RESSALVA Atendendo solicitação do(a) autor(a), o texto completo desta Dissertação será disponibilizado somente a partir de 07/02/2025 DIUNAY ZULIANI MANTEGAZINI Pre-operational drilling test applied to carbonate reservoirs: a multi-objective optimization approach analysis of ROP and MSE Guaratinguetá - SP 2023 UNIVERSIDADE ESTADUAL PAULISTA “JÚLIO DE MESQUITA FILHO” Faculdade de Engenharia e Ciências de Guaratinguetá Diunay Zuliani Mantegazini Pre-operational drilling test applied to carbonate reservoirs: a multi-objective optimization approach analysis of ROP and MSE Dissertation presented to the Faculdade de Engenharia e Ciências - Campus de Guaratinguetá (FEG), from the Universidade Estadual Paulista (UNESP), as part of the fulfillment to award the degree of Doctor in Mechanical Engineering. Supervisor: Prof. Dr. Andreas Nascimento. Co-supervisor: Prof. Dr. João Andrade de Carvalho Junior. Guaratinguetá - SP 2023 M292p Mantegazini, Diunay Zuliani Pre-operational drilling test applied to carbonate reservoirs: a multi-objective optimization approach analysis of ROP and MSE / Diunay Zuliani Mantegazini - Guaratinguetá, 2023. 102 f : il. Bibliography: f. 79-89 Thesis (Doctor) – Unesp São Paulo State University, School of Engineering, Guaratinguetá, 2023. Advisior: Prof. Dr. Andreas Nascimento Co-Advisior: Prof. Dr. João Andrade de Carvalho Junior 1. Hydrocarbon reservoirs. 2. Oil wells - Drilling. 3. Stratigraphic drilling. 4. Petroleum - Geology. I. Títle. CDU 622.323(043) Luciana Máximo Librarian/CRB-8 3595 unesp UNIVERSIDADE ESTADUAL PAULISTA CAMPUS DE GUARATINGUETÁ DIUNAY ZULIANI MANTEGAZINI ESTA TESE FOI JULGADA ADEQUADA PARA A OBTENÇÃO DO TÍTULO DE “DOUTOR EM ENGENHARIA MECÂNICA” PROGRAMA: ENGENHARIA MECÂNICA CURSO: DOUTORADO APROVADA EM SUA FORMA FINAL PELO PROGRAMA DE PÓS-GRADUAÇÃO Prof. Dr. Manoel Cléber de Sampaio Alves Coordenador B A N C A E X A M I N A D O R A: Prof. Dr. ANDREAS NASCIMENTO Orientador - UNIFEI participou por videconferência Prof. Dr. OLDRICH JOEL ROMERO UFES participou por videconferência Prof. Dr. ROBERTO SILVA NETTO Faculdade de Engenharia de Sorocaba participou por videconferência Prof. Dr. MAURO HUGO MATHIAS UNESP participou por videconferência Prof. Dr. MARCOS VALERIO RIBEIRO UNESP participou por videconferência FEVEREIRO de 2023 CURRICULUM INFORMATION DIUNAY ZULIANI MANTEGAZINI BIRTH - Date: 02 nd April 1992; - Place: São Mateus, Espírito Santo, Brazil; FILIATION - Mother: Maria Aparecida Vignatti Mantegazini; - Father: Juberto Mantegazini; 2010/2014 - Degree: Engineer in Mechanical Engineering; - University: North Capixaba Faculty of São Mateus (MULTIVIX); 2018/2020 - Degree: Master of Science in Energy; - University: Federal University of Espírito Santo (UFES); 2020/2023 - Degree: Doctor in Mechanical Engineering; - University: São Paulo State University (UNESP). I dedicate this work to my family. ACKNOWLEDGMENT To my parents, Juberto Mantegazini and Maria Aparecida Vignatti Mantegazini, and my sister Dhangeli Zuliani Mantegazini, for the support, education, and advice. To the Supervisor Prof. Dr. Andreas Nascimento, for the teaching, guidance, competence, professionalism, support, friendship and dedication in developing this dissertation. To co-supervisor Prof. Dr. João Andrade de Carvalho Júnior for the support. To the São Paulo State University (UNESP) and Post-graduation technical session of FEG for all the assistance, support, and dataset provided. To the Coordination for the Improvement of Higher Education Personnel – Brazil (CAPES) and National Council for Scientific and Technological Development (CNPq). This work was carried out with the support of the Coordination for the Improvement of Higher Education Personnel – Brazil (CAPES) – Financing Code 001. ABSTRACT With the discovery of Pre-salt hydrocarbon reservoirs, appeared new challenges. One of the main challenges is the necessity of optimizing drilling processes due to high related operational costs. Drilling costs are considerably high, which leads the Oil and Gas (O&G) industry to search for innovative and entrepreneur methods. The Mechanic Specific Energy (MSE) is a parameter that is being used along drilling operations; coupling of MSE and Rate of Penetration (ROP) is a method that allows identifying ideal conditions during the drilling process aimed at efficiency enhancement. In addition, the performance of the drilling process can be estimated through pre-operational tests, which consist in continuously testing applied drilling mechanic parameters, such