Author
Listed:
- Ying Lin
(School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China
Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China)
- Guangzhi Zhang
(School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China
Key Laboratory of Deep Oil and Gas, 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
Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China)
- Siyuan Chen
(College of Geophysics, China University of Petroleum (Beijing), Beijing 102249, China)
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.
Suggested Citation
Ying Lin & Guangzhi Zhang & Minmin Huang & Baoli Wang & Siyuan Chen, 2022.
"Non-Stationary Random Medium Parameter Estimation of Petrophysical Parameters Driven by Seismic Data,"
Energies, MDPI, vol. 15(13), pages 1-21, July.
Handle:
RePEc:gam:jeners:v:15:y:2022:i:13:p:4849-:d:853926
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4849-:d:853926. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.