MX340384B - Metodos y aparatos para moldear las caracteristicas del esquisto en lodos basados en lodos basados en agua utilizando una red neural artificial. - Google Patents

Metodos y aparatos para moldear las caracteristicas del esquisto en lodos basados en lodos basados en agua utilizando una red neural artificial.

Info

Publication number
MX340384B
MX340384B MX2014012620A MX2014012620A MX340384B MX 340384 B MX340384 B MX 340384B MX 2014012620 A MX2014012620 A MX 2014012620A MX 2014012620 A MX2014012620 A MX 2014012620A MX 340384 B MX340384 B MX 340384B
Authority
MX
Mexico
Prior art keywords
formation
neural network
artificial neural
target
apparatuses
Prior art date
Application number
MX2014012620A
Other languages
English (en)
Other versions
MX2014012620A (es
Inventor
S Maghrabi Shadaab
E Jamison Dale
Gajanan Kulkarni Dhanashree
D Kulkarni Sandeep
D Teke Kushabhau
Original Assignee
Halliburton Energy Services Inc
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 Halliburton Energy Services Inc filed Critical Halliburton Energy Services Inc
Publication of MX2014012620A publication Critical patent/MX2014012620A/es
Publication of MX340384B publication Critical patent/MX340384B/es

Links

Classifications

    • 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
    • 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
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Molecular Biology (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Earth Drilling (AREA)
  • Investigation Of Foundation Soil And Reinforcement Of Foundation Soil By Compacting Or Drainage (AREA)
  • Treatment Of Sludge (AREA)
  • Feedback Control In General (AREA)
  • User Interface Of Digital Computer (AREA)

Abstract

Se describe un aparato y método para determinar la interacción formación-fluido de una formación objetivo y un fluido de perforación objetivo. El método puede incluir el entrenamiento de una red neural artificial utilizando un grupo de datos de entrenamiento. El grupo de datos de entrenamiento puede incluir una característica de la formación de una formación fuente y una característica de fluido de un fluido de perforación fuente. Una vez que es entrenada la red neural artificial, una característica de la formación de la formación objetivo puede ser introducida. La característica de la formación de la formación objetivo puede corresponder a la característica de formación de la formación fuente. Una interacción formación-fluido de la formación objetivo y el fluido de perforación objetivo puede ser determinado utilizando un valor enviado por la red neural artificial.
MX2014012620A 2012-05-24 2013-05-17 Metodos y aparatos para moldear las caracteristicas del esquisto en lodos basados en lodos basados en agua utilizando una red neural artificial. MX340384B (es)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US13/480,245 US9117169B2 (en) 2012-05-24 2012-05-24 Methods and apparatuses for modeling shale characteristics in wellbore servicing fluids using an artificial neural network
PCT/US2013/041665 WO2013176994A1 (en) 2012-05-24 2013-05-17 Methods and apparatuses for modeling shale characteristics in water-based muds using an artificial neural network

Publications (2)

Publication Number Publication Date
MX2014012620A MX2014012620A (es) 2015-05-07
MX340384B true MX340384B (es) 2016-07-07

Family

ID=48539409

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2014012620A MX340384B (es) 2012-05-24 2013-05-17 Metodos y aparatos para moldear las caracteristicas del esquisto en lodos basados en lodos basados en agua utilizando una red neural artificial.

Country Status (8)

Country Link
US (1) US9117169B2 (es)
EP (1) EP2828804A1 (es)
AU (1) AU2013266635B2 (es)
BR (1) BR112014029223A2 (es)
CA (1) CA2871158A1 (es)
EA (1) EA030212B1 (es)
MX (1) MX340384B (es)
WO (1) WO2013176994A1 (es)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140279772A1 (en) * 2013-03-13 2014-09-18 Baker Hughes Incorporated Neuronal networks for controlling downhole processes
US9501740B2 (en) 2014-06-03 2016-11-22 Saudi Arabian Oil Company Predicting well markers from artificial neural-network-predicted lithostratigraphic facies
GB2555019B (en) 2015-06-10 2021-06-02 Halliburton Energy Services Inc Apparatus and methods to manage wellbore fluid properties
GB2559282B (en) * 2015-10-30 2021-07-21 Halliburton Energy Services Inc Enhancing drilling operations with cognitive computing
US10072919B1 (en) 2017-08-10 2018-09-11 Datacloud International, Inc. Efficient blast design facilitation systems and methods
US10101486B1 (en) 2017-08-10 2018-10-16 Datacloud International, Inc. Seismic-while-drilling survey systems and methods
US10697294B2 (en) 2018-02-17 2020-06-30 Datacloud International, Inc Vibration while drilling data processing methods
US10989828B2 (en) 2018-02-17 2021-04-27 Datacloud International, Inc. Vibration while drilling acquisition and processing system
CN114482995B (zh) * 2022-03-10 2024-06-18 西南石油大学 一种细粒沉积物泥质含量精细确定方法

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA2357921C (en) * 2000-09-29 2007-02-06 Baker Hughes Incorporated Method and apparatus for prediction control in drilling dynamics using neural networks

Also Published As

Publication number Publication date
EP2828804A1 (en) 2015-01-28
WO2013176994A1 (en) 2013-11-28
CA2871158A1 (en) 2013-11-28
BR112014029223A2 (pt) 2017-06-27
AU2013266635B2 (en) 2016-01-28
AU2013266635A1 (en) 2014-10-30
EA201492211A1 (ru) 2015-02-27
US9117169B2 (en) 2015-08-25
EA030212B1 (ru) 2018-07-31
MX2014012620A (es) 2015-05-07
US20130318019A1 (en) 2013-11-28

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