Imbibition well stimulation via neural network design

Weiss, William

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Title: Imbibition well stimulation via neural network design

Abstract

A method for stimulation of hydrocarbon production via imbibition by utilization of surfactants. The method includes use of fuzzy logic and neural network architecture constructs to determine surfactant use.

Inventors:

Weiss, William ^[1]

Socorro, NM

Issue Date:: Tue Aug 14 00:00:00 EDT 2007

Research Org.:: Correlations Co Inc

Sponsoring Org.:: USDOE

OSTI Identifier:: 913577

Patent Number(s):: 7255166

Application Number:: 10/901,865

Assignee:: Weiss, William (Socorro, NM)

Patent Classifications (CPCs):: E - FIXED CONSTRUCTIONS E21 - EARTH DRILLING E21B - EARTH DRILLING, e.g. DEEP DRILLING

Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y10 - TECHNICAL SUBJECTS COVERED BY FORMER USPC Y10S - TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS

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E - FIXED CONSTRUCTIONS E21 - EARTH DRILLING E21B - EARTH DRILLING, e.g. DEEP DRILLING
E21B43/16 - Enhanced recovery methods for obtaining hydrocarbons

Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y10 - TECHNICAL SUBJECTS COVERED BY FORMER USPC Y10S - TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
Y10S706/929 - Geological, e.g. seismology

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DOE Contract Number:: FG03-01ER83226

Resource Type:: Patent

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING

Citation Formats


                    Weiss, William. Imbibition well stimulation via neural network design.  United States: N. p., 2007. 
        Web.

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                    Weiss, William. Imbibition well stimulation via neural network design.  United States.

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                    Weiss, William. Tue .  
        "Imbibition well stimulation via neural network design".  United States.  https://www.osti.gov/servlets/purl/913577.

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@article{osti_913577,

  title        = {Imbibition well stimulation via neural network design},

  author       = {Weiss, William},

  abstractNote = {A method for stimulation of hydrocarbon production via imbibition by utilization of surfactants. The method includes use of fuzzy logic and neural network architecture constructs to determine surfactant use.},

  doi          = {},

  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Aug 14 00:00:00 EDT 2007},

  month        = {Tue Aug 14 00:00:00 EDT 2007}

}

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Works referenced in this record:

Fractured Reservoir Characterization and Performance Forecasting Using Geomechanics and Artificial Intelligence
conference, April 2013

Ouenes, A.; Richardson, S.; Weiss, W. W.
SPE Annual Technical Conference and Exhibition
https://doi.org/10.2118/30572-MS

One Core, Few Modern Logs, and Limited Production Data: Is Reliable Reservoir Characterization Possible?
conference, April 2013

Chawathe, A.; Ouenes, A.; Ali, M.
SPE Western Regional Meeting
https://doi.org/10.2118/38260-MS

Obtain an Optimum Artificial Neural Network Model for Reservoir Studies
conference, April 2013

Du, Yuqi; Weiss, W. W.; Jianyun, Xu
SPE Annual Technical Conference and Exhibition
https://doi.org/10.2118/84445-MS

Integrating Core Porosity and Sw Measurements with Log Values
conference, April 2013

Weiss, W. W.; Wo, S.; Balch, R. S.
SPE Rocky Mountain Regional Meeting
https://doi.org/10.2118/55642-MS

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Title: Imbibition well stimulation via neural network design

Abstract

Citation Formats

Fractured Reservoir Characterization and Performance Forecasting Using Geomechanics and Artificial Intelligence conference, April 2013

One Core, Few Modern Logs, and Limited Production Data: Is Reliable Reservoir Characterization Possible? conference, April 2013

Obtain an Optimum Artificial Neural Network Model for Reservoir Studies conference, April 2013

Integrating Core Porosity and Sw Measurements with Log Values conference, April 2013

Fractured Reservoir Characterization and Performance Forecasting Using Geomechanics and Artificial Intelligence
conference, April 2013

One Core, Few Modern Logs, and Limited Production Data: Is Reliable Reservoir Characterization Possible?
conference, April 2013

Obtain an Optimum Artificial Neural Network Model for Reservoir Studies
conference, April 2013

Integrating Core Porosity and Sw Measurements with Log Values
conference, April 2013