Regard,
Masoud Nikravesh
===============================================================================
Through WWW search you will get more than 500,000 application of Fuzzy
Logic
18% Zadeh, lotfi, prade, yager, inferencing, inexact, bouchon, smets,
kohout
===============================================================================
Through WWW search you will get more than 2,000,000 application of
Neural Network
-------------------------------------------------------------------
88% Neural, networks, artificial, algorithms, intelligence, computation,
optimization, genetic, evolutionary
30% Recognition, processing, signal, pattern, speech, phoneme, phonetic,
phonemes, articulatory
29% Fuzzy, control, logic, controller, controllers
29% Adaptive, nonlinear, estimation, detection, dynamical,
multivariable, lyapunov, controllability, observability
27% Neurons, neuron, synaptic, neuronal, synapses, inhibitory,
excitatory, potentiation
25% Computational, dynamics, computations, parallelism
24% Ieee, proceedings, conference, symposium, proc, vol, spie,
transactions, iee
24% Intelligent, systems, expert, knowledge
23% Algorithm, simulated, annealing
23% Connectionist, connectionism, rumelhart, mcclelland, hinton,
lippmann
22% Architectures, parallel, vlsi, circuits, computing, massively,
analog
21% Nets, nips, neuroprose
20% Modeling, simulation, models, simulations, simulator
20% Backpropagation, feedforward, kohonen, perceptron, multilayer,
perceptrons, mlp, lvq, snns
20% Network, weights, hidden, layer, input, activation, output, sigmoid,
activations
19% Cognitive, neuroscience, cognition, neurobiology, neurophysiology,
psychology
18% Modelling, optimisation, ifac, imacs
17% Prediction, forecasting, predictive, predict, predicting,
predictions, futures
17% Engineering, programming, electrical, computer, science
17% Learning, inductive, reinforcement
Through WWW search you will get more than 500,000 application of Fuzzy
Logic
------------------------------------------------------------------
91% Fuzzy, logic, neural, artificial, algorithms, intelligence,
networks, genetic, nets
34% Reasoning, uncertainty, approximate
33% Intelligent, systems, expert, knowledge, representation
25% Adaptive, control, controllers, nonlinear, controller, automation,
robust, process
22% Ieee, proceedings, conference, symposium, papers, vol, proc,
journal, cfp
21% Inference, inputs, rules, outputs, variables, weights, chaining
19% Engineering, vlsi, electrical, circuits, design, programmable,
analog, microelectronics, transistors
19% Robotics, autonomous, robots, robotic, robot, manipulators,
manipulator, kinematics, kinematic
18% Zadeh, lotfi, prade, yager, inferencing, inexact, bouchon, smets,
kohout
18% Optimization, algorithm, discrete, linear
17% Modeling, simulation, simulator, trajecta
17% Recognition, processing, signal, classification, pattern,
segmentation, handwritten, handwriting
16% Modelling, optimisation, epsrc
16% Probabilistic, bayesian, dempster, shafer, elicitation, multivalued,
evidential
15% Computational, computation, evolutionary, automata, robustness,
grammars, computability, koza, icec
15% Programming, prolog, oriented, propositional, predicate, kantrowitz
15% Architectures, parallel, simd
14% Theory, mathematical, sets, probability, probabilities
13% Cognitive, cognition, categorization
12% Connectionist, neurocomputing, connectionism
Through WWW search you will get more than 200,000 application of AI
-------------------------------------------------------------------
47% Neural, artificial, intelligence, fuzzy, networks
21% Sensing, multispectral, geoscience, remote, imagery, landsat,
igarss, thematic, mapper
13% Brain, neurons, brains, neuron, cortex, synapses, synaptic,
dendrites
12% Modelling, simulation, visualization, optimization, supercomputing,
visualizations, multiconference
12% Computational, algorithms, processing, estimation, architectures,
parallel, massively, mimd
12% Consciousness, conscious, dennett, churchland, chardin, teilhard
12% Nonlinear, dynamical, dynamics, stochastic, chaotic, attractors,
deterministic, attractor, nonlinearities
11% Sensors, predicting, noisy
11% Ieee, symposium, proceedings, journal, transactions, vol, acta,
thermophysics, mathematicae
10% Electromagnetic, propagation, circuits, microwave, electromagnetics,
vlsi, antennas, waveguides, transistors
10% Evolution, evolutionary, organisms, darwinian, multicellular,
darwinism
10% Geophysical, geophysics, seismic, inversion, geochemistry,
seismology, petrology, crustal
9% Atmospheric, oceanography, climatology, meteorology, hydrology,
mesoscale, troposphere
9% Physics, solar, plasma, heliospheric
9% Biology, physiology, molecular, ecology, biochemistry, vertebrates,
vertebrate, organismal, biol
9% Engineering, mechanics, quantum, electrical, superconductivity,
geotechnical, biomedical, penrose
9% Astrophysics, astrophysical, telescopes8% Sensed, classification,
remotely, classifier, classifiers
8% Sensory, vestibular, otolith, vestibulo, semicircular
8% Neuroscience, neurobiology, postdoctoral, fellowships, deadline
More than 100 small and big companies, universities, research centers
and consortiums using these technologies or currently investing in this
area.
