WO2005098647A3 - Genetic algorithm based selection of neural network ensemble for processing well logging data - Google Patents

Genetic algorithm based selection of neural network ensemble for processing well logging data Download PDF

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Publication number
WO2005098647A3
WO2005098647A3 PCT/US2005/009494 US2005009494W WO2005098647A3 WO 2005098647 A3 WO2005098647 A3 WO 2005098647A3 US 2005009494 W US2005009494 W US 2005009494W WO 2005098647 A3 WO2005098647 A3 WO 2005098647A3
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WO
WIPO (PCT)
Prior art keywords
genetic algorithm
neural network
algorithm based
well logging
logging data
Prior art date
Application number
PCT/US2005/009494
Other languages
French (fr)
Other versions
WO2005098647A2 (en
Inventor
Dingding Chen
Syed Hamid
Harry D Smith Jr
Original Assignee
Halliburton Energy Serv Inc
Dingding Chen
Syed Hamid
Harry D Smith Jr
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Publication date
Application filed by Halliburton Energy Serv Inc, Dingding Chen, Syed Hamid, Harry D Smith Jr filed Critical Halliburton Energy Serv Inc
Priority to BRPI0509129-2A priority Critical patent/BRPI0509129A/en
Priority to MXPA06011012A priority patent/MXPA06011012A/en
Priority to GB0620649A priority patent/GB2427946B/en
Priority to CA2559860A priority patent/CA2559860C/en
Publication of WO2005098647A2 publication Critical patent/WO2005098647A2/en
Priority to EGNA2006000881 priority patent/EG25977A/en
Publication of WO2005098647A3 publication Critical patent/WO2005098647A3/en

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    • 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
    • G06N3/08—Learning methods
    • G06N3/086—Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
    • 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

Abstract

A system and method for generating a neural network ensemble. Conventional algorithms are used to train a number of neural networks having error diversity, for example by having a different number of hidden nodes in each network. A genetic algorithm having a multi-objective fitness function is used to select one or more ensembles. The fitness function includes a negative error correlation objective to insure diversity among the ensemble members. A genetic algorithm may be used to select weighting factors for the multi-objective function. In one application, a trained model may be used to produce synthetic open hole logs in response to inputs of cased hole log data.
PCT/US2005/009494 2004-03-26 2005-03-22 Genetic algorithm based selection of neural network ensemble for processing well logging data WO2005098647A2 (en)

Priority Applications (5)

Application Number Priority Date Filing Date Title
BRPI0509129-2A BRPI0509129A (en) 2004-03-26 2005-03-22 methods for generating a set of neural networks and for producing synthetic drillhole records from real pulsed neutron records, and apparatus for producing as synthetic values from at least one geophysical parameter to a well in response to actual value inputs of geophysical parameters measured in the well
MXPA06011012A MXPA06011012A (en) 2004-03-26 2005-03-22 Genetic algorithm based selection of neural network ensemble for processing well logging data.
GB0620649A GB2427946B (en) 2004-03-26 2005-03-22 Genetic algorithm based selection of neural network ensemble for processing well logging data
CA2559860A CA2559860C (en) 2004-03-26 2005-03-22 Genetic algorithm based selection of neural network ensemble for processing well logging data
EGNA2006000881 EG25977A (en) 2004-03-26 2006-09-18 Genetic algorithm based selection of neural network ensemble for processing well logging data

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US10/811,403 2004-03-26
US10/811,403 US7280987B2 (en) 2004-03-26 2004-03-26 Genetic algorithm based selection of neural network ensemble for processing well logging data

Publications (2)

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WO2005098647A2 WO2005098647A2 (en) 2005-10-20
WO2005098647A3 true WO2005098647A3 (en) 2009-04-16

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PCT/US2005/009494 WO2005098647A2 (en) 2004-03-26 2005-03-22 Genetic algorithm based selection of neural network ensemble for processing well logging data

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US (1) US7280987B2 (en)
BR (1) BRPI0509129A (en)
CA (1) CA2559860C (en)
EG (1) EG25977A (en)
GB (1) GB2427946B (en)
MX (1) MXPA06011012A (en)
WO (1) WO2005098647A2 (en)

