公开(公告)号：US20160124109A1

公开(公告)日：2016-05-05

申请号：US14896459

申请日：2014-06-27

Applicant: Schlumberger Technology Corporation

Inventor： Can Evren Yarman ,  Nicholas Heaton ,  Lucas Monzon ,  Matthew Reynolds

IPC: G01V3/38 ,  E21B47/12 ,  E21B47/00 ,  G01V3/32 ,  G01N24/08

CPC classification number: G01V3/38 ,  E21B47/00 ,  E21B47/12 ,  G01N24/081 ,  G01R33/448 ,  G01V3/32

Abstract: The present disclosure provides a semi-analytic inversion method that computes an approximate, sparse representation of the data in terms of the (a, T1, T2). Methods, in accordance with the present disclosure, compute T2's in a semi-analytic fashion, such as by using simultaneous Hankel representation of the data, use one dimensional convex optimization to compute the amplitudes, a, and finally compute T1 in an analytic fashion by appropriate averaging techniques. The proposed method provides a more efficient way to represent the data when compared to linearized methods, and is computationally less demanding when compared to some existing nonlinear optimization methods.

Abstract translation: 本公开提供了一种半解析反演方法，其根据（a，T1，T2）计算数据的近似稀疏表示。 根据本公开的方法，例如通过使用数据的同时Hankel表示以半分析方式计算T2，使用一维凸优化来计算幅度a，并且最终以分析方式计算T1 适当的平均技术。 当与线性化方法相比时，所提出的方法提供了更有效的方式来表示数据，并且当与一些现有的非线性优化方法相比时计算量要求较低。