Some of the oil companies which also supporting the LBNL in these
projects are:
BP, CHEVRON, CONOCO, MOBIL, SHELL, TEXACO, UNOCAL, CGG, LANDMARK,
SCHLUMBERGER, and WESTERN ATLAS
SPE Technical Paper Index Results for Neural Network, Fuzzy Logic and
Genetic Algorithm:
------------------------------------------------------------------
38099 Universal Neural Network Based Model for Estimating The PVT
Properties
of Crude Oil Systems , Gharbi, Ridha B. ,Elsharkawy, Adel M.
38034 Reservoir Permeability Determination from Well Log Data using
Artificial
Neural Networks: An Example from the Ravva Field, Offshore India, Wong,
P.M. ,Henderson, D.J. ,Brooks, L.J.
37989 Neural Vector Quantization for Multivariate Upscaling, Chawathe,
A. ,Ye, M.
37695 Neural Network Model for Estimating The PVT Properties of Middle
East Crude Oils, Gharbi, R.B. ,Elsharkawy, A.M.
35737 CT Scan and Neural Network Technology for Construction of Detailed
Distribution of Residual Oil Saturation During Waterflooding, Garg, A.
,Kovscek, A.R. ,Nikravesh, M. ,Castanier, L. M. ,Patzek, T. W.
35721 Neural Networks for Field-Wise Waterflood Management in Low
Permeability, Fractured Oil Reservoirs, Nikravesh, M. ,Kovscek, A.R.
,Murer, A.S. ,Patzek, T.W.
31159-P Predicting Well-Stimulation Results in a Gas-Storage Field in
the Absence of
Reservoir Data With Neural Networks, Mohaghegh, Shahab ,McVey, Dan
,Aminian, Khashayai ,Ameri, Sam
31103 Prediction of Formation Damage During Fluid Injection into
Fractured, Low
Permeability Reservoirs via Neural Networks, Nikravesh, M. ,Kovscek,
A.R. ,Johnston, R.M. ,Patzek, T.W.
31100 Assessment of formation damage using artificial neural networks,
Kalam, M.Z. ,Al-Alawi, S.M. ,Al-Mukheini, M.
31010-P Estimating Permeability by Use of Neural Networks in Thinly
Bedded Shaly
Gas Sands, Malki, H.A. ,Baldwin, J.L. ,Kwari, M.A.
30974-P Development of the HT-BP Neural Network System for the
Identification of a
Well-Test Interpretation Model, Sung, Wonmo ,Yoo, Inhang ,Ra, Seunghoon
,Park, Heungjun
30974 Development of HT - BP Neural Network System for the
Identification of Well Test Interpretation Model, Sung, W. ,Yoo, I. ,Ra,
S. ,Park, H.
30722 Improved Fractured Reservoir Characterization Using Neural
Networks, Geomechanics and 3-D Seismic, Zellou, A.M. ,Ouenes, A. ,Banik,
A.K.
