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Stress distribution and its influencing factors of bottom-hole rock in underbalanced drilling 被引量:3
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作者 ZHANG Ran LI Gen-sheng TIAN Shou-ceng 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第7期1766-1773,共8页
The underbalanced drilling has been widely used due to its advantages of high drilling efficiency and low cost etc., especially for hard formation drilling. These advantages, however, are closely related to the stress... The underbalanced drilling has been widely used due to its advantages of high drilling efficiency and low cost etc., especially for hard formation drilling. These advantages, however, are closely related to the stress state of the bottom-hole rock; therefore, it is significant to research the stress distribution of bottom-hole rock for the correct understanding of the mechanism of rock fragmentation and high penetration rate. The stress condition of bottom-hole rock is very complicated while under the co-action of overburden pressure, horizontal in-situ stresses, drilling mud pressure, pore pressure and temperature etc. In this paper, the fully coupled simulation model is established and the effects of overburden pressure, horizontal in-situ stresses, drilling mud pressure, pore pressure and temperature on stress distribution of bottom-hole rock are studied. The research shows that: in air drilling, as the well depth increases, the more easily the bottom-hole rock is broken; the mud pressure has a great effect on the bottom hole rock. The bigger the mud pressure is, the more difficult to break the bottom-hole rock; the max principle stress of the bottom-hole increased with the increasing of mud pressure, well depth and temperature difference. The bottom-hole rock can be divided into 3 regions respectively according to the stress state, 3 direction stretch zone, 2 direction compression area and 3 direction compression zone; the corresponding fragmentation degree of difficulty is easily, normally and hardly. 展开更多
关键词 thermo-poroelastoplasticity bottom-hole rock stress fully coupled numerical solution fragmentation mechanism
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An adaptive neuro-fuzzy inference system white-box model for real-time multiphase flowing bottom-hole pressure prediction in wellbores
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作者 Chibuzo Cosmas Nwanwe Ugochukwu Ilozurike Duru 《Petroleum》 EI CSCD 2023年第4期629-646,共18页
The majority of published empirical correlations and mechanistic models are unable to provide accurate flowing bottom-hole pressure(FBHP)predictions when real-time field well data are used.This is because the empirica... The majority of published empirical correlations and mechanistic models are unable to provide accurate flowing bottom-hole pressure(FBHP)predictions when real-time field well data are used.This is because the empirical correlations and the empirical closure correlations for the mechanistic models were developed with experimental datasets.In addition,most machine learning(ML)FBHP prediction models were constructed with real-time well data points and published without any visible mathematical equation.This makes it difficult for other readers to use these ML models since the datasets used in their development are not open-source.This study presents a white-box adaptive neuro-fuzzy inference system(ANFIS)model for real-time prediction of multiphase FBHP in wellbores.1001 real well data points and 1001 normalized well data points were used in constructing twenty-eight different Takagi eSugeno fuzzy inference systems(FIS)structures.The dataset was divided into two sets;80%for training and 20%for testing.Statistical performance analysis showed that a FIS with a 0.3 range of influence and trained with a normalized dataset achieved the best FBHP prediction performance.The optimal ANFIS black-box model was then translated into the ANFIS white-box model with the Gaussian input and the linear output membership functions and the extracted tuned premise and consequence parameter sets.Trend analysis revealed that the novel ANFIS model correctly simulates the anticipated effect of input parameters on FBHP.In addition,graphical and statistical error analyses revealed that the novel ANFIS model performed better than published mechanistic models,empirical correlations,and machine learning models.New training datasets covering wider input parameter ranges should be added to the original training dataset to improve the model's range of applicability and accuracy. 展开更多
关键词 Machine learning models Empirical correlations Mechanistic models Multiphase flowing bottom-hole pressure Adaptive neuro-fuzzy inference system White-box model
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An artificial neural network visible mathematical model for real-time prediction of multiphase flowing bottom-hole pressure in wellbores
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作者 Chibuzo Cosmas Nwanwe Ugochukwu Ilozurike Duru +1 位作者 Charley Anyadiegwu Azunna I.B.Ekejuba 《Petroleum Research》 EI 2023年第3期370-385,共16页
