Casing Wear: Prediction, Monitoring, Analysis and Management in the Culzean Field

2021 ◽  
Author(s):  
Florian Aichinger ◽  
Loic Brillaud ◽  
Ben Nobbs ◽  
Florent Couliou ◽  
Joy Oyovwevotu ◽  
...  
Keyword(s):  
Field Measurements ◽  
String Model ◽  
Maximum Error ◽  
Groove Depth ◽  
Average Error ◽  
Bias Error ◽  
Wear Factor ◽  
Wear Prediction ◽  
Casing Wear ◽  
Well Data

Abstract Objectives/Scope This paper will present predicted vs. measured wear for six wells that were analysed in the Culzean field, which is a high-pressure, high-temperature (HPHT) gas condensate field located in the central North Sea. The focus rests on the casing wear prediction, monitoring and analysing process and within that, especially on how to make use of offset data to improve the accuracy of casing wear predictions. Methods The three major inputs to successfully predict casing wear are: Trajectory & Tortuosity, Wear Factor and required rotating operations. All those were calibrated based on field measurements (High-resolution gyro, MFCL (Multi-Finger-Caliper-Log) and automatically recorded rig mechanics data), to improve the prediction quality for the next section and/or well. The simulations were done using an advanced stiff-string model featuring a 3D mesh that distinguishes the influence of different contact type and geometry on the wear groove shape. The "single MFCL interpretation method", in which the wear is measured against the most probable elliptical casing shape and herby allowing wear interpretation with only one MFCL log and avoiding bias error, was applied. (Aichinger, 2016) Results, Observations, Conclusions For the six wells that were analysed the prediction of the largest wear peak per well section was compared to the measurement. In the planning phase (before any survey data was available) the mean error on the wear groove depth was +/− 0.025 [in] (+/− 0.6 [mm]), the maximum error was +/− 0.045 [in] (1.1 [mm]). The average error of the results is summarized in Figure 10 and laid out in detail in Figure 9. Generally, the predictions are accurate enough to be able to manage casing wear effectively. In this particular case, the maximum allowable wear on the intermediate casing was extremely limited to ensure proper well integrity in case of a well full of gas event while drilling an HTHP reservoir. Novel/Additive Information This paper should provide help to Engineers who seek to improve the accuracy of casing wear prediction and hence improve casing wear management. It presents a new way of anticipating tortuosity based on offset well data and it offers a suggestion on how to deal with MFCL measurement error during Wear Factor calibration and Wear prediction.

scholarly journals Turbine Blade Three-Wavelength Radiation Temperature Measurement Method Based on Reflection Error Correction

2021 ◽  
Vol 11 (9) ◽  
pp. 3913
Author(s):  
Kaifeng Zheng ◽  
Jinguang Lü ◽  
Yingze Zhao ◽  
Jin Tao ◽  
Yuxin Qin ◽  
...  
Keyword(s):  
Temperature Measurement ◽  
Turbine Blade ◽  
Measurement Method ◽  
Turbine Blades ◽  
Target Surface ◽  
Maximum Error ◽  
Radiation Temperature ◽  
Average Error ◽  
Real Surface ◽  
Wavelength Radiation

The turbine blade is a key component in an aeroengine. Currently, measuring the turbine blade radiation temperature always requires obtaining the emissivity of the target surface in advance. However, changes in the emissivity and the reflected ambient radiation cause large errors in measurement results. In this paper, a three-wavelength radiation temperature measurement method was developed, without known emissivity, for reflection correction. Firstly, a three-dimensional dynamic reflection model of the turbine blade was established to describe the ambient radiation of the target blade based on the real surface of the engine turbine blade. Secondly, based on the reflection correction model, a three-wavelength radiation temperature measurement algorithm, independent of surface emissivity, was proposed to improve the measurement accuracy of the turbine blade radiation temperature in the engine. Finally, an experimental platform was built to verify the temperature measurement method. Compared with three conventional colorimetric methods, this method achieved an improved performance on blade temperature measurement, demonstrating a decline in the maximum error from 6.09% to 2.13% and in the average error from 2.82% to 1.20%. The proposed method would benefit the accuracy in the high-temperature measurement of turbine blades.

Minimizing Casing Wear in Dog Legs

1977 ◽  
Vol 99 (1) ◽  
pp. 215-223 ◽  
Author(s):  
W. B. Bradley
Keyword(s):  
Drill Pipe ◽  
Field Measurements ◽  
Experimental Information ◽  
Wear Performance ◽  
Wear Rates ◽  
Casing Wear

Procedures are presented for estimating the amount of casing wear produced in wells by the rotation of tool joints, drill pipe, and drill pipe protectors against casing. The procedures are based upon experimental information and limited field measurements developed over a period of several years [1–5]. The procedures have been used with moderate success in predicting the casing wear rates seen in the field for a limited number of cases. The paper again emphasizes that with the proper use of drill pipe protectors casing wear can be minimized. In addition, the paper presents suggested procedures for selecting drill pipe protectors to assure consistent casing wear performance.

