MX2021014549A - Interpretacion de fallas sismicas mediante tecnicas de aprendizaje automatico. - Google Patents

Interpretacion de fallas sismicas mediante tecnicas de aprendizaje automatico.

Info

Publication number
MX2021014549A
MX2021014549A MX2021014549A MX2021014549A MX2021014549A MX 2021014549 A MX2021014549 A MX 2021014549A MX 2021014549 A MX2021014549 A MX 2021014549A MX 2021014549 A MX2021014549 A MX 2021014549A MX 2021014549 A MX2021014549 A MX 2021014549A
Authority
MX
Mexico
Prior art keywords
machine learning
learning technique
seismic
probability values
generating
Prior art date
Application number
MX2021014549A
Other languages
English (en)
Inventor
Cen Li
Aria Abubakar
Original Assignee
Geoquest Systems Bv
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Geoquest Systems Bv filed Critical Geoquest Systems Bv
Publication of MX2021014549A publication Critical patent/MX2021014549A/es

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/34—Displaying seismic recordings or visualisation of seismic data or attributes
    • G01V1/345—Visualisation of seismic data or attributes, e.g. in 3D cubes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/301—Analysis for determining seismic cross-sections or geostructures
    • G01V1/302—Analysis for determining seismic cross-sections or geostructures in 3D data cubes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/282—Application of seismic models, synthetic seismograms
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/34—Displaying seismic recordings or visualisation of seismic data or attributes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/64—Geostructures, e.g. in 3D data cubes
    • G01V2210/642—Faults
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/66—Subsurface modeling
    • G01V2210/667—Determining confidence or uncertainty in parameters

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Remote Sensing (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Geophysics (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Geology (AREA)
  • Environmental & Geological Engineering (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Artificial Intelligence (AREA)
  • Data Mining & Analysis (AREA)
  • Mathematical Physics (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Geophysics And Detection Of Objects (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)

Abstract

Un método para interpretar datos sísmicos incluye recibir datos sísmicos que representan un volumen subterráneo y generar valores de probabilidad en línea y valores de probabilidad transversales utilizando una primera técnica de aprendizaje automático. La primera técnica de aprendizaje automático está entrenada para identificar una o más líneas de fallas verticales en un volumen sísmico con base en los datos sísmicos. El método incluye generar un conjunto de datos fusionados al combinar los valores de probabilidad en línea y los valores de probabilidad transversales, entrenar una segunda técnica de aprendizaje automático basada en un subconjunto de planos horizontales etiquetados del conjunto de datos fusionados, la segunda técnica de aprendizaje automático entrenada para identificar líneas de falla horizontales del volumen sísmico y generar una representación del volumen sísmico basada en la segunda técnica de aprendizaje automático, la representación incluye una indicación de una estructura de falla tridimensional dentro del volumen sísmico.
MX2021014549A 2019-05-28 2020-05-28 Interpretacion de fallas sismicas mediante tecnicas de aprendizaje automatico. MX2021014549A (es)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201962853681P 2019-05-28 2019-05-28
PCT/US2020/034779 WO2020243216A1 (en) 2019-05-28 2020-05-28 Interpreting seismic faults with machine learning techniques

Publications (1)

Publication Number Publication Date
MX2021014549A true MX2021014549A (es) 2022-02-11

Family

ID=73554182

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2021014549A MX2021014549A (es) 2019-05-28 2020-05-28 Interpretacion de fallas sismicas mediante tecnicas de aprendizaje automatico.

Country Status (8)

Country Link
US (1) US20220229199A1 (es)
EP (1) EP4147075A4 (es)
CN (1) CN114402231A (es)
AU (1) AU2020283948A1 (es)
BR (1) BR112021023950A2 (es)
CA (1) CA3141760A1 (es)
MX (1) MX2021014549A (es)
WO (1) WO2020243216A1 (es)

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2597429B (en) * 2019-09-12 2023-07-12 Landmark Graphics Corp Geological feature detection using generative adversarial neural networks
CA3214674A1 (en) * 2021-03-22 2022-09-29 Schlumberger Canada Limited Automatic subsurface property model building and validation
CN113640879B (zh) * 2021-08-16 2022-02-15 中国矿业大学(北京) 基于双网络的储层时移参数预测方法和系统
US20230358910A1 (en) * 2022-05-06 2023-11-09 Landmark Graphics Corporation Automated fault segment generation
US20240069237A1 (en) * 2022-08-26 2024-02-29 Landmark Graphics Corporation Inferring subsurface knowledge from subsurface information

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101506686B (zh) * 2006-06-21 2013-11-06 特拉斯帕克地球科学有限责任公司 地质沉积体系的解释
US9952340B2 (en) * 2013-03-15 2018-04-24 General Electric Company Context based geo-seismic object identification
US10139508B1 (en) * 2016-03-24 2018-11-27 EMC IP Holding Company LLC Methods and apparatus for automatic identification of faults on noisy seismic data
CN110462445B (zh) * 2017-02-09 2022-07-26 地质探索系统公司 地球物理深度学习

Also Published As

Publication number Publication date
CN114402231A (zh) 2022-04-26
US20220229199A1 (en) 2022-07-21
WO2020243216A1 (en) 2020-12-03
EP4147075A4 (en) 2024-07-24
AU2020283948A1 (en) 2021-12-23
EP4147075A1 (en) 2023-03-15
CA3141760A1 (en) 2020-12-03
BR112021023950A2 (pt) 2022-02-01

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