<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1646-9895</journal-id>
<journal-title><![CDATA[RISTI - Revista Ibérica de Sistemas e Tecnologias de Informação]]></journal-title>
<abbrev-journal-title><![CDATA[RISTI]]></abbrev-journal-title>
<issn>1646-9895</issn>
<publisher>
<publisher-name><![CDATA[AISTI - Associação Ibérica de Sistemas e Tecnologias de Informação]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1646-98952021000300005</article-id>
<article-id pub-id-type="doi">10.17013/risti.43.5-20</article-id>
<title-group>
<article-title xml:lang="pt"><![CDATA[Aplicação das Redes Neuronais Artificias para classificação das operações de perfuração: O caso de poços deepwater de Exploração e Produção]]></article-title>
<article-title xml:lang="en"><![CDATA[Application of Artificial Neural Networks for Classification of Drilling: Operations: The deepwater wells case of exploration and production]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Chaile]]></surname>
<given-names><![CDATA[Valter]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Moro]]></surname>
<given-names><![CDATA[Sergio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Carneiro]]></surname>
<given-names><![CDATA[Aristides]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ramos]]></surname>
<given-names><![CDATA[Ricardo F.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
<xref ref-type="aff" rid="A a"/>
<xref ref-type="aff" rid="A4"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,ISCTE-IUL, Instituto Universitário de Lisboa  ]]></institution>
<addr-line><![CDATA[Lisboa ]]></addr-line>
<country>Portugal</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Galp  ]]></institution>
<addr-line><![CDATA[Lisboa ]]></addr-line>
<country>Portugal</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Instituto Politécnico de Coimbra  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Portugal</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Universidade Autónoma de Lisboa CICEE - Centro de Investigação em Ciências Económicas e Empresariais ]]></institution>
<addr-line><![CDATA[Lisboa ]]></addr-line>
<country>Portugal</country>
</aff>
<pub-date pub-type="pub">
<day>30</day>
<month>09</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>30</day>
<month>09</month>
<year>2021</year>
</pub-date>
<numero>43</numero>
<fpage>5</fpage>
<lpage>20</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_arttext&amp;pid=S1646-98952021000300005&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_abstract&amp;pid=S1646-98952021000300005&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_pdf&amp;pid=S1646-98952021000300005&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="pt"><p><![CDATA[Resumo A aplicação de métodos automáticos para classificação de texto não estruturadas são extremamente valiosas para a indústria de Oil&amp;Gas. A perfuração é uma operação que acarreta custos elevados que são proporcionais à duração das atividades. A classificação das diversas operações durante a perfuração é muito importante para gerar premissas de duração para o projeto de novos poços. Para este artigo, dois procedimentos independentes foram realizados para identificar o melhor modelo de NPT (Non-Productive Time) e PT (Productive Time). As conclusões apontam o modelo Multi-layer Perceptron (MLP) como o melhor modelo. O sistema de classificação pode ser utilizado para produzir um relatório preciso e detalhado sobre as atividades realizadas durante a perfuração de um poço. Através desse trabalho é possível concluir que os relatórios diários de perfuração atualmente disponíveis representam uma fonte rica de informação e podem ser utilizados para melhorar o processo de construção de poços de petróleo.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The application of automatic methods for the classification of unstructured text is precious for the Oil&amp;Gas industry. Drilling is an operation that entails high costs that demands efficiency. A classification of the various operations during drilling is vital to generate assumptions of duration for the design of new wells. For this paper, two classification analyses for operation classification were conducted to identify the Non-Productive Time (NPT) and Productive Time (PT) best model. Conclusions led to Multi-layer Perceptron (MLP) as the best model. The classification system can produce an accurate and detailed report on the activities performed during the drilling of a well. Through this work, it is possible to conclude that the currently available daily drilling report represents a rich source of information and can optimize the oil well construction process.]]></p></abstract>
<kwd-group>
<kwd lng="pt"><![CDATA[redes neuronais artificiais]]></kwd>
<kwd lng="pt"><![CDATA[inteligência artificial]]></kwd>
<kwd lng="pt"><![CDATA[classificação]]></kwd>
<kwd lng="pt"><![CDATA[aprendizagem de máquina]]></kwd>
<kwd lng="pt"><![CDATA[perfuração]]></kwd>
<kwd lng="pt"><![CDATA[completação]]></kwd>
<kwd lng="en"><![CDATA[Artificial Neural Network]]></kwd>
<kwd lng="en"><![CDATA[Artificial Intelligence]]></kwd>
<kwd lng="en"><![CDATA[Classification]]></kwd>
<kwd lng="en"><![CDATA[Machine Learning]]></kwd>
<kwd lng="en"><![CDATA[Drilling]]></kwd>
<kwd lng="en"><![CDATA[Completion]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Agwu]]></surname>
