Theory and Application of Geostatistical Inversion: A Facies-Constrained MCMC Algorithm

To improve the prediction of thin reservoirs with special geophysical responses, a geostatistical inversion technique is proposed based on an in-depth analysis theory inversion. This Markov chain Monte Carlo algorithm, to which we added contents facies-constrained. The feasibility and reliability results are demonstrated by sand bodies in braided river channel bars Xiazijie Oilfield Junggar Basin. Based MCMC show that leveraging lateral changes seismic waveforms as geologically relevant information drive construction variogram optimization statistical sampling can largely overcome obstacle prevents traditional inversions from accurately delineating sedimentary characteristics; thereby, algorithm truly achieves facies-constrained case study showed this technology. accuracy FCMCMC algorithm-based high 6 m for interbedded reservoirs, coincidence rate between well log data more than 85%, confirms technique. performance provides preliminary reference formed terrestrial basins characterized small thicknesses rapid responses.