as Drill-String Rotary Speed (RPM) and Weigh-On-Bit (WOB), looking for optimum sets would ultimately provide the most desirable ROP. Thus, the goal of this dissertation was to analyze field data from Pre-salt layers operations, using a multi-objective optimization based on a play-back methodology for pre-operational drilling tests, through the ideal combination, simultaneously aiming at the highest possible ROP and the lowest achievable MSE. In addition, the Response Surface Method (RSM) was used to explore the effects of input variables on response variables at a 95% confidence level. The results showed that the new concept of pre-operational tests based on MSE and ROP proved to be effective in the drilling process optimization. The combination between the highest ROP and the lowest MSE allows for performing an efficient drilling process. In terms of parameters setting interval in pre-operational drilling-tests, for WOB, intervals of 5 and 7 [klb] showed to be sufficient for presenting reliable results. Through the parameters obtained from pre-operational tests, it could be estimated eventual cost-saving and time-saving values ranged from USD 1,056,180.72 to 1,151,898.30 and 19.50 to 21.27 [h], respectively. KEYWORDS: Desirability; Drill-rate test; Mechanical Specific Energy; Pre-salt layers; Oil & Gas. RESUMO Com a descoberta dos reservatórios de hidrocarbonetos do Pré-sal, surgiram novos desafios. Um dos principais desafios é a necessidade de otimizar o processo de perfuração devido aos altos custos operacionais. Os custos de perfuração são consideravelmente altos, o que leva a indústria de Petróleo e Gás (O&G) a buscar métodos inovadores e empreendedores. A Energia Mecânica Específica (MSE) é um parâmetro que está sendo utilizado ao longo das operações de perfuração; o acoplamento da MSE e da Taxa de Penetração (ROP) é um método que permite identificar condições ideais durante o processo de perfuração visando o aumento da eficiência operacional. Além disso, o desempenho do processo de perfuração pode ser estimado por meio de testes pré-operacionais, que consistem em testar continuamente parâmetros mecânicos de perfuração, como a velocidade de rotação da coluna de perfuração (RPM) e o peso aplicado sobre a broca (WOB), procurando obter conjuntos ótimos que fornecam a ROP desejável. Dessa forma, o objetivo desta dissertação de doutorado foi analisar os dados de campo das operações de perfuração no Pré-sal, utilizando a otimização multi-objetivo baseada na metodologia play-back para testes pré-operacionais, através da combinação ideal, visando simultaneamente o maior ROP possível e o menor MSE alcançável. Além disso, o Método de Superfície de Resposta (RSM) foi usado para explorar os efeitos das variáveis de entrada sobre as variáveis de resposta a um nível de confiança de 95%. Os resultados mostraram que o novo conceito de testes pré-operacionais baseados na MSE e ROP se mostrou eficaz na otimização do processo de perfuração. A combinação entre a mais elevada ROP e a menor MSE permite realizar um processo de perfuração eficiente. Em termos de intervalo de parametrização em testes de perfuração pré-operacionais, para WOB, os intervalos de 5 e 7 [klb] mostraram-se suficientes para apresentar resultados confiáveis. Através dos parâmetros obtidos nos testes pré-operacionais, pode-se estimar eventuais valores de economia de custo e tempo variando de 1.056.180,72 a 1.151.898,30 [USD] e de 19,50 a 21,27 [h], respectivamente. PALAVRAS-CHAVE: Desejabilidade; Teste da taxa de perfuração; Energia Mecânica Específica; Pré-sal; Óleo & Gás. LIST OF FIGURES Figure 1- Primary energy consumption by energy source in the world (quadrillion British thermal units). ........................................................................................................................... 21 Figure 2 - Relevance of the O&G industry in Brazil. ............................................................... 22 Figure 3 - Location of the pre-salt layer. .................................................................................. 23 Figure 4 - Location of the SEOBB. .......................................................................................... 24 Figure 5 - Main forms of O&G exploration in Brazil. ............................................................. 24 Figure 6 - Schematic view of a rotary drilling rig. ................................................................... 25 Figure 7 - Schematic drawing of the top drive. ........................................................................ 