Families Citing this family (54)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1205863A1 (en) * 2000-11-14 2002-05-15 Honda R&D Europe (Deutschland) GmbH Multi-objective optimization
EP1235180A1 (en) * 2001-02-26 2002-08-28 Honda R&D Europe (Deutschland) GmbH Parameter adaptation in evolution strategies
US8374974B2 (en) * 2003-01-06 2013-02-12 Halliburton Energy Services, Inc. Neural network training data selection using memory reduced cluster analysis for field model development
EP1598751B1 (en) * 2004-01-12 2014-06-25 Honda Research Institute Europe GmbH Estimation of distribution algorithm (EDA)
EP1557788B1 (en) * 2004-01-26 2008-04-16 Honda Research Institute Europe GmbH Reduction of fitness evaluations using clustering technique and neural network ensembles
US7526461B2 (en) * 2004-11-17 2009-04-28 Gm Global Technology Operations, Inc. System and method for temporal data mining
US7613665B2 (en) * 2005-06-24 2009-11-03 Halliburton Energy Services, Inc. Ensembles of neural networks with different input sets
US7587373B2 (en) * 2005-06-24 2009-09-08 Halliburton Energy Services, Inc. Neural network based well log synthesis with reduced usage of radioisotopic sources
EP1768053A1 (en) * 2005-09-12 2007-03-28 Honda Research Institute Europe GmbH Evolutionary search for robust solutions
US7505947B2 (en) * 2005-10-20 2009-03-17 International Business Machines Corporation Computer controlled method using genetic algorithms to provide non-deterministic solutions to problems involving physical restraints
US20070288410A1 (en) * 2006-06-12 2007-12-13 Benjamin Tomkins System and method of using genetic programming and neural network technologies to enhance spectral data
AU2007274283A1 (en) * 2006-07-13 2008-01-17 4Sc Ag Benzopyranopyrazoles
US8065244B2 (en) * 2007-03-14 2011-11-22 Halliburton Energy Services, Inc. Neural-network based surrogate model construction methods and applications thereof
WO2009025560A1 (en) * 2007-08-17 2009-02-26 Institutt For Energiteknikk System and method for empirical ensemble-based virtual sensing of gas emission
US20090182693A1 (en) * 2008-01-14 2009-07-16 Halliburton Energy Services, Inc. Determining stimulation design parameters using artificial neural networks optimized with a genetic algorithm
US8364528B2 (en) * 2008-05-06 2013-01-29 Richrelevance, Inc. System and process for improving product recommendations for use in providing personalized advertisements to retail customers
US9514388B2 (en) * 2008-08-12 2016-12-06 Halliburton Energy Services, Inc. Systems and methods employing cooperative optimization-based dimensionality reduction
BRPI0820365A2 (en) * 2008-08-26 2015-05-12 Halliburton Energy Serv Inc Method, system, and computer readable storage media.
NO329798B1 (en) * 2009-02-16 2010-12-20 Inst Energiteknik System and method for empirical ensemble-based virtual sensing of particulate matter
WO2010123494A1 (en) 2009-04-21 2010-10-28 Halliburton Energy Services, Inc. System and method of predicting gas saturation of a formation using neural networks
US9092737B2 (en) * 2009-07-30 2015-07-28 Northwestern University Systems, methods, and apparatus for 3-D surface mapping, compliance mapping, and spatial registration with an array of cantilevered tactile hair or whisker sensors
JP2011107648A (en) * 2009-11-20 2011-06-02 Fujifilm Corp Lens unit
US9104978B2 (en) 2010-10-07 2015-08-11 Microsoft Technology Licensing, Llc System and method for parameter evaluation
US8775341B1 (en) 2010-10-26 2014-07-08 Michael Lamport Commons Intelligent control with hierarchical stacked neural networks
US9015093B1 (en) 2010-10-26 2015-04-21 Michael Lamport Commons Intelligent control with hierarchical stacked neural networks
CN102681011B (en) * 2011-03-15 2014-08-13 无锡物联网产业研究院 Mining method and system for seismic data
US8700549B2 (en) 2012-05-23 2014-04-15 King Fahd University Of Petroleum And Minerals Method of predicting gas composition
US9022140B2 (en) 2012-10-31 2015-05-05 Resource Energy Solutions Inc. Methods and systems for improved drilling operations using real-time and historical drilling data
NO347038B1 (en) * 2013-03-27 2023-04-24 Logined Bv Automatic geosteering and evolutionary algorithm for use with same
EP2924560A1 (en) 2014-03-28 2015-09-30 ForecasstThis Ltd Apparatus and process for automating discovery of effective algorithm configurations for data processing using evolutionary graphical search
US9501740B2 (en) 2014-06-03 2016-11-22 Saudi Arabian Oil Company Predicting well markers from artificial neural-network-predicted lithostratigraphic facies
RU2666631C2 (en) 2014-09-12 2018-09-11 МАЙКРОСОФТ ТЕКНОЛОДЖИ ЛАЙСЕНСИНГ, ЭлЭлСи Training of dnn-student by means of output distribution
US10410118B2 (en) * 2015-03-13 2019-09-10 Deep Genomics Incorporated System and method for training neural networks
US11062228B2 (en) 2015-07-06 2021-07-13 Microsoft Technoiogy Licensing, LLC Transfer learning techniques for disparate label sets
WO2017154284A1 (en) * 2016-03-09 2017-09-14 ソニー株式会社 Information processing method and information processing device
TWI612433B (en) * 2016-11-17 2018-01-21 財團法人工業技術研究院 Ensemble learning prediction aparatus and method, and non-transitory computer-readable storage medium
US10474925B2 (en) 2017-07-31 2019-11-12 Industrial Technology Research Institute Deep neural network with side branches for recognizing and classifying media data and method for using the same
US11060214B2 (en) 2017-08-11 2021-07-13 Northwestern University Processing methods and apparatus to manufacture a functional, multi-scale, tapered fiber from polymer filament
US10885900B2 (en) 2017-08-11 2021-01-05 Microsoft Technology Licensing, Llc Domain adaptation in speech recognition via teacher-student learning
US11074503B2 (en) 2017-09-06 2021-07-27 SparkCognition, Inc. Execution of a genetic algorithm having variable epoch size with selective execution of a training algorithm
US11106978B2 (en) 2017-09-08 2021-08-31 SparkCognition, Inc. Execution of a genetic algorithm with variable evolutionary weights of topological parameters for neural network generation and training
US10635978B2 (en) 2017-10-26 2020-04-28 SparkCognition, Inc. Ensembling of neural network models
WO2020046721A1 (en) * 2018-08-27 2020-03-05 D5Ai Llc Building a deep neural network with diverse strata
US11443244B2 (en) * 2019-06-05 2022-09-13 International Business Machines Corportation Parallel ensemble of machine learning algorithms
US11634980B2 (en) 2019-06-19 2023-04-25 OspreyData, Inc. Downhole and near wellbore reservoir state inference through automated inverse wellbore flow modeling
US11475297B2 (en) 2019-08-28 2022-10-18 International Business Machines Corporation Cross-domain homophily quantification for transfer learning
US11741370B2 (en) * 2019-08-28 2023-08-29 International Business Machines Corporation Transfer learning based on cross-domain homophily influences
CN111027782B (en) * 2019-12-25 2020-11-06 安徽建筑大学 Building secondary water supply optimal scheduling method and device based on centerless genetic algorithm
CN111414977B (en) * 2020-03-09 2023-06-20 西南交通大学 Weighted integration temperature sensitive point combination selection method for machine tool spindle thermal error modeling
CN111767674B (en) * 2020-05-29 2024-03-29 中国科学技术大学 Logging lithology recognition method based on active domain adaptation
CN111915097B (en) * 2020-08-14 2022-11-11 南通大学 Water quality prediction method for optimizing LSTM neural network based on improved genetic algorithm
KR102428572B1 (en) * 2020-12-10 2022-08-03 한국전자기술연구원 Hyper Parameter Optimization Method in Lightweight Artificial Intelligence System Using Genetic Algorithm
CN116012688B (en) * 2023-03-27 2023-06-09 成都神鸟数据咨询有限公司 Image enhancement method for urban management evaluation system
CN116644662B (en) * 2023-05-19 2024-03-29 之江实验室 Well-arrangement optimization method based on knowledge embedded neural network proxy model

