Contact Pressure Threshold: An Important New Aspect of Casing Wear

Hall, R; Malloy, Kenneth P.

doi:10.2523/94300-ms

Cited by 8 publications

(3 citation statements)

References 1 publication

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“…The first analytical solution for residual burst strength of worn casing was developed by Song et al 5 Full size tests were conducted and the comparison between actual rupture pressures and predicted values of worn casing verified the accuracy of the method. Hall and Malloy 6 acquired best fitting empirical function for the majority of more than 450 wear tests data and confirmed the nonlinear relationship between casing wear volume and dissipation energy. Sun et al 7 classed wear stages into steady-state wear and running-in wear, and a nonlinear wear prediction model was developed.…”

Section: Introductionsupporting

confidence: 52%

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

2020

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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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Section: Introductionsupporting

confidence: 52%

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

2020

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“…Disregarding it can provoke a lot of costs and abandon the well before it reaches the target or, in other special cases to blowout, wear occurs with increasing drilling depth, drilling time, and contact load. [1][2][3][4][5] Bradley and Fontenot determined wear in rotating, tripping, and wireline operations by investigating the effect of time, rotation speed, mud conditions, pipe wear capability, wear resistance, dogleg severity, and tension at the wear point. Moreover, they studied the factors affecting casing wear in these operations and showed that the least wear happens within the wireline and tripping operations.…”

Section: Introductionmentioning

confidence: 99%

“…These results showed that the casing wear coefficient is not constant and decreases with increasing wear groove depth. [5] Gao et al investigated the effect of drill pipe diameter on casing wear in ERD wells. They concluded that the casing wears groove geometry is having a substantial impact on the wear groove depth.…”

Section: Introductionmentioning

confidence: 99%

New Method for Predicting Casing Wear in Highly Deviated Wells Using Mud Logging Data

Farab

Shahbazi

Hashemi

et al. 2021

Preprint

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Casing wear is an essential and complex phenomenon in oil and gas wells. Research is being conducted to predict this phenomenon. This study was conducted at a well in southwestern Iran. In this paper, first examine the force exerted on the drill string. Next, the contact force between the drill string and the casing is calculated. Finally, the wear volume and the depth of the wear groove are determined. These calculations were performed using MATLAB and Python software. In addition, due to the high accuracy of coding, mud log data was used to make the results more accurate. It has also been shown that increasing RPM increases the depth of wear and attempts to drill a highly deviated wells as a sliding mode. Finally, compared the results and matched them with the wireline logs recorded from the well.

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Improving Casing Wear Prediction and Mitigation Using a Statistically Based Model

Mitchell¹,

Xiang²

2012

IADC/SPE Drilling Conference and Exhibition

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Wells are now routinely drilled both in deepwater and on land to depths that were previously considered impossible. In these environments, casing design is critical to safely and successfully drilling and producing wells, and unexpected casing wear can result in significant costs or even the loss of a well. As part of a successful casing design strategy, the engineer must assess the maximum permissible casing wear required to maintain casing integrity. Then, steps must be taken to ensure that casing wear thresholds are not exceeded.Casing wear models use the number of drill string revolutions and contact force between the drill pipe and casing to calculate wear. The contact force is calculated using the dog-leg severity within the well, with the maximum dog-leg severity often determining the location and extent of the most severe casing wear. There is often a large discrepancy between predicted and actual casing wear because of survey quality and inaccurate estimates of dog-leg severity and total revolutions. These discrepancies result in predictions of contact force and drill string revolutions that are in error by 50% or more. To improve the accuracy of casing wear models, an extensive database was created from a wide variety of wells with measured depths greater than 13,000ft. The database results in a statistically based model for determining dog-leg severity within vertical, build, and tangent sections, as well as total drill string revolutions at various levels of confidence to bound average and maximum expected contact force and casing wear.Case histories compare measured wear with predictions of casing wear based on original well data and the statistically based model. The case histories also demonstrate the effect of various drilling parameters on casing wear, and evaluate the effectiveness of non-rotating protectors in preventing casing wear. Project GoalThe goal of this project was to more accurately quantify casing wear risk by improving casing wear analysis accuracy. To do this, data from a large number of wells was analyzed to generate probabilities for dog-leg severity in common well types and also correlate those to actual backmodeled casing wear factors. The results will allow an engineer to analyze what the expected casing wear might be for an average (P50) horizontal well, and then evaluate the maximum expected wear for a 1 in 10 case (P90), 1 in 20 case (P95), or 1 in 100 (P99) case. SurveysAll casing wear software, and torque and drag software as well, use a directional survey to determine the side force or contact force between the drill string and wellbore. These points within a directional survey can be a representation of a planned well path, or it can be taken from actual downhole measurements. The survey points are then connected into a single line representing a best approximation of the wellpath with the information given.

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Contact Pressure Threshold: An Important New Aspect of Casing Wear

Abstract: TX 75083-3836, U.S.A., fax 01-972-952-9435.

Cited by 8 publications

References 1 publication

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

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

New Method for Predicting Casing Wear in Highly Deviated Wells Using Mud Logging Data

Improving Casing Wear Prediction and Mitigation Using a Statistically Based Model

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