26 Figure 8 - Circulation system. .................................................................................................. 27 Figure 9 - Workflow for a well design. .................................................................................... 29 Figure 10 - Basic points of a directional well trajectory. ......................................................... 31 Figure 11 - Trajectory correction effect. .................................................................................. 32 Figure 12 - Operational window example. ............................................................................... 33 Figure 13 - Oil well phases. ...................................................................................................... 36 Figure 14 - Main differences between: a) PDC drill-bits; b) conical roller drill-bits. .............. 39 Figure 15 - PDC-roller hybrid drill-bit (right) combines roller cone drill-bit (middle) and PDC drill-bit (left). ............................................................................................................................ 39 Figure 16 - Main components of the drill-string. ..................................................................... 40 Figure 17 - Vibrations in the drill-string. ................................................................................. 50 Figure 18 - Drill-rate test curve. ............................................................................................... 52 Figure 19 - MSE versus ROP plot with the indication of efficient/inefficient regions. ........... 53 Figure 20 - Tukey's box plot method. ....................................................................................... 55 Figure 21 - Example of the drill-rate test to intervals of: (a) 3 [klb]; (b) 5 [klb]; (c) 7 [klb]. .. 56 Figure 22 - Multi-objective optimization. ................................................................................ 57 Figure 23 - Code used to automate the different scenarios. ..................................................... 58 Figure 24 - Tukey's box plot method: a) WOB; b) RPM; c) TOB; d) FLOW; e) ROP. ......... 59 Figure 25 - Input and response variables. ................................................................................. 60 Figure 26 - Residual plots: a) normal probability plot; b) versus fit; c) versus order. ............. 62 Figure 27 - surface plots: ROP vs. WOB and RPM; b) ROP vs. WOB and TOB; c) ROP vs. WOB and FLOW; d) ROP vs. RPM and TOB; e) ROP vs. RPM and FLOW; f) ROP vs. TOB and FLOW. ............................................................................................................................... 64 Figure 28 - Residual plots: a) normal probability plot; b) versus fit; c) versus order. ............. 66 Figure 29 - Surface plots: MSE vs. WOB and RPM; b) MSE vs. WOB and TOB; c) MSE vs. WOB and FLOW; d) MSE vs. RPM and TOB; e) MSE vs. RPM and FLOW; f) MSE vs. TOB and FLOW. ............................................................................................................................... 67 Figure 30 - WOB's groups of 3 [klb]: (a) ROP vs. WOB plot; (b) MSE vs. ROP plot. ........... 69 Figure 31 - WOB's groups of 5 [klb]: (a) ROP vs. WOB plot; (b) MSE vs. ROP plot. ........... 69 Figure 32 - WOB's groups of 7 [klb]: (a) ROP vs. WOB plot; (b) MSE vs. ROP plot. ........... 70 Figure 33- Relation between the MSE vs. WOB plot for several grouping: (a) 3 [klb]; (b) 5 [klb]; (c) 7 [klb]. ....................................................................................................................... 71 Figure 34 - Distribution of dataset. ........................................................................................... 90 LIST OF TABLES Table 1 - Results obtained by simulation of the different ROP models. .................................. 43 Table 2 - Values of weights used in the optimization process. ................................................ 58 Table 3 - Summary of statistical information. .......................................................................... 61 Table 4 - Effect of factors on ROP. .......................................................................................... 63 Table 5 - Effect of factors on MSE. ......................................................................................... 67 Table 6 - Multi-objective optimization for grouping of 3 [klb]. .............................................. 