<given-names><![CDATA[O. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Akpabio]]></surname>
<given-names><![CDATA[J. U.]]></given-names>
</name>
<name>
<surname><![CDATA[Alabi]]></surname>
<given-names><![CDATA[S. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Dosunmu]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Artificial intelligence techniques and their applications in drilling fluid engineering: A review]]></article-title>
<source><![CDATA[Journal of Petroleum Science and Engineering]]></source>
<year>2018</year>
<numero>167</numero>
<issue>167</issue>
<page-range>300-15</page-range></nlm-citation>
</ref>
<ref id="B2">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ahmadi]]></surname>
<given-names><![CDATA[M. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Shadizadeh]]></surname>
<given-names><![CDATA[S. R.]]></given-names>
</name>
<name>
<surname><![CDATA[Shah]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Bahadori]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[An accurate model to predict drilling fluid density at wellbore conditions]]></article-title>
<source><![CDATA[Egyptian Journal of Petroleum]]></source>
<year>2018</year>
<volume>27</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>1-10</page-range></nlm-citation>
</ref>
<ref id="B3">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Barreto]]></surname>
<given-names><![CDATA[J. M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Introdução às Redes Neurais Artificiais]]></article-title>
<source><![CDATA[V Escola Regional de Informática]]></source>
<year>1997</year>
<numero>5</numero>
<issue>5</issue>
<page-range>47-71</page-range></nlm-citation>
</ref>
<ref id="B4">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bello]]></surname>
<given-names><![CDATA[O.]]></given-names>
</name>
<name>
<surname><![CDATA[Holzmann]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Yaqoob]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Teodoriu]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Application Of Artificial Intelligence Methods In Drilling System Design And Operations: A Review Of The State Of The Art]]></article-title>
<source><![CDATA[Journal of Artificial Intelligence and Soft Computing Research]]></source>
<year>2015</year>
<volume>5</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>121-39</page-range></nlm-citation>
</ref>
<ref id="B5">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bishop]]></surname>
<given-names><![CDATA[C. M.]]></given-names>
</name>
</person-group>
<source><![CDATA[Neural Networks: A Pattern Recognition Perspective]]></source>
<year>1996</year>
<publisher-name><![CDATA[Aston University]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B6">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Chapman]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Clinton]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Kerber]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Khabaza]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Reinartz]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Shearer]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[CRISP-DM 1.0 Step-by-step data mining guide]]></article-title>
<source><![CDATA[SPSS Inc]]></source>
<year>2000</year>
<numero>9</numero>
<issue>9</issue>
<page-range>13</page-range></nlm-citation>
</ref>
<ref id="B7">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Elkatatny]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Real-Time Prediction of Rheological Parameters of KCl Water-Based Drilling Fluid Using Artificial Neural Networks]]></article-title>
<source><![CDATA[Arabian Journal for Science and Engineering]]></source>
<year>2017</year>
<volume>42</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>1655-65</page-range></nlm-citation>
</ref>
<ref id="B8">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Goldstein]]></surname>
<given-names><![CDATA[E. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Coco]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A machine learning approach for the prediction of settling velocity]]></article-title>
<source><![CDATA[Water Resources Research]]></source>
<year>2014</year>
<volume>50</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>3595-601</page-range></nlm-citation>
</ref>
<ref id="B9">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Han]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Kamber]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Pei]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The Morgan Kaufmann Series in Data Management Systems third edition]]></article-title>
<source><![CDATA[Data Mining Concepts and Techniques]]></source>
<year>2011</year>
<volume>5</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>83-124</page-range></nlm-citation>
</ref>
<ref id="B10">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Heriot]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
</person-group>
<source><![CDATA[Drilling Engineering. In: Material de apoio ao curso de MSc Petroleum Engineering]]></source>
<year>2013</year>
<publisher-name><![CDATA[Heriot Watt University]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B11">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hoffimann]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Mao]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Wesley]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Taylor]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Sequence Mining and Pattern Analysis in Drilling Reports with Deep Natural Language Processing]]></article-title>
