Assessment of Net-To-Gross Uncertainty at Reservoir Appraisal Stage: Application to a Turbidite Reservoir Offshore West Africa

Amisha Maharaja and A. G. Journel and Guillaume Caumon and S. Strebelle. ( 2008 )
in: Proc. eighth Geostatistical Geostatistics Congress, Santiago, pages 707--716, Gecamin ltd

Abstract

The appraisal stage net-to-gross (NTG) uncertainty of a deepwater turbidite reservoir is assessed using a comprehensive workflow that accounts for uncertainty due to different geological scenarios, incorporates historical information and company expertise through prior probability distributions, and integrates seismic data to correct for the potential bias in NTG estimate due to preferentially drilled wells. Results show that the impact of the geological scenario on NTG uncertainty is larger when the facies geometries are very different. Both the range and shape of the prior distribution impact the posterior NTG probability distributions; the range of the posterior distribution is smaller than that of the prior distribution because of the underlying Bayesian framework. With each additional well, the posterior distributions becomes narrower, indicating that more data reduces uncertainty about the global NTG value.

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    BibTeX Reference

    @INPROCEEDINGS{Maharaja08,
        author = { Maharaja, Amisha and Journel, A. G. and Caumon, Guillaume and Strebelle, S. },
        editor = { Ortiz, Julian and Emery, Xavier },
         title = { Assessment of Net-To-Gross Uncertainty at Reservoir Appraisal Stage: Application to a Turbidite Reservoir Offshore West Africa },
     booktitle = { Proc. eighth Geostatistical Geostatistics Congress },
        volume = { 2 },
       chapter = { 0 },
          year = { 2008 },
         pages = { 707--716 },
     publisher = { Gecamin ltd },
      location = { Santiago },
      abstract = { The appraisal stage net-to-gross (NTG) uncertainty of a deepwater turbidite reservoir is assessed using a comprehensive workflow that accounts for uncertainty due to different geological scenarios, incorporates historical information and company expertise through prior probability distributions, and integrates seismic data to correct for the potential bias in NTG estimate due to preferentially drilled wells. Results show that the impact of the geological scenario on NTG uncertainty is larger when the facies geometries are very different. Both the range and shape of the prior distribution impact the posterior NTG probability distributions; the range of the posterior distribution is smaller than that of the prior distribution because of the underlying Bayesian framework. With each additional well, the posterior distributions becomes narrower, indicating that more data reduces uncertainty about the global NTG value. }
    }