30600-P Application of Neural Networks to Modeling Fluid Contacts in
Prudhoe Bay, Panda, Manmath N. ,Zaucha, David E. ,Perez, Godofredo
,Chopra, Anil K.
30600 Application of Neural Networks to Modeling Fluid Contacts in
Prudhoe Bay,
Panda, M. N. ,Zaucha, D. E. ,Perez, G. ,Chopra, A. K.
30556 Automatic Parameter Estimation From Well Test Data Using
Artificial Neural Network, Athichanagorn, Suwat ,Horne, Roland N.
30202 Predicting Production Using a Neural Network (Artificial
Intelligence Beats Human Intelligence), Boomer, Robert J.
30079 Brief: Predicting Quality and Performance of Oilfield Cements With
Artificial
Neural Networks and FTIR Spectroscopy, Fletcher, Philip ,Coveney, P.V.
,Hughes, T.L. ,Methven, C.M.
29219 Neural Network: What It Can Do for Petroleum Engineers, Mohaghegh,
Shahab
29159-P Identification of Parameters Influencing the Response of Gas
Storage Wells to Hydraulic Fracturing With the Aid of a Neural Network,
McVey, D.S. ,Mohaghegh, Shahab ,Aminian, Khashayar ,Ameri, Samuel
29159 Identification of Parameters Influencing the Response of Gas
Storage Wells to
Hydraulic Fracturing With the Aid of a Neural Network, McVey, D.S.
,Mohaghegh, Shahab
28824 Predicting the Quality and Performance of Oilfield Cements Using
Artificial Neural Networks and FTIR Spectroscopy, Fletcher, Philip
,Coveney, P.V. ,Hughes, T.L. ,Methven, C.M.
28598 Application of Neural Networks in the Prediction of Reservoir
Hydrocarbon Mixture Composition From Production Data Briones, M.F.
,Rojas, G.A.
28597-P Use of Neural Networks for Prediction of Vapor/Liquid
Equilibrium K Values for Light-Hydrocarbon Mixtures, Habiballah, W.A.
,Startzman, R.A. ,Barrufet, M.A.
28597 Use of Neural Networks for Prediction of Vapor-Liquid Equilibrium
K-Values for Light Hydrocarbon Mixtures, Habiballah, W.A. ,Startzman,
R.A. ,Barrufet, M.A.
28394 A Methodological Approach for Reservoir Heterogeneity
CharacterizationUsing Artificial Neural Networks, Mohaghegh, Shahab
,Arefi, Reza ,Ameri, Samuel ,Hefner, M.H.
28237 Design and Development of an Artificial Neural Network for
Estimation of Formation Permeability, Mohaghegh, Shahab ,Arefi, Reza
,Bilgesu, Ilkin ,Ameri, Samuel ,Rose, Deanna
28237 Design and Development of An Artificial Neural Network for
Estimation of Formation Permeability Mohaghegh, Shahab ,Arefi, Reza
,Ameri, Samuel ,Rose, D.
28165 Authors' Reply to Discussion of Using Artificial Neural Nets To
Identify the Well-Test Interpretation Model, Al-Kaabi, Abdulaziz U.
,Lee, W. John
28151 Discussion of Using Artificial Neural Nets To Identify the
Well-Test Interpretation Model, Yeung, Kacheong ,Chakrabarty, Chayan
,Wu, Sherman
27905 Higher-Order Neural Networks in Petroleum Engineering Kumoluyi,
A.O.
27561 Neural Networks: A New Tool for the Petroleum Industry?, Ali, J.K.
27558-P Identification of Well Test Interpretation Models Using Higher
Order Neural Networks, Kumoluyi, A.O. ,Daltaban, T.S. ,Archer, J.S.
27558 Identification of Well-Test Models by Use of Higher-Order Neural
Networks Kumoluyi, A.O. ,Daltaban, T.S. ,Archer, J.S.
27558 Identification of Well Test Models Using Higher-Order Neural
Networks Kumoluyi, A.O. ,Daltaban, T.S. ,Archer, J.S.