<source><![CDATA[SPE Annual Technical Conference and Exhibition]]></source>
<year>2018</year>
<publisher-name><![CDATA[Society of Petroleum Engineers]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B12">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ian]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Eibe]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Mark Hall]]></surname>
<given-names><![CDATA[C. P.]]></given-names>
</name>
</person-group>
<source><![CDATA[Data mining: practical machine learning tools and techniques]]></source>
<year>2016</year>
<edition>4</edition>
</nlm-citation>
</ref>
<ref id="B13">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Iversen]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Gressgård]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Thorogood]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Balov]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Hepsø]]></surname>
<given-names><![CDATA[V.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Drilling Automation: Potential for Human Error]]></article-title>
<source><![CDATA[SPE Drilling &amp; Completion]]></source>
<year>2013</year>
<volume>28</volume>
<numero>01</numero>
<issue>01</issue>
<page-range>45-59</page-range></nlm-citation>
</ref>
<ref id="B14">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jeirani]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
<name>
<surname><![CDATA[Mohebbi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Artificial Neural Networks Approach for Estimating Filtration Properties of Drilling Fluids]]></article-title>
<source><![CDATA[Journal of the Japan Petroleum Institute]]></source>
<year>2006</year>
<volume>49</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>65-70</page-range></nlm-citation>
</ref>
<ref id="B15">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jiang]]></surname>
<given-names><![CDATA[Q.]]></given-names>
</name>
<name>
<surname><![CDATA[Tang]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Huang]]></surname>
<given-names><![CDATA[Q.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Stock Price Forecast Based on LSTM Neural Network]]></article-title>
<source><![CDATA[Proceedings of the Twelfth International Conference on Management Science and Engineering Management. ICMSEM 2018]]></source>
<year>2019</year>
<page-range>393-408</page-range></nlm-citation>
</ref>
<ref id="B16">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kamari]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Gharagheizi]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Shokrollahi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Arabloo]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Mohammadi]]></surname>
<given-names><![CDATA[A. H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Estimating the drilling fluid density in the mud technology: Application in high temperature and high pressure petroleum wells]]></article-title>
<source><![CDATA[Heavy Oil: Characteristics, Production and Emerging Technologies]]></source>
<year>2017</year>
<page-range>285-95</page-range><publisher-name><![CDATA[Nova Science Publishers, Inc]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B17">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Khan]]></surname>
<given-names><![CDATA[S. A. R.]]></given-names>
</name>
<name>
<surname><![CDATA[Yu]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Logistics forecasting method based on a hybrid quantum particle swarm optimization and RBF neural network model]]></article-title>
<source><![CDATA[RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao]]></source>
<year>2016</year>
<numero>18B</numero>
<issue>18B</issue>
<page-range>317-236</page-range></nlm-citation>
</ref>
<ref id="B18">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kohn]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Manaris]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Tell Me What&#8217;s Wrong: : A Python IDE with Error Messages]]></article-title>
<source><![CDATA[Proceedings of the 51st ACM Technical Symposium on Computer Science Education]]></source>
<year>2020</year>
<page-range>1054-60</page-range><publisher-name><![CDATA[ACM]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B19">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Landis]]></surname>
<given-names><![CDATA[J. R.]]></given-names>
</name>
<name>
<surname><![CDATA[Koch]]></surname>
<given-names><![CDATA[G. G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The Measurement of Observer Agreement for Categorical Data]]></article-title>
<source><![CDATA[Biometrics]]></source>
<year>1977</year>
<volume>33</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>159</page-range></nlm-citation>
</ref>
<ref id="B20">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Laureano]]></surname>
<given-names><![CDATA[R. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Caetano]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Cortez]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Predicting inpatient length of stay in a Portuguese hospital using the CRISP-DM methodology]]></article-title>