Accurate prediction of multiphase flowing bottom-hole pressure(FBHP)in wellbores is an important factor required for optimal tubing design and production optimization.Existing empirical correlations and mechanistic mo... Accurate prediction of multiphase flowing bottom-hole pressure(FBHP)in wellbores is an important factor required for optimal tubing design and production optimization.Existing empirical correlations and mechanistic models provide inaccurate FBHP predictions when applied to real-time field datasets because they were developed with laboratory-dependent parameters.Most machine learning(ML)models for FBHP prediction are developed with real-time field data but presented as black-box models.In addition,these ML models cannot be reproduced by other users because the dataset used for training the machine learning algorithm is not open source.These make using the ML models on new datasets difficult.This study presents an artificial neural network(ANN)visible mathematical model for real-time multiphase FBHP prediction in wellbores.A total of 1001 normalized real-time field data points were first used in developing an ANN black-box model.The data points were randomly divided into three different sets;70%for training,15%for validation,and the remaining 15%for testing.Statistical analysis showed that using the Levenberg-Marquardt training optimization algorithm(trainlm),hyperbolic tangent activation function(tansig),and three hidden layers with 20,15 and 15 neurons in the first,second and third hidden layers respectively achieved the best performance.The trained ANN model was then translated into an ANN visible mathematical model by extracting the tuned weights and biases.Trend analysis shows that the new model produced the expected effects of physical attributes on FBHP.Furthermore,statistical and graphical error analysis results show that the new model outperformed existing empirical correlations,mechanistic models,and an ANN white-box model.Training of the ANN on a larger dataset containing new data points covering a wider range of each input parameter can broaden the applicability domain of the proposed ANN visible mathematical model. 展开更多
关键词 Flowing bottom-hole pressure Real-time prediction Artificial neural network Visible mathematical model Levenberg-marquardt optimization ALGORITHM Hyperbolic tangent activation function Empirical correlations Mechanistic models
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A fast explicit finite difference method for determination of wellhead injection pressure 被引量:2
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作者 白冰 李小春 +2 位作者 刘明泽 石露 李琦 《Journal of Central South University》 SCIE EI CAS 2012年第11期3266-3272,共7页
A fast explicit finite difference method (FEFDM),derived from the differential equations of one-dimensional steady pipe flow,was presented for calculation of wellhead injection pressure.Recalculation with a traditiona... A fast explicit finite difference method (FEFDM),derived from the differential equations of one-dimensional steady pipe flow,was presented for calculation of wellhead injection pressure.Recalculation with a traditional numerical method of the same equations corroborates well the reliability and rate of FEFDM.Moreover,a flow rate estimate method was developed for the project whose injection rate has not been clearly determined.A wellhead pressure regime determined by this method was successfully applied to the trial injection operations in Shihezi formation of Shenhua CCS Project,which is a good practice verification of FEFDM.At last,this method was used to evaluate the effect of friction and acceleration terms on the flow equation on the wellhead pressure.The result shows that for deep wellbore,the friction term can be omitted when flow rate is low and in a wide range of velocity the acceleration term can always be deleted.It is also shown that with flow rate increasing,the friction term can no longer be neglected. 展开更多
关键词 wellhead pressure injection pressure bottom-hole pressure fast explicit finite difference method
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FUNDAMENTAL EQUATIONS OF LARGE SPATIAL DEFLECTION PROBLEMS OF RODS AND ITS APPLICATION TO DRILLING ENGINEERING
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作者 蔡宗熙 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 1993年第12期1103-1111,共9页
The fundamental equations for analysis of a straight slender rod which deform at large deflections of order of several times of the dimension of the cross section of the rod are derived by using convecled coordinate s... The fundamental equations for analysis of a straight slender rod which deform at large deflections of order of several times of the dimension of the cross section of the rod are derived by using convecled coordinate system. In accordance with the practice of oil drilling, an effective method of three dimensional static analysis of bottom-hole assemblies is simply described. Errors in reference [8 ] are pointed out. 展开更多
关键词 bottom-hole assemblies large displacement analytic solution
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Modeling and simulation of non-isothermal three-phase flow for accurate prediction in underbalanced drilling
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作者 FALAVAND-JOZAEI A HAJIDAVALLOO E +1 位作者 SHEKARI Y GHOBADPOURI S 《Petroleum Exploration and Development》 CSCD 2022年第2期406-414,共9页