26430 Determining Reservoir Properties in Reservoir Studies Using a
Fuzzy Neural Network, Zhou, Cheng Dang ,Wu, Xi-Ling ,Cheng, Ju-An
]
26427 A Robust Neural Network Model for Pattern Recognition of Pressure
Transient Test Data, Ershaghi, Iraj ,Li, Xuehai ,Hassibi, Mahnaz
,Shikari, Yusuf
26106 Complexities of Using Neural Network in Well Test Analysis of
Faulted Reservoirs, Juniardi, I.R. ,Ershaghi, Iraj
25420-P Application of an Artificial Neural Network to Pump Card
Diagnosis, Ashenayi, K. ,Nazi, G. A. ,Lea, J. F. ,Kemp, F.
25420 Application of an Artificial Neural Network to Pump Card
Diagnosis, Ashenayi, K.
25420 Application of Artificial Neural Network to Pump Card Diagnosis,
Nazi, G.M. ,Ashenayi, Kaveh ,Lea, J.F. ,Kemp, Frank
25359 Neural Network-Based Formation Parameters Estimation From Well
Logs in Quantitative Log Analysis: A Comparative Study, Zhou, Cheng-Dang
,Wu, Xi-Ling
24454 Inversion of a Lateral Log Using Neural Networks, Garcia, Gerardo
,Whitman, W.W.
22843 Using a Simulated Bidirectional Associative Neural Network Memory
With Incomplete Prototype Memories To Identify Facies From Intermittent
Logging Data Acquired in a Siliciclastic Depositional Sequence: A Case
Study, Baldwin, J.L.
21699-P Discriminant Analysis and Neural Nets: Valuable Tools To
Optimise
Completion Practices , Nitters, Gerrit ,Davies, D.R. ,Epping, W.J.M.
21699 Discriminant Analysis and Neural Nets: Valuable Tools To Optimize
Completion Practices, Nitters, Gerrit ,Davies, D.R. ,Epping, W.J.M.
21699 Discriminant Analysis and Neural Nets: Valuable Tools To Optimize
Completion Practices, Nitters, G. ,Davies, D.R. ,Epping, W.J.M.
20651 Artificial Neural Networks for Identification of Beam Pump
Dynamometer Load Cards, Rogers, J.D. ,Guffey, C.G. ,Oldham, W.J.B.
20552 An Artificial Neural Network Approach To Identify the Well Test
Interpretation Model: Applications, Al-Kaabi, A.U. ,Lee, W.J.
20332 Using Artificial Neural Nets To Identify the Well-Test
Interpretation Model, Al-Kaabi, Abdul-Aziz U. ,Lee, W. John
20332 Using Artificial Neural Networks To Identify the Well Test
Interpretation Model, Al-Kaabi, A.U. ,Lee, W.J.
19619 Computer Emulation of Human Mental Processes: Application of
Neural Network Simulators to Problems in Well Log Interpretation,
Baldwin, J.L. ,Otte, D.N. ,Whealtley, C.L.
19558 Drill Bit Diagnosis Using Neural Networks, Arehart, R.A.
37728 Statistical and Fuzzy Infill Drilling Recovery Models for
Carbonate Reservoirs, Wu, C.H. ,Lu, G.F. ,Gillespie, W. ,Yen, J.
30741 Application of Fuzzy Expert Systems for EOR Project Risk
Analysis, Chung, Ting-Horng ,Carroll, Herbert B. ,Lindsey, Rhonda
28239 Fuzzy Logic Controls Pressure In Fracturing Fluid Characterization
Facility, Rivera, Vincent P.
27672 An Investigation Into the Application of Fuzzy Logic to Well
Stimulation Treatment Design, Xiong, Hongjie ,Holditch, S.A.
27672 An Investigation Into the Application of Fuzzy Logic to Well
Stimulation Treatment Design, Xiong, Hongjie ,Holditch, S.A.
26430 Determining Reservoir Properties in Reservoir Studies Using a
Fuzzy Neural Network, Zhou, Cheng Dang ,Wu, Xi-Ling ,Cheng, Ju-An
26288 Novel Approaches to the Determination of Archie Parameters II:
Fuzzy Regression Analysis, Chen, H. C. ,Fang, J. H. ,Kortright, M. E.