<source><![CDATA[RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao]]></source>
<year>2014</year>
<numero>13</numero>
<issue>13</issue>
<page-range>83-99</page-range></nlm-citation>
</ref>
<ref id="B21">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Moazzeni]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Nabaei]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Jegarluei]]></surname>
<given-names><![CDATA[S. G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Decision Making for Reduction of Nonproductive Time through an Integrated Lost Circulation Prediction]]></article-title>
<source><![CDATA[Petroleum Science and Technology]]></source>
<year>2012</year>
<volume>30</volume>
<numero>20</numero>
<issue>20</issue>
<page-range>2097-107</page-range></nlm-citation>
</ref>
<ref id="B22">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Moro]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Cortez]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Rita]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A divide-and-conquer strategy using feature relevance and expert knowledge for enhancing a data mining approach to bank telemarketing]]></article-title>
<source><![CDATA[Expert Systems]]></source>
<year>2018</year>
<volume>35</volume>
<numero>3</numero>
<issue>3</issue>
</nlm-citation>
</ref>
<ref id="B23">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Moro]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Laureano]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Cortez]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<source><![CDATA[Using data mining for bank direct marketing: An application of the crisp-dm methodology]]></source>
<year>2011</year>
</nlm-citation>
</ref>
<ref id="B24">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Murillo]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Neuman]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Samuel]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Pipe Sticking Prediction and Avoidance Using Adaptive Fuzzy Logic Modeling]]></article-title>
<source><![CDATA[SPE Production and Operations Symposium]]></source>
<year>2009</year>
<publisher-name><![CDATA[Society of Petroleum Engineers]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B25">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Osman]]></surname>
<given-names><![CDATA[E. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Aggour]]></surname>
<given-names><![CDATA[M. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Determination of Drilling Mud Density Change with Pressure and Temperature Made Simple and Accurate by ANN]]></article-title>
<source><![CDATA[Middle East Oil Show]]></source>
<year>2003</year>
<publisher-name><![CDATA[Society of Petroleum Engineers]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B26">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ozbayoglu]]></surname>
<given-names><![CDATA[E. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Ozbayoglu]]></surname>
<given-names><![CDATA[M. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Estimating Flow Patterns and Frictional Pressure Losses of Two-Phase Fluids in Horizontal Wellbores Using Artificial Neural Networks]]></article-title>
<source><![CDATA[Petroleum Science and Technology]]></source>
<year>2009</year>
<volume>27</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>135-49</page-range></nlm-citation>
</ref>
<ref id="B27">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rable]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
</person-group>
<source><![CDATA[The Future is Here: 3 Ways AI Roots Itself in O&amp;G in the Surge Magazine]]></source>
<year>2017</year>
</nlm-citation>
</ref>
<ref id="B28">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ribeiro]]></surname>
<given-names><![CDATA[M. T.]]></given-names>
</name>
<name>
<surname><![CDATA[Singh]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Guestrin]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[&#8220;Why Should I Trust You?&#8221;: Explaining the Predictions of Any Classifier]]></article-title>
<source><![CDATA[Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining]]></source>
<year>2016</year>
<page-range>1135-44</page-range><publisher-name><![CDATA[ACM]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B29">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rooki]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Ardejani]]></surname>
<given-names><![CDATA[F. D.]]></given-names>
</name>
<name>
<surname><![CDATA[Moradzadeh]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Mirzaei]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Kelessidis]]></surname>
<given-names><![CDATA[V.]]></given-names>
</name>
<name>
<surname><![CDATA[Maglione]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Norouzi]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Optimal determination of rheological parameters for herschel-bulkley drilling fluids using genetic algorithms (GAs)]]></article-title>
<source><![CDATA[Korea-Australia Rheology Journal]]></source>
<year>2012</year>
<volume>24</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>163-70</page-range></nlm-citation>
</ref>
<ref id="B30">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sanchez-Pi]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Martí]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Garcia]]></surname>
