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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:
 [1]
  1. Socorro, NM
Issue Date:
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):
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
E - FIXED CONSTRUCTIONS E21 - EARTH DRILLING E21B - EARTH DRILLING, e.g. DEEP DRILLING
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.
Weiss, William. Imbibition well stimulation via neural network design. United States.
Weiss, William. Tue . "Imbibition well stimulation via neural network design". United States. https://www.osti.gov/servlets/purl/913577.
@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 = {2007},
month = {8}
}

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Works referenced in this record:

Fractured Reservoir Characterization and Performance Forecasting Using Geomechanics and Artificial Intelligence
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