,Chen, D. S.
26288-P Novel Approaches to the Determination of Archie Parameters II:
Fuzzy Regression Analysis, Chen, H. C. ,Fang, J. H. ,Kortright, M. E.
,Chen, D. C.
26288 Novel Approaches to the Determination of Archie Parameters II:
Fuzzy Regression Analysis, Chen, H.C. ,Fang, J.H. ,Kortright, M.E.
,Chen, D.S.
6993 Application of Genetic Algorithm on the Distribution of Gas-Lift
Injection Martinez, E.R. ,Moreno, W.J. ,Moreno, J.A. ,Maggiolo, Ricardo
26367 Design Applications of Genetic Algorithms, Jefferys, E.R.
26208 Genetic Algorithm and Its Application to Petrophysics, Fang, J.H.
,Karr, C.L. ,Stanley, D.A.
24754 Stochastic Reservoir Modeling Using Simulated Annealing and
Genetic Algorithms, Sen, Mrinal K. ,Datta-Gupta, Akhil ,Stoffa, P.L.
,Lake, L.W. ,Pope, G.A.
24754 Stochastic Reservoir Modeling Using Simulated Annealing and
Genetic Algorithm Sen, M.K. ,Gupta, Akhil Datta ,Stoffa, P.L. ,Lake,
L.W. ,Pope, G.A.
24714 Random Genetic Simulation of the Internal Geometry of Deltaic Sand
Bodies, Hu, L.Y. ,Joseph, Philippe ,Dubrule, Olivier
24714 Random Genetic Simulation of the Internal Geometry of Deltaic
Sandstone Bodies Hu, Lin Ying ,Joseph, Philippe ,Dubrule, Olivier
14591 COMPUTER-AIDED GAS PIPELINE OPERATION USING GENETIC ALGORITHMS AND
RULE LEARNING PART II: Rule Learning Control of a Pipeline Under Normal
and Abnormal Conditions, Goldberg, David E.
14590 COMPUTER-AIDED GAS PIPELINE OPERATION USING GENETIC ALGORITHMS
AND RULE LEARNING PART I: Genetic Algorithms in Pipeline Optimization,
Goldberg, David E.
SEG Technical Paper Index Results for Neural Network, Fuzzy Logic and
Genetic Algorithm:
---------------------------------------------------------------------
Huang, Z., Shimeld, J., Williamson, M. and Katsube, J., 1996,
Permeability prediction with artificial neural network modeling in the
Venture gas field, offshore
eastern Canada: 61, 2, no. 422-436, .
Li-Xin Wang and Jerry M. Mendel, 1996, Adaptive minimum prediction-error
deconvolution and source wavelet estimation using Hopfield neural
networks, Soc.
Expl. Geophys. (Transl.): Seismic source signature estimation and
measurement.
Dai, Henchang and MacBeth, Colin, 1995, Identifying P- and S-Waves Using
Artificial Neural Network: 57th Mtg. Eur. Assoc. Expl Geophys., Extended
Abstracts, , 95, Session:C039.
Treitel, Sven and Essenreiter, Robert, 1995, Predictive Deconvolution
Revisited with Neural Nets: 57th Mtg. Eur. Assoc. Expl Geophys.,
Extended Abstracts, ,
95, Session:P065.
Leggett, Miles, Smyth, Mike, Manning, Alisdair, Prescott, Cliff N. and
Edwards, Huw, 1995, Neural networks and paper seismic interpretation:
65th Annual
Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, , 95, 142-144.
Zhang, Xuegong, Li, Yanda, Hu, Qiang and Feng, Deyong, 1995, Early-stage
reservoir analysis with SOMA: A neural network approach: 65th Annual
Internat.
Mtg., Soc. Expl. Geophys., Expanded Abstracts, , 95, 138-141.
Zhang, Xuegong, Li, Yanda, Liu, Fugui and Wang, Lichun, 1995, Estimating
reservoir's lithological parameters from seismic data using neural
network: 65th Annual
Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, , 95, 606-608.