Wear-Factor Prediction Based on Data-Driven Inversion Technique for Casing Wear Estimation

2020 ◽  
Author(s):  
Manish K. Mittal ◽  
Robello Samuel ◽  
Aldofo Gonzales
Keyword(s):  
Physical Model ◽  
Factor Model ◽  
Data Driven ◽  
Wear Volume ◽  
Model Parameters ◽  
Wear Factor ◽  
Side Force ◽  
Inversion Technique ◽  
Casing Wear ◽  
Volume Output

Abstract Wear factor is an important parameter for estimating casing wear, yet the industry lacks a sufficient data-driven wear-factor prediction model based on previous data. Inversion technique is a data-driven method for evaluating model parameters for a setting wherein the input and output values for the physical model/equation are known. For this case, the physical equation to calculate wear volume has wear factor, side force, RPM, tool-joint diameter, and time for a particular operation (i.e., rotating on bottom, rotating off bottom, sliding, back reaming, etc.) as inputs. Except for wear factor, these values are either available or can be calculated using another physical model (wear-volume output is available from the drilling log). Wear factor is considered the model parameter and is estimated using the inversion technique method. The preceding analysis was performed using soft-string and stiff-string models for side-force calculations and by considering linear and nonlinear wear-factor models. An iterative approach was necessary for the nonlinear wear-factor model because of its complexity. Log data provide the remaining thickness of the casing, which was converted into wear volume using standard geometric calculations. A paper [1] was presented in OMC 2019 discussing a method for bridging the gap. A study was conducted in this paper for a real well based on the new method, and successful results were discussed. The current paper extends that study to another real well casing wear prediction with this novel approach. Some methods discussed are already included in the mentioned paper.

Calculation of the temperature of crystallization of silicates from basaltic melts

1981 ◽  
Vol 44 (333) ◽  
pp. 19-26 ◽  
Author(s):  
W. J. French ◽  
E. P. Cameron
Keyword(s):  
Crystallization Temperature ◽  
Maximum Error ◽  
Average Error ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Marquesas Islands ◽  
Melt Composition ◽  
The Relationship ◽  
Basaltic Melts

AbstractThis paper discusses the relationship between the chemical composition of basic melts and the temperatures at which olivine, clinopyroxene, and plagioclase begin to crystallize at one atmosphere. Diagrams are given which show the correlation between crystallization temperature and melt composition and which allow some of the temperatures to be estimated. Because the relationship between melt composition and crystallization temperature is virtually linear over short compositional ranges, the data available can be subdivided and examined by linear multivariate statistical techniques. The result is a set of equations which permit the crystallization temperatures to be calculated with an average error of less than 6 °C and a maximum error of 27 °C. These equations have been tested by experimental determination of crystallization temperatures for a range of rocks from the Marquesas Islands.

Experimental Study and Prediction Model of Casing Wear in Oil and Gas Wells

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
Zhanghua Lian ◽  
Qiang Zhang ◽  
Tiejun Lin ◽  
Kuncheng Li ◽  
Yonghui Liu
Keyword(s):  
Prediction Model ◽  
Contact Force ◽  
Oil And Gas ◽  
Economic Losses ◽  
Wear Depth ◽  
Gas Wells ◽  
Wear Prediction ◽  
Oil And Gas Wells ◽  
Casing Wear ◽  
Force Calculation

With the development of drilling technology and reinforced exploration and exploitation of unconventional reservoirs, there has been a great increase of complex wells. Meanwhile, however, consequent casing wear is and will continue to be a serious problem that causes enormous economic losses and many safety issues. The purpose of this paper is to find out the mechanism of casing wear and establish casing wear prediction model. Casing wear experiment was carried out to study the effect of contact force, rotation speed, and casing grade on wear depth. Meanwhile, wear coefficients under different working conditions were obtained through the normalizing of data. With the extensive research of downhole drag and torque calculation method, a contact force calculation model was established. Through the combination of crescent-shaped model and wear-efficiency model, the past complicated casing wear prediction models and confusing empirical formulae were greatly simplified. Therefore, the wear volume and depth of the casing string can be accurately predicted. Finally, a prediction software was developed to predict downhole casing wear of oil and gas wells. Comparison with the field data confirmed that the established model and software had enough accuracy to help predict and analyze casing wear at field.

A Prediction Model of Casing Wear in Extended-Reach Drilling With Buckled Drillstring

2017 ◽  
Vol 85 (2) ◽  
Author(s):  
Leichuan Tan ◽  
Deli Gao ◽  
Jinhui Zhou
Keyword(s):  
Practical Method ◽  
Economic Loss ◽  
Groove Depth ◽  
Calculation Error ◽  
Wear Depth ◽  
Energy Principle ◽  
New Model ◽  
Casing Wear ◽  
Complicated Geometry ◽  
Extended Reach Drilling

