Bayesian Time-lapse Difference Inversion Based on the exact Zoeppritz Equations with Blockiness Constraint
Author(s) -
Lin Zhou,
Jianping Liao,
Jingye Li,
Xiaohong Chen,
Tianchun Yang,
Andrew Hursthouse
Publication year - 2020
Publication title -
journal of environmental and engineering geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.573
H-Index - 32
eISSN - 1943-2658
pISSN - 1083-1363
DOI - 10.2113/jeeg19-045
Subject(s) - inversion (geology) , gaussian , mathematics , bayesian probability , laplace transform , inverse transform sampling , geology , mathematical optimization , computer science , statistics , mathematical analysis , physics , seismology , surface wave , quantum mechanics , tectonics , telecommunications
Accurately inverting changes in the elastic parameters of a reservoir that are caused by oil and gas exploitation is of great importance in accurately describing reservoir dynamics and enhancing recovery. Previously numerous time-lapse seismic inversion methods based on the approximate formulas of exact Zoeppritz equations or wave equations have been used to estimate these changes. However the low accuracy of calculations using approximate formulas and the significant calculation effort for the wave equations seriously limits the application of these methods. However, these limitations can be overcome by using exact Zoeppritz equations. Therefore, we study the time-lapse seismic difference inversion method using the exact Zoeppritz equations. Firstly, the forward equation of time-lapse seismic difference data is derived based on the exact Zoeppritz equations. Secondly, the objective function based on Bayesian inversion theory is constructed using this equation, with the changes in elastic parameters assumed to obey a Gaussian distribution. In order to capture the sharp time-lapse changes of elastic parameters and further enhance the resolution of the inversion results, the blockiness constraint, which follows the differentiable Laplace distribution, is added to the prior Gaussian background model. All examples of its application show that the proposed method can obtain stable and reasonable Pand S-wave velocities and density changes from the difference data . The accuracy of estimation is higher than for existing methods, which verifies the effectiveness and feasibility of the new method. It can provide high-quality seismic inversion results for dynamic detailed reservoir description and well location during development.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom