ABSTRACT

Elastic impedance inversion is one of the major trends of pre-stack inversion because of its high-efficiency and high-stability. The seismic stochastic inversion can make use of the high frequency information of logging data and improve the vertical resolution compared with the conventional inversion. The stochastic elastic impedance inversion is based on the dynamic multi-chain Markov chain Monte Carlo (DM-MCMC) method in this paper. The practical test verifies the feasibility and robustness of the method.

Presentation Date: Tuesday, October 18, 2016

Start Time: 8:00:00 AM

Location: 155

Presentation Type: ORAL

Keywords:
artificial intelligence, mcmc method, inversion result, reservoir characterization, stochastic elastic impedance inversion, machine learning, seismic data, annual meeting, upstream oil & gas, bayesian inference
Subjects:
Reservoir Characterization, Seismic processing and interpretation
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2016. Society of Exploration Geophysicists
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