Schmidt, K. and James, C., 1995, Application of Euler deconvolution and
neural network system as interpretation aids for three component
downhole TEM data:
12th Aust. Soc. Expl. Geophys. Conf., Expl. Geophys., 26, 154-157.
Huang, Kou-Yuan and Yuan, Yune-Wei, 1995, Neural network of fuzzy
K-nearest neighbor classification rule for seismic first-arrival
picking: 65th Annual Internat.
Mtg., Soc. Expl. Geophys., Expanded Abstracts, , 95, 145-148.
Dai, Hengchang and MacBeth, Colin, 1994, A neural network picker for VSP
data: 56th Mtg. Eur. Assoc. Expl Geophys., Extended Abstracts, , 94,
Session:G032.
Thadani, S. G., 1994, Stochastic imaging of reservoir properties using
probabilistic neural networks *: 56th Mtg. Eur. Assoc. Expl Geophys.,
Extended Abstracts, ,
94, Session:H047. (* * paper cancelled)
Leggett, M., Sandham, W. A. and Durrani, T. S., 1994, 3D seismic horizon
tracking using an artificial neural network: 56th Mtg. Eur. Assoc. Expl
Geophys.,
Extended Abstracts, , 94, Session:B049.
Dai, Hengchang and MacBeth, Colin, 1994, Split shear-wave analysis using
an artificial neural network: First Break, 12, no. 12, 605-613.
Ronen, S., Hoskins, J., Schultz, P. S., Hattori, M. and Corbett, C.,
1994, Seismic-guided estimation of log properties, part 2: Using
artificial neural networks for
nonlinear attribute calibration *: The Leading Edge, 13, no. 6, 674-678.
(* Erratum in TLE-13-8-822)
Huang, Z. and Williamson, M. A., 1994, Geological pattern recognition
and modelling with a general regression neural network: Can. J. Expl.
Geophys., 30, no. 1,
60-68.
Fish, Barry C. and Kusuma, Tony, 1994, A neural network approach to
automate velocity picking: 64th Annual Internat. Mtg., Soc. Expl.
Geophys., Expanded
Abstracts, , 94, 185-188.
Thadani, Suresh G., 1994, Stochastic imaging of reservoir properties
using probabilistic neural networks *: 64th Annual Internat. Mtg., Soc.
Expl. Geophys.,
Expanded Abstracts, , 94, 189-191. (* Paper withdrawn)
Huang, Kou-Yuan and Hu, Yi-Chung, 1994, Fuzzy functional-link net for
seismic trace editing: 64th Annual Internat. Mtg., Soc. Expl. Geophys.,
Expanded
Abstracts, , 94, 200-201.
Cartabia, G., Zerilli, A. and Apolloni, B., 1994, Lineaments recognition
for potential fields images using a learning algorithm for Boltzmann
machines: 64th Annual
Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, , 94, 432-435.
Fei, Dongyu, Teng, Yu-Chiung and Kuo, John T., 1994, Detection of
conductive thick plate based on finite-element method and neural
networks: 64th Annual
Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, , 94, 636-639.
An, Ping, 1994, The effect of random noise in lateral reservoir
characterization using feed-forward neural networks: 64th Annual
Internat. Mtg., Soc. Expl.
Geophys., Expanded Abstracts, , 94, 787-790.
Cai, Yudong, 1994, The artificial neural network for research of the
recovery ratio of oil fields: 64th Annual Internat. Mtg., Soc. Expl.
Geophys., Expanded
Abstracts, , 94, 791-793.
An, Ping, Chung, Chang-Jo F. and Rencz, Andy N., 1994, A preliminary
study of alteration mapping from airborne geophysical and remote sensing
data using
feed-forward neural networks: 64th Annual Internat. Mtg., Soc. Expl.
Geophys., Expanded Abstracts, , 94, 837-840.
Schneiderbauer, Klaus, 1994, Application of a neural network in the
interpretation of electromagnetic data: 56th Mtg. Eur. Assoc. Expl
Geophys., Extended
Abstracts, , 94, Session:P039.
