Open AccessResearch on calibrating rock mechanical parameters with a statistical method
Author(s) -
Zhen Liu,
Ye Guo,
Shihong Du,
WU Gengyu,
Pan Mao
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0176215
Subject(s) - interpolation (computer graphics) , rock mechanics , kriging , geology , well logging , calibration , computer science , experimental data , geotechnical engineering , petroleum engineering , mathematics , machine learning , statistics , artificial intelligence , motion (physics)
Research on the modeling of rock mechanics parameters is of great significance to the exploration of oil and gas. The use of logging data with the Kriging interpolation to study rock mechanics parameters has been proven to be effective in reservoir prediction and other oilfield applications and can provide additional data. However, there will sometimes be a great deviation due to the limited samples and the strong heterogeneity of a layer. To solve this problem, a new approach was proposed to calibrate rock mechanical models through the statistical analysis of logging data. A module was developed to calibrate rock mechanics parameters automatically, which was then applied to the Wangyao area of the Ansai oilfield. This method significantly improved the accuracy of rock mechanics modeling.