Buckled drillstring easily existed in extended-reach drilling (ERD) engineering, causing casing wear more severe. However, the effect of the buckled drillstring on casing wear prediction is going unheeded in long-term studies. To solve the issue, this paper proposes a new model, named as circumferential casing wear depth (CCWD) model, based on the energy principle and the more complicated geometry relationship than that in casing wear groove depth (CWGD) model. Meanwhile, sensitivity analysis of parameters clearly describes the changing trends among them. With the established composite wear models, the change of casing wear depth versus drilling footage under different composite wear cases is also discussed. The results show that the severe casing wear may occur if there is the buckled drillstring; due to the greater contact force and more sophisticated wear shape than those under nonbuckling condition, a shorter drilling footage could make a larger calculation error when only CWGD model is used. In the case study, the method of the inversion of casing wear factor from the drilled well can be used to predict the well whose structure resembles it; the revised coefficient, the maximum risky casing wear depth can be evaluated for each wellbore section to avoid drilling engineering failure. The new model provides a practical method to improve the prediction accuracy of casing wear in ERD. Neglecting the effect of the buckled drillstring will make the prediction underestimated and a great economic loss, which is significant for ERD.

scholarly journals Building Vibration Prediction Induced by Moving Train with Random Forest

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jinbao Yao ◽  
Lei Fang
Keyword(s):  
Random Forest ◽  
Prediction Accuracy ◽  
Reaction Force ◽  
Prediction Method ◽  
Element Model ◽  
Maximum Error ◽  
Average Error ◽  
Train Track ◽  
Vibration Prediction ◽  
Moving Train

This paper adopts a combination of numerical simulation, field test, and Random Forest to predict the building vibration induced by moving train. First, a three-dimensional finite element model based on train-track-site soil-building system is established, and the track dynamic reaction force calculated by the train-track model is applied as an excitation to the site. On the soil-building model, this paper analyzes the influence of train speed, axle load, site soil characteristics, and distance from the building on the vibration of the building caused by the train. With the Random Forest, these different influencing factors are used as inputs, and the building vibration is the output. Thus, the prediction model of the building vibration caused by moving train is established. The prediction accuracy can be tested with the measured data. The results show that this prediction method can provide a higher prediction accuracy with the maximum error (less than 6.41%) and the average error (less than 2.29%). This method overcomes the shortcomings of traditional prediction methods and improves the accuracy of vibration prediction.

scholarly journals Performance Prediction Model of Dynamic Pressure Oil-Air Separator

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiaobin Zhang ◽  
Lei Lang ◽  
Xiaofeng Zhang ◽  
Hongqing Lv ◽  
Na Gao
Keyword(s):  
Prediction Models ◽  
Separation Efficiency ◽  
Dynamic Pressure ◽  
Maximum Error ◽  
Least Square ◽  
Lubricating Oil ◽  
Average Error ◽  
Nonlinear Fitting ◽  
Resistance Performance ◽  
Air Separator

Based on the aeroengine lubricating oil system test bench, this paper used a dimensional analysis method to establish a mathematical model for predicting the separation efficiency and resistance of a dynamic pressure oil-air separator suitable for engineering. The analysis of the multivariate nonlinear fitting error and the experimental data showed that the established separation efficiency and resistance model could accurately predict the separation and resistance performance of the dynamic pressure oil-air separator within a certain range; the average error of the four separation characteristic prediction models was 3.5%, and the maximum error was less than 16%. The model that was established by the least square method had the highest accuracy; the average error of the multivariate nonlinear fitting of the four resistance characteristic prediction models was less than 4%, and the maximum error was less than 15%, which could be used to predict the resistance performance of the separator. The applicable working condition of the model is lubricating oil flow rate 4.3~8.5 L/min and oil-air ratio 0.5~3.

scholarly journals Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation

2020 ◽  
Vol 103 (4) ◽  
pp. 003685042096957
Author(s):  
Liangliang Ding ◽  
Miao Xian ◽  
Qiang Zhang
Keyword(s):  
Friction Coefficient ◽  
Contact Force ◽  
Residual Strength ◽  
Strength Degradation ◽  
Force Model ◽  
Wear Depth ◽  
Wear Prediction ◽  
Strength Evaluation ◽  
Casing Wear ◽  
Deviated Wells

Casing wear is a serious problem in highly-deviated wells because serious wear will lead to casing deformation, drilling tool sticking and failure of subsequent operations. The purpose of this paper is to predict casing wear depth and evaluate its effect on casing strength degradation in highly-deviated well drilling operation. Special attention has been given to the algorithm to achieve the prediction and evaluation. The effect of tool joint on contact force distribution is considered in contact force model. Then a wear depth prediction model and its solution method are proposed based on crescent-shaped wear morphology and wear-efficiency model. Besides, strength degradation of worn casing is analyzed in bipolar coordinate system and the model is verified by finite element method. Therefore, the technology of casing wear prediction and residual strength evaluation is completed systematically. Then, to apply casing wear prediction and residual strength evaluation technologies to an actual highly-deviated well, casing wear experiment and friction coefficient experiment are carried out to obtain wear coefficient and friction coefficient. Finally, based on the established models as well as experimental results, the distribution of casing wear is predicted and residual strength is evaluated. The method presented in this paper will contribute greatly to casing wear prediction and evaluation in highly-deviated wells.

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