Non-Stationary Random Medium Parameter Estimation of Petrophysical Parameters Driven by Seismic Data

Ying Lin, Guangzhi Zhang, Minmin Huang, Baoli Wang and Siyuan Chen
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Ying Lin: School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China
Guangzhi Zhang: School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China
Minmin Huang: Shenzhen Branch, CNOOC (China) Co., Ltd., Shenzhen 518067, China
Baoli Wang: School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China
Siyuan Chen: College of Geophysics, China University of Petroleum (Beijing), Beijing 102249, China

Energies, 2022, vol. 15, issue 13, 1-21

Abstract: The estimation of non-stationary random medium parameters of petrophysical parameters is the key to the application of random medium theory in fine seismic exploration. We proposed a method for estimating non-stationary random medium parameters of petrophysical parameters using seismic data. Based on the linear petrophysical model, the relationship between seismic data and porosity, clay volume, and water saturation in the random medium was described, and the principle and method of estimating the autocorrelation parameters of the petrophysical parameter random medium were introduced in this study. Subsequently, the specific steps of applying the power spectrum method, for parameter estimation in non-stationary random media with petrophysical parameters, were explained. The feasibility and correctness of the method were verified through the estimation test of the two-dimensional theoretical model. Eventually, the estimation test of non-stationary random medium parameters of petrophysical parameters was carried out by field seismic data, and the results indicated that the non-stationary random medium parameters can better portray the information of subsurface medium petrophysical parameters. The method can provide a reference for the construction of a priori information on petrophysical parameters, and it can also provide a theoretical basis for the in-depth application of random medium theory to practical data.

Keywords: parameter estimation; petrophysical parameters; non-stationary random medium; autocorrelation parameters; partially stacked seismic (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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