AUTOMATED SEISMIC INTERPRETATION SYSTEMS AND METHODS FOR CONTINUAL LEARNING AND INFERENCE OF GEOLOGICAL FEATURES

Title:

AUTOMATED SEISMIC INTERPRETATION SYSTEMS AND METHODS FOR CONTINUAL LEARNING AND INFERENCE OF GEOLOGICAL FEATURES

Document Type and Number:

WIPO Patent Application WO/2020/123100

Kind Code:

A3

Abstract:

A method and apparatus for automated seismic interpretation (ASI), including: obtaining trained models comprising a geologic scenario from a model repository, wherein the trained models comprise executable code; obtaining test data comprising geophysical data for a subsurface region; and performing an inference on the test data with the trained models to generate a feature probability map representative of subsurface features. A method and apparatus for machine learning, including: an ASI model; a training dataset comprising seismic images and a plurality of data portions; a plurality of memory locations, each comprising a replication of the ASI model and a different data portion of the training dataset; a plurality of data augmentation modules, each identified with one of the plurality of memory locations; a training module configured to receive output from the plurality of data augmentation modules; and a model repository configured to receive updated models from the training module.

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Inventors:

MACDONALD CODY J (US)
HERNANDEZ DIEGO A (US)
LIU WEI D (US)
DENLI HUSEYIN (US)
LIU KUANG-HUNG (US)
KOVALSKI MICHAEL H (US)
SOM DE CERFF VICTORIA M (US)

Application Number:

PCT/US2019/061797

Publication Date:

July 23, 2020

Filing Date:

November 15, 2019

Export Citation:

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Assignee:

EXXONMOBIL UPSTREAM RES CO (US)

International Classes:

G01V1/28; G01V1/30; G01V99/00

Domestic Patent References:

WO2018026995A1

2018-02-08

Foreign References:

EP1036341A1

2000-09-20

Other References:

LEI HUANG ET AL: "A scalable deep learning platform for identifying geologic features from seismic attributes", THE LEADING EDGE, vol. 36, no. 3, 30 March 2017 (2017-03-30), US, pages 249 - 256, XP055474335, ISSN: 1070-485X, DOI: 10.1190/tle36030249.1
YING JIANG: "Detecting geological structures in seismic volumes using deep convolutional neural networks", 22 February 2017 (2017-02-22), XP055523502, Retrieved from the Internet [retrieved on 20181113]

Attorney, Agent or Firm:

BAEHL, Stephen A. et al. (US)

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