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5862513A (en) * 1996-11-01 1999-01-19 Western Atlas International, Inc. Systems and methods for forward modeling of well logging tool responses

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5251286A (en) * 1992-03-16 1993-10-05 Texaco, Inc. Method for estimating formation permeability from wireline logs using neural networks
US5444619A (en) * 1993-09-27 1995-08-22 Schlumberger Technology Corporation System and method of predicting reservoir properties
US5828981A (en) * 1995-05-11 1998-10-27 Texaco Inc. Generating pore types and synthetic capillary pressure curves from wireline logs using neural networks
US6789620B2 (en) * 2001-02-16 2004-09-14 Halliburton Energy Services, Inc. Downhole sensing and flow control utilizing neural networks

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5862513A (en) * 1996-11-01 1999-01-19 Western Atlas International, Inc. Systems and methods for forward modeling of well logging tool responses

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
GRANITTO, P. M. ET AL.: "Modeling of Sonic Logs in Oil Wells with Neural Networks Ensembles.", ASAI, 2001, pages I *
ZHOU, Z. H. ET AL.: "Genetic Algorithm based Selective Neural Network Ensemble.", 17TH INTL JOINT CONF ON AI, vol. 2, 2001, pages 797 - 802 *

Also Published As

Publication number Publication date
CA2559860C (en) 2011-06-07
WO2005098647A2 (en) 2005-10-20
GB0620649D0 (en) 2006-12-06
GB2427946B (en) 2008-03-19
CA2559860A1 (en) 2005-10-20
EG25977A (en) 2012-11-18
MXPA06011012A (en) 2007-01-25
GB2427946A (en) 2007-01-10
BRPI0509129A (en) 2007-08-28
US20050246297A1 (en) 2005-11-03
US7280987B2 (en) 2007-10-09

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