<given-names><![CDATA[A. C. B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Text Classification Techniques in Oil Industry Applications]]></article-title>
<source><![CDATA[International Joint Conference SOCO&#8217;13-CISIS&#8217;13-ICEUTE&#8217;13]]></source>
<year>2014</year>
<page-range>211-20</page-range></nlm-citation>
</ref>
<ref id="B31">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Shahdi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Arabloo]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Application of SVM Algorithm for Frictional Pressure Loss Calculation of Three Phase Flow in Inclined Annuli]]></article-title>
<source><![CDATA[Journal of Petroleum &amp; Environmental Biotechnology]]></source>
<year>2014</year>
<volume>05</volume>
<numero>03</numero>
<issue>03</issue>
</nlm-citation>
</ref>
<ref id="B32">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sidahmed]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Coley]]></surname>
<given-names><![CDATA[C. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Shirzadi]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Augmenting Operations Monitoring by Mining Unstructured Drilling Reports]]></article-title>
<source><![CDATA[SPE Digital Energy Conference and Exhibition]]></source>
<year>2015</year>
<page-range>403-15</page-range></nlm-citation>
</ref>
<ref id="B33">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Silva]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Barreiros]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Intelligent Analysis Program Applied to Production Logs in Oil and Gas Wells]]></article-title>
<source><![CDATA[IEEE Latin America Transactions]]></source>
<year>2006</year>
<volume>4</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>353-8</page-range></nlm-citation>
</ref>
<ref id="B34">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Silva]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Martins]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Doria Neto]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Rodrigues]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Da Mata]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Optimization of the Oil Production Fields Submitted the Water Injection, Using the Algorithm NSGA-II]]></article-title>
<source><![CDATA[IEEE Latin America Transactions]]></source>
<year>2016</year>
<volume>14</volume>
<numero>9</numero>
<issue>9</issue>
<page-range>4166-72</page-range></nlm-citation>
</ref>
<ref id="B35">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Siruvuri]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Nagarakanti]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Samuel]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Stuck Pipe Prediction and Avoidance: A Convolutional Neural Network Approach]]></article-title>
<source><![CDATA[IADC/SPE Drilling Conference]]></source>
<year>2006</year>
<publisher-name><![CDATA[Society of Petroleum Engineers]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B36">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Smith]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
</person-group>
<source><![CDATA[Python, the Fundamentals]]></source>
<year>2020</year>
</nlm-citation>
</ref>
<ref id="B37">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Thomas]]></surname>
<given-names><![CDATA[J. E.]]></given-names>
</name>
</person-group>
<source><![CDATA[Fundamentos de engenharia de petro&#769;leo]]></source>
<year>2001</year>
<publisher-name><![CDATA[Intercie&#770;ncia]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B38">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Toreifi]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Rostami]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Manshad]]></surname>
<given-names><![CDATA[A. K.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[New method for prediction and solving the problem of drilling fluid loss using modular neural network and particle swarm optimization algorithm]]></article-title>
<source><![CDATA[Journal of Petroleum Exploration and Production Technology]]></source>
<year>2014</year>
<volume>4</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>371-9</page-range></nlm-citation>
</ref>
<ref id="B39">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Pu]]></surname>
<given-names><![CDATA[X.-L.]]></given-names>
</name>
<name>
<surname><![CDATA[Tao]]></surname>
<given-names><![CDATA[H.-Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A Support Vector Machine Approach for the Prediction of Drilling Fluid Density at High Temperature and High Pressure]]></article-title>
<source><![CDATA[Petroleum Science and Technology]]></source>
<year>2012</year>
<volume>30</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>435-42</page-range></nlm-citation>
</ref>
<ref id="B40">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhu]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[G. X.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[Q. Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Research of Prewarning Pipe-Sticking Based on Neural Network]]></article-title>
<source><![CDATA[Applied Mechanics and Materials]]></source>
<year>2013</year>
<numero>325-326</numero>
<issue>325-326</issue>
<page-range>1734-7</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
