Improving the simulation of a waterflooding recovery process using artificial neural networks

Gil, E. S.

doi:10.33915/etd.1071

Cited by 2 publications

(4 citation statements)

References 5 publications

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“…A lot of work was done previously and thesis documents submitted on works which involved prediction of porosity and permeability using neural network. One previous work by Gil 7 used random selection of test set through a random number generator for training purposes. He used the porosity and permeability obtained from the prediction in his simulation study.…”

Section: Previous Work In Neural Network Predictionmentioning

confidence: 99%

“…This data was, however, changed in the simulation process for the history matching purposes. with the data that was used for the simulation by Gil 7 and also those used in this study.…”

Section: Fluid Propertiesmentioning

confidence: 99%

“…A.N.N has been and is being used widely to predict permeability distribution. Previous work7 used random selection of test set through a random number generator for training purposes. However recent study 5 uses a predefined test set, the results of which were used for the work under study here.…”

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confidence: 99%

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Using waterflood performance to characterize flow-units in a heterogeneous reservoir

Alla¹

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Section: Previous Work In Neural Network Predictionmentioning

confidence: 99%

“…This data was, however, changed in the simulation process for the history matching purposes. with the data that was used for the simulation by Gil 7 and also those used in this study.…”

Section: Fluid Propertiesmentioning

confidence: 99%

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Using waterflood performance to characterize flow-units in a heterogeneous reservoir

Alla¹

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“…Gil, E. 42 The third method utilized trial and error to define the best possible test set. He concluded in this study that using each of these methods improved prediction permeability in some of the study wells but not in all of them.…”

Section: 817b Studies Using Ann In Jacksonburg-stringtown Fieldmentioning

confidence: 99%

Identification of technical barriers and preferred practices for oil production in the Appalachian Basin

Paez¹,

Sandra²

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The Appalachian Basin is characterized by great number of stripper wells and marginally producing oilfields that face a number of production problems. The purpose of this study was to identify the main problematic issues and preferred solutions for oil production in the Appalachian Basin. Investigation and identification of oil production problems and preferred solutions began with searches in the Society of Petroleum Engineer (SPE) library, and Petroleum Technology Transfer Council (PTTC) website. In addition, journals, workshop, conference were used to find additional information. Formal interviews were arranged with oil producers to gain more insight into problems in the Appalachian Basin. Accordingly, the following production problems were identified and ranked in order of decreasing importance: water production, poor understanding of reservoir heterogeneity, limited availability of compatible water for water injection, lack of sufficient reservoir data such as permeability, porosity, and primary production data for reservoir characterization, and paraffin and asphaltene causing operational issues. The technologies that are investigated included: water controls treatment, water-handling methods, and reservoir characterization using Artificial Neural Networks, paraffin and asphaltene control. In addition, corrosion problems and electrical cost reduction are discussed. Finally and the most importantly, I would like to dedicate my thesis research work to all of my family. Especially my parents, Elizabeth and Fernando for always being excellent examples for me, for their dedication, unconditional help, support, encouragement, and love that they have given to me throughout my life. I am so proud to be their daughter. I would like to thank my sisters Maria and Carla, for being my inspiration and motivation for doing the right things. I hope my example of perseverance and sacrifice with my studies will influence their goals and inspirations. To my grandmothers, Delia and Ana for always keeping an eye on me. I am so glad to have wonderful grandmothers like them. To David for his encouragement, help, advice and love he gave to me, I really appreciate his dedication. In addition, I am sincerely grateful to all of my friends that are thousands of miles away whose encouragement and motivation that was given to me to continue with the project. You guys are really wonderful friends. To all the above mentioned I would like to give my sincerest love. v TABLE OF CONTENTS ABSTRACT……………………………………………………………………………...ii ACKNOWLEDGEMENTS…………………………………………………………….iii TABLE OF CONTENTS………………………………………………………………..v LIST OF FIGURES…………………………………………………………………….ix LIST OF TABLES…………………………………………………………………….xiii

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Improving the simulation of a waterflooding recovery process using artificial neural networks

Abstract: The waterflood performance of the dual five-spot pilot project in the Stringtown oil field, situated in West Virginia, has been studied. A numerical simulator, called BOAST98, was used for the simulation purposes, after developing a reservoir description.

Cited by 2 publications

References 5 publications

Using waterflood performance to characterize flow-units in a heterogeneous reservoir

Using waterflood performance to characterize flow-units in a heterogeneous reservoir

Identification of technical barriers and preferred practices for oil production in the Appalachian Basin

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