Invention Grant
- Patent Title: Interpretation of seismic survey data using synthetic modelling
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Application No.: US15118964Application Date: 2015-03-19
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Publication No.: US10338243B2Publication Date: 2019-07-02
- Inventor: Nicholas Mcardle
- Applicant: Foster Findlay Associates Limited
- Applicant Address: GB Tyne and Wear
- Assignee: Foster Findlay Associates Limited
- Current Assignee: Foster Findlay Associates Limited
- Current Assignee Address: GB Tyne and Wear
- Agency: Workman Nydegger
- Priority: GB1405779.8 20140331
- International Application: PCT/GB2015/050802 WO 20150319
- International Announcement: WO2015/150728 WO 20151008
- Main IPC: G01V1/28
- IPC: G01V1/28 ; G01V1/30 ; G01V1/38

Abstract:
A method is provided for an improved interpretation of seismic data, comprising the steps of: •(a) obtaining a 3D seismic data set from a predetermined region; •(b) generating at least one attribute volume comprising at least one attribute of said 3D seismic data; •(c) selecting a zone of interest from said at least one attribute volume of said 3D seismic data set; •(d) determining a frequency spectrum of said zone of interest; •(e) generating a synthetic model of said zone of interest based on said frequency spectrum of said zone of interest and the model defined by at least a three dimensional space, wherein a first variable parameter is variable in a first dimension of the space, and at least a second variable parameter is variable in at least a second and/or third dimension; •(f) calibrating said synthetic model utilizing additional data indicative to physical properties of said zone of interest; •(g) utilizing said calibrated synthetic model to provide the frequency spectrum of a synthetic seismic response of said zone of interest and project the spectrum on a horizon of said zone of interest, and •(h) generating a visual representation of said projected spectrum against said first variable parameter and at least said second variable parameter.
Public/Granted literature
- US20170052268A1 Improved Interpretation of Seismic Survey Data Using Synthetic Modelling Public/Granted day:2017-02-23
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