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International Journal for Uncertainty Quantification
IF: 0.967 5-Year IF: 1.301 SJR: 0.531 SNIP: 0.8 CiteScore™: 1.52

ISSN Print: 2152-5080
ISSN Online: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2019027680
Forthcoming Article

Reducing Fracture Prediction Uncertainty Based On Time-Lapse Seismic (4D) And Deterministic Inversion Algorithm

zhang Liming
china unversity of petroleum
Cui Chenyu
china unversity of petroleum
wang yi
china unversity of petroleum
Zhang Kai
china unversity of petroleum
sun zhixue
china unversity of petroleum
yao jun
china unversity of petroleum

ABSTRACT

The uncertainty of hydraulic fracture is high due to the complex geological features that people can hardly understand accurately and limitations of fracture diagnose method. However, hydraulic fractures are one of the main drive force for oilfield to improve economic benefit and the important reference imformation for oilfield further development and adjustment. Therefore, reducing fracture morpholody uncertainty is a key challenge for the further development of oilfield. To improve this situation, we present a novel method based on Time-Lapse (4D) seismic and Discrete Network Deterministic Inversion(DNDI) algorithm for mapping the geometry of hydraulic fracture. Time-Lapse(4D) seismic can provide spatial and dynamic change of reservoir and this information is learned by DNDI to optimize fracture geometry continuely, where 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 result based on the posterior probability is also presented in this paper. In the final, this method has been validated in different scale study cases.