公开(公告)号：US12050295B2

公开(公告)日：2024-07-30

申请号：US17247501

申请日：2020-12-14

Applicant: ExxonMobil Technology and Engineering Company

Inventor： Mehdi Aharchaou ,  Anatoly Baumstein ,  Junzhe Sun ,  Rongrong Lu ,  Erik Neumann

IPC: G01V1/28 ,  E21B47/002 ,  E21B49/00 ,  G01V1/30 ,  G01V1/34 ,  G01V1/38 ,  G06N3/044 ,  G06N3/045 ,  G06N3/08 ,  G01V1/36

CPC classification number: G01V1/30 ,  E21B47/0025 ,  E21B49/00 ,  G01V1/282 ,  G01V1/345 ,  G01V1/3843 ,  G06N3/044 ,  G06N3/045 ,  G06N3/08 ,  E21B2200/20 ,  G01V1/366 ,  G01V2210/1423 ,  G01V2210/43 ,  G01V2210/614

Abstract: A methodology for extending bandwidth of geophysical data is disclosed. Geophysical data, obtained via a towed streamer, may have significant noise in a certain band (such as less than 4 Hz), rendering the data in the certain band unreliable. To remedy this, geophysical data, from a band that is reliable, may be extended to the certain band, resulting in bandwidth extension. One manner of bandwidth extension comprises using machine learning to generate a machine learning model. Specifically, because bandwidth may be viewed as a sequence, machine learning configured to identify sequences, such as recurrent neural networks, may be used to generate the machine learning model. In particular, machine learning may use a training dataset acquired via ocean bottom nodes in order to generate the machine learning model. After which, the machine learning model may be used to extend the bandwidth of a test dataset acquired via a towed streamer.