscientists and Engineers, EAGE
Number of pages5
ISBN (Electronic)9781510814110
StatePublished - 2015
EventPetroleum Geostatistics 2015 - Biarritz, France
Duration: Sep 7 2015Sep 11 2015

Publication series

NamePetroleum Geostatistics 2015


OtherPetroleum Geostatistics 2015

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Geophysics
  • Statistics, Probability and Uncertainty
  • Geology


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