72 Table 7 - Multi-objective optimization for grouping of 5 [klb]. .............................................. 73 Table 8 - Multi-objective optimization for 110 rev/min and 7 [klb]. ....................................... 73 Table 9 - Cost analysis of parameters used during the drilling of zone 2. ............................... 74 Table 10 - Cost analysis related to the parameters and values presented in Table 6. .............. 75 Table 11 - Cost analysis related to the parameters and values presented in Table 7. .............. 75 Table 12 - Cost analysis related to the parameters and values presented in Table 8. .............. 76 Table 13 - Effect of factors on ROP using heteroscedasticity-consistent standard errors (variant HC0). ........................................................................................................................... 91 Table 14 - Effect of factors on ROP using heteroscedasticity-consistent standard errors (variant HC1). ........................................................................................................................... 91 Table 15 - Effect of factors on ROP using heteroscedasticity-consistent standard errors (variant HC3). ........................................................................................................................... 92 Table 16 - Effect of factors on MSE using heteroscedasticity-consistent standard errors (variant HC0). ........................................................................................................................... 92 Table 17 - Effect of factors on MSE using heteroscedasticity-consistent standard errors (variant HC1). ........................................................................................................................... 93 Table 18 - Effect of factors on MSE using heteroscedasticity-consistent standard errors (variant HC3). ........................................................................................................................... 93 Table 19 - Pre-salt dataset. ....................................................................................................... 94 LIST OF ABBREVIATIONS AND INITIALS ABM Air-Based Muds ANN Artificial Neural Networks ANP Brazilian National Agency of Petroleum, Natural Gas and Biofuels (Agênica Nacional do Petróleo, Gás Natural e Biocombustíveis) BOP Blowout Preventer BTU British Thermal Units BYM Bourgoyone and Young model CAPES Coordination for the Improvement of Higher Education Personnel (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) CCS Confined Compressive Strength DOT Drill-Off Test DRT Drill-Rate Test EFFM Drilling Efficiency Factor EIA Energy Information Administration EOB End-Of-Build EOD End-Off-Drop FEG Faculty of Engineering and Sciences - Campus of Guaratinguetá (Faculdade de Engenharia e Ciências - Campus de Guaratinguetá) FLOW Flow-Rate GRG Generalized Reduced Gradient HAC Heteroscedasticity and Autocorrelation Consistent HCCME Heteroscedasticity Consistent Covariance Matrix Estimators HPHT High Pressure High Temperature HSME Hydro-Mechanical Specific Energy IQR Interquartile range KOP Kick-Off Point LTB Larger-The-Better LWD Logging While Drilling MD Measured Depth MLR Multiple Linear Regression MSE Mechanical Specific Energy MWD Measurement While Drilling NPT Non-Productive Time NTB Nominal-The-Best OBM Oil-Based Muds O&G Oil and Gas PDC Polycrystalline Diamond Compact; PDM Positive Displacement Motor ROP Rate of Penetration RSM Response Surface Methodology RPM Drill-String Rotary Speed SBM Synthetic-Based Mud SEOBB Southeastern Offshore Brazilian Basins SSI Stick Skip Index STB Smaller-The-Better TOB Torque-On-Bit UCS Unconfined Compressive Strength WBM Water-Based Mud WOB Weight-On-Bit LIST OF SYMBOLS 𝑎1 Formation strength and drilling fluid properties coefficient 𝑎2 Normal compaction trend coefficient 𝑎3 Under-compaction and pore pressure coefficient 𝑎4 Differential pressure coefficient 𝑎5 Constant dependent on drilling conditions and WOB behavior 𝑎6 Constant dependent on drilling conditions and rotary speed behavior 𝑎7 Teeth-cutters wear coefficient 𝑎8 Hydraulic coefficient Ab Drill-bit cross-section area Db Drill-bit diameter gc Mass conversion HL Lower quartile HU Upper quartile K Constant dependent drill-bit dullness, formation and drilling conditions L Low limit T Target U Upper limit X Input variables X1 WOB X2 RPM X3 TOB X4 FLOW Y Response variable Y1 ROP Y2 MSE β0 Constant coefficient βj Linear coefficient βjj Quadratic coefficient βij Interaction coefficient η Efficiency of PDM n Dummy factor for energy reduction μb Bit-Specific Coefficient of Sliding Friction μs Coefficient of friction of drill-string γb Inclination of the bottom hole ∆Pb Pressure drop across the drill-bit ∆Pm Differential pressure across the drill-bit TABLE OF CONTENT 1 INTRODUCTION ............................................................................................... 