RT Journal Article
ID 738f47ca64d7c860
A1 Zhang, Liming 
A1 Cui, Chenyu 
A1 Zhang, Kai 
A1 Wang, Yi 
A1 Sun, Zhixue 
A1 Yao, Jun 
A1 Luo, Qin 
T1 REDUCING FRACTURE PREDICTION UNCERTAINTY BASED ON TIME-LAPSE SEISMIC (4D) AND DETERMINISTIC INVERSION ALGORITHM
JF International Journal for Uncertainty Quantification
JO IJUQ
YR 2019
FD 2019-04-23
VO 9
IS 2
SP 187
OP 204
K1 fracture prediction uncertainty
K1 Bayesian theory
K1 time-lapse seismic (4D)
K1 deterministic inversion
K1 reservoir fracturing
AB The uncertainty of hydraulic fracture is high due to the complex geological features of which there is limited accurate understanding, and the limitations of the fracture diagnosis method. However, hydraulic fractures are one of the main driving forces for oilfields to improve economic benefit and important reference imformation for further development and adjustment of oilfields. Therefore, reducing fracture morphology uncertainty is a key challenge for the further development of oilfields. To improve this situation, we present a novel method based on the time-lapse (4D) seismic and discrete network deterministic inversion (DNDI) algorithm for mapping the geometry of hydraulic fracture. The time-lapse (4D) seismic method can provide spatial and dynamic change of reservoir; this information is used by DNDI to optimize fracture geometry continually, where the embedded discrete fracture model (EDFM) is implied to simulate reservoir production, and objective function is constructed using Bayesian theory for reaching iterative convergence quickly. An uncertainty analysis of results based on the posterior probability is also presented in this paper. Finally, this method has been validated in different scale study cases.

PB Begell House
LK https://www.dl.begellhouse.com/journals/52034eb04b657aea,3f762e845665d4bd,738f47ca64d7c860.html