• Title of article

    Simulation of acoustic impedance images by stochastic inversion of post-stack seismic reflection amplitudes and well data

  • Author/Authors

    Alves، نويسنده , , Fernando and Almeida، نويسنده , , José Antَnio and Silva، نويسنده , , Ana Paula، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    14
  • From page
    52
  • To page
    65
  • Abstract
    Here we present an approach for simulation of 3D images of acoustic impedance conditional both to post-stack seismic reflection amplitudes and well impedance data. The method uses the following steps: (1) we calculate an initial deterministic image of impedances and reflection coefficients; (2) we apply a modified version of the sequential simulation and co-simulation algorithm for generating the impedance images conditioned to the reflection coefficients previously calculated and the impedance observed in the wells; and (3) we validate the results, particularly with respect to the correlation between the observed seismic cubes and the synthetic seismic cubes obtained by convolution of the simulated images of impedance. The advantages of this workflow are (1) efficiency – it is necessary to run only one simulation for each output image; (2) mapping of uncertainty – the set of equiprobable output images is conditional to both the impedance well data and the reflection coefficients of the deterministic image; and (3) compliance – the method complies with the characteristics of a simulation, namely, the declustered histogram of the well data, the variogram, and the reproduction of well data in blocks close to well locations. The approach was tested for modeling the impedance of a selected region of the Stratton gas reservoir.
  • Keywords
    siliciclastic reservoir , local and global uncertainty , stochastic simulation of impedance , post-stack seismic inversion , 3D modeling
  • Journal title
    Journal of Petroleum Science and Engineering
  • Serial Year
    2014
  • Journal title
    Journal of Petroleum Science and Engineering
  • Record number

    2216710