The present study aims at investigating the effect of temperature variation due to heat transfer between the formation and drilling fluids considering influx from the reservoir in the underbalanced drilling condition.... The present study aims at investigating the effect of temperature variation due to heat transfer between the formation and drilling fluids considering influx from the reservoir in the underbalanced drilling condition. Gas-liquid-solid three-phase flow model considering transient thermal interaction with the formation was applied to simulate wellbore fluid to calculate the wellbore temperature and pressure and analyze the influence of different parameters on fluid pressure and temperature distribution in annulus. The results show that the non-isothermal three-phase flow model with thermal consideration gives more accurate prediction of bottom-hole pressure(BHP) compared to other models considering geothermal temperature. Viscous dissipation, the heat produced by friction between the rotating drilling-string and well wall and drill bit drilling, and influx of oil and gas from reservoir have significant impact on the distribution of fluid temperature in the wellbore, which in turn affects the BHP. Bottom-hole fluid temperature decreases with increasing liquid flow rate, circulation time, and specific heat of liquid and gas but it increases with increasing in gas flow rate. It was found that BHP is strongly depended on the gas and liquid flow rates but it has weak dependence on the circulation time and specific heat of liquid and gas. BHP increase with increasing liquid flow rate and decreases with increasing gas flow rate. 展开更多
关键词 under-balanced drilling bottom-hole pressure fluid temperature CUTTINGS three-phase flow model temperature profile wellbore heat transfer
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A new model for predicting the critical liquid-carrying velocity in inclined gas wells
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作者 WANG Wujie CUI Guomin +1 位作者 WEI Yaoqi PAN Jie 《Petroleum Exploration and Development》 CSCD 2021年第5期1218-1226,共9页
Based on the assumption of gas-liquid stratified flow pattern in inclined gas wells,considering the influence of wettability and surface tension on the circumferential distribution of liquid film along the wellbore wa... Based on the assumption of gas-liquid stratified flow pattern in inclined gas wells,considering the influence of wettability and surface tension on the circumferential distribution of liquid film along the wellbore wall,the influence of the change of the gas-liquid interface configuration on the potential energy,kinetic energy and surface free energy of the two-phase system per unit length of the tube is investigated,and a new model for calculating the gas-liquid distribution at critical conditions is developed by using the principle of minimum energy.Considering the influence of the inclination angle,the calculation model of interfacial friction factor is established,and finally closed the governing equations.The interface shape is more vulnerable to wettability and surface tension at a low liquid holdup,resulting in a curved interface configuration.The interface is more curved when the smaller is the pipe diameter,or the smaller the liquid holdup,or the smaller the deviation angle,or the greater gas velocity,or the greater the gas density.The critical liquid-carrying velocity increases nonlinearly and then decreases with the increase of inclination angle.The inclination corresponding to the maximum critical liquid-carrying velocity increases with the increase of the diameter of the wellbore,and it is also affected by the fluid properties of the gas phase and liquid phase.The mean relative errors for critical liquid-carrying velocity and critical pressure gradient are 1.19%and 3.02%,respectively,and the misclassification rate is 2.38%in the field trial,implying the new model can provide a valid judgement on the liquid loading in inclined gas wells. 展开更多
关键词 inclined gas well gas-liquid phase distribution interfacial friction factor critical liquid-carrying velocity bottom-hole liquid loading
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Operational method for determining bottom hole pressure in mechanized oil producing wells,based on the application of multivariate regression analysis 被引量:2
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作者 Inna N.Ponomareva Vladislav I.Galkin Dmitriy A.Martyushev 《Petroleum Research》 2021年第4期351-360,共10页
One of the major tasks of monitoring production well operations is to determine bottom-hole flowing pressure.The overwhelming majority of wells in the Perm Krai are serviced using borehole pumps,which makes it difficu... One of the major tasks of monitoring production well operations is to determine bottom-hole flowing pressure.The overwhelming majority of wells in the Perm Krai are serviced using borehole pumps,which makes it difficult to take direct bottom-hole flowing pressure measurements.The bottomhole filtration pressure(BHFP)in these wells is very often determined by recalculating the parameters measured at the well mouth(annulus pressure,dynamic fluid level depth).The recalculation is done by procedures based on analytically determining the characteristics of the gas-liquid mixture in the wellbore,which is very inconsistent to perform due to the mixture's complex behavior.This article proposes an essentially different approach to BHFP measurements that relies on the mathematical processing of the findings of more than 4000 parallel mouth and deep investigations of the oil production wells of a large oil-production region.As a result,multivariate mathematical models are elaborated that allow reliably determining the BHFP of oil-production wells in operation. 展开更多
关键词 Production well bottom-hole flowing pressure BHFP determination Technique Multivariate statistical model Regression analysis Multilevel modeling
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