18 1.1 OBJECTIVES ........................................................................................................ 19 1.2 DISSERTATION STRUCTURE .......................................................................... 20 2 LITERATURE REVIEW ................................................................................... 21 2.1 PRE-SALT ............................................................................................................. 21 2.2 DRILLING EQUIPMENT .................................................................................... 25 2.2.1 Rotary system ....................................................................................................... 26 2.2.2 Well safety system ................................................................................................ 27 2.2.3 Circulation system ............................................................................................... 27 2.2.4 Monitoring system ............................................................................................... 28 2.3 WELL DESIGN..................................................................................................... 28 2.3.1 Well prospect ........................................................................................................ 29 2.3.2 Planning the trajectory........................................................................................ 30 2.3.3 Geopressure .......................................................................................................... 33 2.3.4 Drilling Fluid ........................................................................................................ 34 2.2.5 Casing and cementing process ............................................................................ 36 2.2.6 Drill-bits and drill-string ..................................................................................... 37 2.2.7 Blowout preventer ............................................................................................... 41 2.2.8 Drilling optimization ........................................................................................... 41 2.2.9 Well completion ................................................................................................... 48 2.4 VIBRATION MODELING ................................................................................... 49 2.5 PRE-OPERATIONAL TEST ................................................................................ 51 3 METHODOLOGY .............................................................................................. 54 3.1 DATASET ACQUISITION .................................................................................. 54 3.2 OUTLIER ELIMINATION ................................................................................... 54 3.3 DRILL-RATE TEST ............................................................................................. 55 3.4 MULTI-OBJECTIVE OPTIMIZATION .............................................................. 57 4 RESULTS AND DISCUSSION .......................................................................... 59 4.1 OUTLIER ELIMINATION ................................................................................... 59 4.2 TRADITIONAL METHOD OF ANALYSIS ....................................................... 60 4.2.1 2D Analysis ........................................................................................................... 60 4.2.2 Response surface methodology ........................................................................... 62 4.3 DRILL-RATE TEST ............................................................................................. 69 4.4 MULTI-OBJECTIVE OPTIMIZATION .............................................................. 71 4.5 ANALYSIS OF COSTS ........................................................................................ 74 5 CONCLUSION .................................................................................................... 