Winkler, Edmund, 1994, Inversion of electromagnetic data using neural
networks: 56th Mtg. Eur. Assoc. Expl Geophys., Extended Abstracts, , 94,
Session:P124.
Cai, Y., 1994, The artificial neural network approach for hydrocarbon
prediction by synthesizing multiple seismic information: 56th Mtg. Eur.
Assoc. Expl
Geophys., Extended Abstracts, , 94, Session:P153.
Wang, Jar-Long and Huang, Kou-Yuan, 1993, Neural networks for robust
recognition of seismic reflection patterns: 63rd Annual Internat. Mtg.,
Soc. Expl.
Geophys., Expanded Abstracts, , 93, 246-249.
Kusuma, Tony and Fish, Barry C., 1993, Towards more robust neural net
first-break and horizon pickers: 63rd Annual Internat. Mtg., Soc. Expl.
Geophys.,
Expanded Abstracts, , 93, 238-241.
Calderon-Macias, Carlos and Sen, Mrinal K., 1993, Geophysical
interpretation by artificial neural systems: A feasibility study: 63rd
Annual Internat. Mtg., Soc.
Expl. Geophys., Expanded Abstracts, , 93, 254-257.
Vallas, H. A., Jr., Mezzatesta, A. and Strack, K.-M., 1993,
Resistivity-log inversion using a heterogeneous artificial neural
network: 63rd Annual Internat. Mtg.,
Soc. Expl. Geophys., Expanded Abstracts, , 93, 1395. (* Neural Networks,
Expert Systems,; Fuzzy Logic & Unconventional Mathematical Techniques in
Geophysics -; Post-Convention Workshop)
An, Ping and Moon, Wooil M., 1993, Reservoir characterization using
feedforward neural networks: 63rd Annual Internat. Mtg., Soc. Expl.
Geophys., Expanded
Abstracts, , 93, 258-262.
McCormack, M. D., Zaucha, D. E. and Dushek, D. W., 1993, First-break
refraction event picking and seismic data trace editing using neural
networks *:
Geophysics, 58, no. 1, 67-78. (* Erratum in GEO-58-2-315-318)
Johnston, David H., 1993, Seismic attribute calibration using neural
networks: 63rd Annual Internat. Mtg., Soc. Expl. Geophys., Expanded
Abstracts, , 93,
250-253.
de Groot, P. F. M., Campbell, A. E., Kavli, T. and Melnyk, D., 1993,
Reservoir characterization from 3D seismic data using artificial neural
networks and stochastic modeling techniques: 55th Mtg. Eur. Assoc. Expl
Geophys., Abstracts, , 93, Session:B047.
Hansen, Kim Vejlby, 1993, Neural networks for primary reflection
identification: 63rd Annual Internat. Mtg., Soc. Expl. Geophys.,
Expanded Abstracts, , 93,
242-245.
Minior, Dorothy V. and Smith, Stanley, 1993, The use of neural networks
in the interpretation of ground-penetrating radar*: 55th Mtg. Eur.
Assoc. Expl Geophys.,
Abstracts, , 93, Session:D022. (* Paper withdrawn)
Hengchang, Dai and MacBeth, Colin, 1993, Analysis of split shear-waves
from near-offset VSP data using a neural network: 55th Mtg. Eur. Assoc.
Expl
Geophys., Abstracts, , 93, Session:C010.
Huang, Kou-Yuan and Liaw, J. Y., 1992, Neocognitron of neural network
for seismic pattern recognition: 62nd Annual Internat. Mtg., Soc. Expl.
Geophys.,
Expanded Abstracts, , 92, 26-29.
Roth, Gunter and Tarantola, Albert, 1992, Inversion of seismic waveforms
using neural networks: 62nd Annual Internat. Mtg., Soc. Expl. Geophys.,
Expanded
Abstracts, , 92, 788-791.
Cisar, Darrin, Novotny, Timothy J. and Dickerson, John, 1992,
Electromagnetic data evaluation with a neural network: Initial
investigation - underground storage
tanks: 62nd Annual Internat. Mtg., Soc. Expl. Geophys., Expanded
Abstracts, , 92, 409-411.
