1887

Abstract

Summary

A key component in modelling temperature and pressure evolution of a basin and in forecasting the distribution of overpressure zones, is the ability to properly include geochemical compaction processes effects. Two major mechanisms driving geochemical compaction are: the deposition and cementation of quartz and the transformation of smectite to illite.

The proposed solution take into account of non-linear interactions among these diagenetic processes with temperature and pressure evolution and of the lacking of information about rock properties between wells. The execution of a global sensitivity analysis of the major factors affecting compaction and overpressure is an approach able to deal with the incomplete availability of experimental data. This allows to obtain: improved estimates with associated uncertainty as well as to understand the relationships among uncertain input data and modelled output results.

Since global sensitivity analysis requires many model runs to obtain pressure and temperature distributions, the proposed modelling strategy is based on the approximation of the basin response through a so called polynomial chaos expansion.

This procedure allows obtaining at low computational cost the so called Sobol indices, that quantify the effect of each uncertain parameter on the main variables of the basin.

The methodology is illustrated through applications to synthetic and real cases.

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/content/papers/10.3997/2214-4609.20143789
2014-09-21
2020-04-05
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References

  1. Carrera, J. and S.Neumann, S.
    [1986] Estimation of Aquifer Parameters Under Transient and Steady State Conditions: 1. Maximum Likelihood Method Incorporating Prior Information. Water Resourses Research22(2), 199–210.
    [Google Scholar]
  2. Formaggia, L., Guadagnini, A., Imperiali, I., Lever, V., Porta, G., Riva, M., Scotti, A., Tamellini, L.
    [2012] Global sensitivity analysis through polynomial chaos expansion of a basin-scale geochemical compaction model. Computational Geosciences, 17(1), 25–42.
    [Google Scholar]
  3. Fowler, A. C. and Yang, X.
    [2003] Dissolution/precipitation mechanisms for diagenesis in sedimentary basins. Journal of Geophysical Research, 108(B10), 2509.
    [Google Scholar]
  4. Huang, W. L., Longo, J. M., and Pevear, D. P.
    [1993] An experimentally derived kinetic model for smectite-to-illite conversion and its use as a geothermometer. Clays and Clay Minerals, 41(2), 162–177.
    [Google Scholar]
  5. Scrofani, G., Ruffo, P., Porta, G., Riva, M., Lever, V., Scotti, A., Imperiali, I.
    [2013] Preliminary analysis of diagenetic effects on basin scale over pressure dynamics. 6th IPTC, Beijing, Extended Abstracts, 16690.
    [Google Scholar]
  6. Walderhaug, O.
    [1996] Kinetic modeling of quartz cementation and porosity loss in deeply buried sandstone reservoirs. AAPG Bulletin80, 731–745.
    [Google Scholar]
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