77 REFERENCES .................................................................................................... 79 APPENDIX A ....................................................................................................... 90 APPENDIX B ....................................................................................................... 91 APPENDIX C ....................................................................................................... 94 18 1 INTRODUCTION The registered increasing demand for energy in general and hydrocarbons within the next few years, forecasted by different energy outlook reports in recent years, also supported the Oil and Gas (O&G) industry in exploring reserves in more challenging environments (NASCIMENTO, 2016; BP, 2023; EIA, 2023). Drilling wells in challenging environments involves high costs, mostly related to well construction and drilling processes (BARBOSA et al., 2019). Thus, it is still very important to focus on efficiency enhancements, which may allow potential time saving and operational costs reduction (SOARES; DAIGLE; GRAY, 2016). The exploration of Pre-salt layers serves as an example of the challenges and difficulties faced during drilling activities. In this case, the challenges are related to the operations in ultradeep water, reservoirs located below 5,000 [m] and thick evaporite layers, high pressure and high temperature, offshore located (up to 300 [km] of the coast), and considerably abrasive carbonate rock reservoir (NASCIMENTO et al., 2015). In addition to the challenges indicated above, the definition of optimum drilling parameters while drilling, such as Drill- String Rotary Speed (RPM), Weight-On-Bit (WOB), Torque-On-Bit (TOB), and Flow-Rate (FLOW), it is still important and a not so a trivial activity. Within the O&G industry, these are common nomenclatures and respective abbreviations used when referring to such parameters. The main drilling performance indicators are the rate of penetration (ROP) and Mechanical Specific Energy (MSE). ROP is an indication of how fast the well is drilled in terms of the length of hole drilled per unit of time (SOARES; DAIGLE; GRAY, 2016). While the MSE measures the amount of energy necessary to remove a unit volume of rock (TEALE, 1965). The combination between the highest ROP and the lowest MSE has not only the potential to reduce the costs of the drilling process, but also to reduce operating time. Once the drilling time is reduced, the time in which geological formations are exposed is also reduced, reducing the chances of destabilization and operational risks (GANDELMAN, 2012). ROP prediction has been the subject of several types of research over the years. The first studies began in the 1960s. Maurer (1962) developed an ROP model for cone drill-bits, using parameters such as WOB, RPM, drill-bit diameter, and Uniaxial Compressive Strength of rock (UCS). Bingham (1965) used the drill-bit diameter, WOB, and RPM in his model, while Eckel (1967) incorporated the drilling mud effects. Bourgoyne and Young (1974) created one of the most complex ROP models using several parameters, such as the WOB, 19 RPM, drill-bit diameter, drill-bit tooth wear, formation strength, depth, compaction, pore pressure, differential pressure, and the effect of drill-bit hydraulic jet impact force. Drilling models have been improved with technological advances, Arabjamaloei and Shadizadeh (2011) used Artificial Neural Networks (ANN) to predict ROP through field data obtained in an Iranian oil field. While Hegde and Gray (2017) used machine learning to predict and increase ROP, through input parameters such as RPM, WOB, and FLOW. The first relation for calculating MSE was proposed by Teale (1965) for a rotary system based on experimental results. The main disadvantage of the equation presented by Teale is that it requires TOB measurement. Considering the problem presented, Pessier and Fear (1992) introduced the Bit-Specific Coefficient of Sliding Friction (μb) to express TOB as a function of WOB. Later, the equation originally introduced by Teale was adjusted by Dupriest and Koederitz (2005) to include the Drilling Efficiency Factor (EFFM). In the last decade, Chen et al. (2014) developed a relation between the WOB measured at the surface and the WOB measured at the bottom of the well. While Chen et al. (2016) developed a new model for rotary drilling using a Positive Displacement Motor (PDM). The drilling process performance can be estimated using pre-operational tests. The pre- operational tests, such as the Drill-Rate Test (DRT) and Drill-Off Test (DOT) determine the best combinations of parameters for drilling a given formation. The test consists in continuously increasing the WOB, keeping the RPM fixed in a short depth interval to obtain the ROP values (SOUTO; NASCIMENTO, 2016). However, it is important to enhance that the drilling process optimization doesn't consist simply in obtaining the highest ROP. In fact, it is necessary to search for parameters that allow drilling a phase of the well in the shortest time. Thus, the objective of this research is to obtain a multi-objective optimization capable of optimizing the drilling process, through the combination between the highest ROP and the lowest MSE, by the ideal combination of operating conditions. 1.1 OBJECTIVES This dissertation aims to analyze and evaluate how the parameters of the drilling process affect the ROP and MSE and consequently the time and cost of the process, based on the following specific objectives:  Analyze a field dataset from a real Pre-salt drilling operation; 20  Study and apply new techniques and research about drilling optimization from drilling mechanics parameters;  Study a multi-objective optimization based on a play-back methodology for pre- operational drilling tests;  Develop and apply a new concept of pre-operational tests based on MSE;  Develop and apply a methodology based on the desirability method proposed by Derring and Suich;  Cost and time analysis based on values of mechanical parameters obtained from multi- objective optimization. 1.2 DISSERTATION STRUCTURE The dissertation is structured as follows:  Introduction: presents the relevance and importance of the subject in the well drilling process;  Literature review: presents a review of the concepts used in the dissertation;  Methodology: presents the acquisition and treatment of the dataset, in addition to the methodology developed for multi-objective optimization;  Development: presents data analysis through the pre-operational test, multi-objective optimization, and surface response method;  Conclusion: presents a consolidation of results. 77 5 CONCLUSION In this dissertation, response surface methodology and multi-objective optimization based on pre-operational drilling tests, linked to a new recent methodology aiming at improving the drilling process through a possible ideal combination of ROP and MSE were performed. DRT methodology was mainly based on a recreation (play-back methodology) of the usual DRT from a field dataset, from a real Pre-salt drilling operation. The main conclusions drawn from this dissertation are:  The representation of drilling parameters through 2D plots as a function of depth allowed identifying the inefficient drilling zone and the possible parameters responsible for this inefficiency;  From the statistical analysis, it was possible to identify the input parameters that had a significant effect on the response variables. In addition, statistical models can predict all trends presented by the dataset, considering a 95% confidence level;  The new concept of pre-operational tests based on MSE showed to promise effective improvements in the drilling processes;  The combination of the highest ROP and the lowest MSE allows to perform an efficient drilling operation, transpering machinery, and equipment overload, and subsequently possible ways to improve operational efficiency;  Desirability Method, as per Derringer and Suich (1980), allowed optimizing the drilling process satisfactorily, which may be extended to other operations and scenarios;  For all WOB intervals of 3, 5, and 7 [klb] good fit of parameters was obtained, and as an interesting outcome for the industry, DRT with 5 and 7 [klb] may be sufficient to be applied in a real-time field operation;  Through the parameters obtained from pre-operational tests, specifically for the data analyzed, it was possible to obtain eventual cost-saving and time-saving values ranging from USD 1,056,180.72 to 1,151,898.30 and 19.50 to 21.27 [h], respectively. 78 For future work:  Expand this analysis to more field datasets from real Pre-salt and geothermal energy operations;  Apply the methodology of this dissertation in a didactic drilling rig bench to test the efficiency of the proposal on a laboratory scale in real-time;  To develop a software through the methodology presented in this dissertation to be used directly in the industry. 79 REFERENCES AADNOY, B.; COOPER, I.; MISKA, S.; MITCHELL, R.; PAYNE, M. 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