BR112023026368A2 - METHOD AND SYSTEM FOR RECORDING DATA FOR A MINERAL SAMPLE - Google Patents

METHOD AND SYSTEM FOR RECORDING DATA FOR A MINERAL SAMPLE

Info

Publication number
BR112023026368A2
BR112023026368A2 BR112023026368A BR112023026368A BR112023026368A2 BR 112023026368 A2 BR112023026368 A2 BR 112023026368A2 BR 112023026368 A BR112023026368 A BR 112023026368A BR 112023026368 A BR112023026368 A BR 112023026368A BR 112023026368 A2 BR112023026368 A2 BR 112023026368A2
Authority
BR
Brazil
Prior art keywords
estimate
sample
material type
initial
abundance
Prior art date
Application number
BR112023026368A
Other languages
Portuguese (pt)
Inventor
Michael Gonzalez Christopher
John Wedge Daniel
Holden Chang Eun-Jung
Leonora Hackman
Thomas Green
Anthony Horrocks Tom
Original Assignee
Tech Resources Pty Ltd
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
Priority claimed from AU2021901798A external-priority patent/AU2021901798A0/en
Application filed by Tech Resources Pty Ltd filed Critical Tech Resources Pty Ltd
Publication of BR112023026368A2 publication Critical patent/BR112023026368A2/en

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/24—Earth materials
    • 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
    • G06N3/0455—Auto-encoder networks; Encoder-decoder 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
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • 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
    • G06N3/088—Non-supervised learning, e.g. competitive learning
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/20—Identification of molecular entities, parts thereof or of chemical compositions
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B2200/00—Special features related to earth drilling for obtaining oil, gas or water
    • E21B2200/22—Fuzzy logic, artificial intelligence, neural networks or the like
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N2021/3595—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using FTIR
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/12—Circuits of general importance; Signal processing
    • G01N2201/129—Using chemometrical methods
    • G01N2201/1296—Using chemometrical methods using neural networks
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/70—Machine learning, data mining or chemometrics

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Evolutionary Computation (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Molecular Biology (AREA)
  • Computational Linguistics (AREA)
  • Geology (AREA)
  • Biophysics (AREA)
  • Biomedical Technology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Biochemistry (AREA)
  • Analytical Chemistry (AREA)
  • Environmental & Geological Engineering (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Mining & Mineral Resources (AREA)
  • Pathology (AREA)
  • Immunology (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Medicinal Chemistry (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Food Science & Technology (AREA)
  • Remote Sensing (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Fluid Mechanics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Geochemistry & Mineralogy (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)
  • Automatic Analysis And Handling Materials Therefor (AREA)

Abstract

a presente invenção refere-se a vários sistemas e métodos de registro para registrar dados obtidos para uma amostra, incluindo um registrador de tipo de material infravermelho configurado para: receber espectros de infravermelho associados com a amostra; processar os espectros de infravermelho utilizando um algoritmo de aprendizado de máquina pré-treinado ou um algoritmo estatístico para gerar um ou ambos de: uma estimativa de abundância de tipo de material inicial para a amostra, em que a estimativa de abundância de tipo de material inicial é uma estimativa da presença de um ou mais tipos de materiais específicos dentro da amostra e uma estimativa da abundância relativa de cada dito tipo de material, e uma estimativa de percentagem de massa inicial para a amostra; e armazenar a estimativa de abundância de tipo de material inicial e/ou estimativa de percentagem de massa inicial geradas na memória.The present invention relates to various recording systems and methods for recording data obtained for a sample, including an infrared material type recorder configured to: receive infrared spectra associated with the sample; process the infrared spectra using a pre-trained machine learning algorithm or a statistical algorithm to generate one or both of: an initial material type abundance estimate for the sample, wherein the initial material type abundance estimate is an estimate of the presence of one or more specific types of materials within the sample and an estimate of the relative abundance of each said type of material, and an estimate of the initial mass percentage for the sample; and storing the initial material type abundance estimate and/or initial mass percentage estimate generated in memory.

BR112023026368A 2021-06-16 2022-06-16 METHOD AND SYSTEM FOR RECORDING DATA FOR A MINERAL SAMPLE BR112023026368A2 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
AU2021901798A AU2021901798A0 (en) 2021-06-16 A method and system for logging data for a mineral sample
AU2022900471A AU2022900471A0 (en) 2022-02-28 A method and system for logging data for a mineral sample
PCT/AU2022/050599 WO2022261712A1 (en) 2021-06-16 2022-06-16 A method and system for logging data for a mineral sample

Publications (1)

Publication Number Publication Date
BR112023026368A2 true BR112023026368A2 (en) 2024-03-05

Family

ID=84525710

Family Applications (1)

Application Number Title Priority Date Filing Date
BR112023026368A BR112023026368A2 (en) 2021-06-16 2022-06-16 METHOD AND SYSTEM FOR RECORDING DATA FOR A MINERAL SAMPLE

Country Status (6)

Country Link
EP (1) EP4356167A4 (en)
AU (1) AU2022293197A1 (en)
BR (1) BR112023026368A2 (en)
CA (1) CA3221595A1 (en)
CL (1) CL2023003732A1 (en)
WO (1) WO2022261712A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118072850B (en) * 2024-04-19 2024-06-21 四川省地质矿产勘查开发局成都综合岩矿测试中心（国土资源部成都矿产资源监督检测中心） Method and system for mass analysis of geochemical sample in target area

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018136998A1 (en) * 2017-01-25 2018-08-02 Technological Resources Pty. Limited A method and system for validating logging data for a mineral sample
US11352879B2 (en) * 2017-03-14 2022-06-07 Saudi Arabian Oil Company Collaborative sensing and prediction of source rock properties
US20220207079A1 (en) * 2019-05-09 2022-06-30 Abu Dhabi National Oil Company Automated method and system for categorising and describing thin sections of rock samples obtained from carbonate rocks

Also Published As

Publication number Publication date
AU2022293197A1 (en) 2023-12-21
CA3221595A1 (en) 2022-12-22
WO2022261712A1 (en) 2022-12-22
EP4356167A1 (en) 2024-04-24
EP4356167A4 (en) 2024-10-09
CL2023003732A1 (en) 2024-05-17

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