Joint Bayesian Stochastic Inversion of Well Logs and Seismic Data for Volumetric Uncertainty Analysis

Publish Year: 1394
نوع سند: مقاله ژورنالی
زبان: English
View: 486

This Paper With 12 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

JR_IJMGE-49-1_012

تاریخ نمایه سازی: 15 شهریور 1395

Abstract:

Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior information in Bayesian statistics. Data integration leads to a probability density function (named as a posteriori probability) that can yield a model of subsurface. The Markov Chain Monte Carlo (MCMC) method is used to sample the posterior probability distribution, and the subsurface model characteristics can be extracted by analyzing a set of the samples. In this study, the theory of stochastic seismic inversion in a Bayesian framework was described and applied to infer P-impedance and porosity models. The comparison between the stochastic seismic inversion and the deterministic model based seismic inversion indicates that the stochastic seismic inversion can provide more detailed information of subsurface character. Since multiple realizations are extracted by this method, an estimation of pore volume and uncertainty in the estimation were analyzed.

Authors

Moslem Moradi

Simulation and Data Processing Laboratory, Mining Engineering Department, University of Tehran, Iran

Omid Asghari

Simulation and Data Processing Laboratory, Mining Engineering Department, University of Tehran, Iran

Gholamhossein Norouzi

Simulation and Data Processing Laboratory, Mining Engineering Department, University of Tehran, Iran

Mohammad Ali Riahi

Institute of Geophysics, University of Tehran, Iran