Reservoir parameter inversion based on weighted statistics

• Published in: Applied geophysics Vol. 12; no. 4; pp. 523 - 532
• Main Authors: Gui, Jin-Yong, Gao, Jian-Hu, Yong, Xue-Shan, Li, Sheng-Jun, Liu, Bin-Yang, Zhao, Wan-Jin
• Format: Journal Article
• Language: English
• Published: Beijing Chinese Geophysical Society 01.12.2015; Springer Nature B.V; Research Institute of Petroleum Exploration & Development-Northwest Branch,Petrochina,Lanzhou 730020,China
• Subjects: Bayesian analysis; Computer simulation; Density; Earth and Environmental Science; Earth Sciences; Geophysics; Geophysics/Geodesy; Geostatistics; Geotechnical Engineering & Applied Earth Sciences; Inversions; Markov chains; Mathematical models; Monte Carlo simulation; Natural gas exploration; Objective function; Physical properties; Physics; Reservoirs; Rock; Rocks; Statistical methods; Uncertainty; stochastic simulation; inversion; weighted statistics; Reservoir parameters; Bayesian framework
• DOI: 10.1007/s11770-015-0523-z
• ISSN: 1672-7975

Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.