Schmidt, Jurandyr and Hadsell, Frank A., 1992, Neural network stacking
velocity picking: 62nd Annual Internat. Mtg., Soc. Expl. Geophys.,
Expanded Abstracts,
, 92, 18-21.
Kemp, L. Franklin, Threet, Jody R. and Veezhinathan, J., 1992, A neural
net branch and bound seismic horizon tracker: 62nd Annual Internat.
Mtg., Soc. Expl.
Geophys., Expanded Abstracts, , 92, 10-13.
Zerilla, Andrea, Massimo, Fossati, Ronchini, Gabriele and Apolloni,
Brune, 1992, Lineaments analysis for potential fields data using neural
networks: 62nd Annual
Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, , 92, 6-9.
Guo, Yi, Hansen, Richard O. and Harthill, Norman, 1992, Feature
recognition from potential fields using neural networks: 62nd Annual
Internat. Mtg., Soc. Expl.
Geophys., Expanded Abstracts, , 92, 1-5.
Murat, Michael E. and Rudman, Albert J., 1992, Automated first arrival
picking: A neural network approach: Geophys. Prosp., 40, no. 6, 587-604.
Poulton, M. M., Sternberg, B. K. and Glass, C. E., 1992, Location of
subsurface targets in geophysical data using neural networks:
Geophysics, 57, no. 12,
1534-1544.
Cary, Peter and Upham, Warren, 1992, An evaluation of neural networks:
The Leading Edge, 11, no. 9, 45-47.
Wang, L.-X. and Mendel, J. M., 1992, Adaptive minimum prediction-error
deconvolution and source wavelet estimation, using Hopfield neural
networks:
Geophysics, 57, no. 5, 670-679.
Lorenzetti, Elizabeth A., 1992, Predicting lithology from Vp and Vs
using neural networks: 62nd Annual Internat. Mtg., Soc. Expl. Geophys.,
Expanded Abstracts,
, 92, 14-17.
Michaels, Paul and Smith, R. B., 1992, Recurrent neural network
representation of the inelastic wave equation and full waveform
inversion without local minima:
62nd Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, ,
92, 22-25.
Cheng-Dang, Zhou, Yong-Zhong, Gan, Zhen-Wu, Jin and Quan, Guo Shu, 1992,
Bi-directional optimal reduction of dimensionality in multi-channel
seismic signal
processing using neural networks: 9th Aust. Soc. Expl. Geophys. Conf.,
Expl. Geophys., 23, 57-60.
Poulton, Mary M. and El Fouly, Adel, 1991, Pre-processing of GPR
signatures for cascading neural network classification: 61st Annual
Internat. Mtg., Soc. Expl.
Geophys., Expanded Abstracts, , 91, 507-509.
Huang, Kou Yuan and Yang, Feng Mei, 1991, Multi-layer perception for the
detection of seismic anomalies: 61st Annual Internat. Mtg., Soc. Expl.
Geophys.,
Expanded Abstracts, , 91, 309-312.
Roeth, Gunter and Tarantola, A., 1991, Use of neural networks for the
inversion of seismic data: 61st Annual Internat. Mtg., Soc. Expl.
Geophys., Expanded
Abstracts, , 91, 302-305.
Wiener, Jack M., Rogers, J. A., Rogers, J. R. and Moll, R. F., 1991,
Predicti
############################################################################
This message was posted through the fuzzy mailing list.
(1) To subscribe to this mailing list, send a message body of
"SUB FUZZY-MAIL myFirstName mySurname" to listproc@dbai.tuwien.ac.at
(2) To unsubscribe from this mailing list, send a message body of
"UNSUB FUZZY-MAIL" or "UNSUB FUZZY-MAIL yoursubscription@email.address.com"
to listproc@dbai.tuwien.ac.at
(3) To reach the human who maintains the list, send mail to
fuzzy-owner@dbai.tuwien.ac.at
(4) WWW access and other information on Fuzzy Sets and Logic see
http://www.dbai.tuwien.ac.at/ftp/mlowner/fuzzy-mail.info
(5) WWW archive: http://www.dbai.tuwien.ac.at/marchives/fuzzy-mail/index.html