Casing Wear Modelling:A Comparison between MFCL and 3D Stiff StringModel

摘要

A stiff-string torque & drag & buckling model has been coupled to a 3D meshed casing wear calculation tomodel the effect of drilling operations on casing wall thickness reduction.Results of the numeric simulationare compared to MFCL for field cases and provide an understanding of possible well integrity issues duringthe well life cycle.A Hall wear model and 3D rigid stiff string model is used to predict casing wear.UsingWear Factor Coefficients obtained for several hard-banding,casing grade and mud-types,the process wastested against numerous field cases.For each field case,a history of drill string runs were modelled andfiltered into operations in which the drill string rotates such as Drilling,Reaming,Back reaming and ROB.Initially,the calliper log was not analysed to ensure the results are non-biased using experimentally foundWear Factors.In a second phase,the Wear Factors were calibrated against the measured calliper log.Thispaper provides a methodology that was used to successfully quantify the effect of casing wear againstnumerous field cases.The 3D orientation of the casing wear was found from an un-calibrated MFCL.Aftercalibration of the new Wear Factor,the casing wear can be predicted before and after well construction.When used as a post analysis tool,the methodology helps determine if casing wear was a root cause of lossof well integrity.This process also helps reduce the uncertainty in Wear factor as a major unknow in thecontact force,is now properly modelled.When used in a post analysis process,the results where quantitative(groove depth vs 3D orientation)but also qualitative,providing a post-mortem description of the state of thewell to operation's personnel.The methodology presented here can be used to both predict excessive casingwear and determine if excessing casing wear was a cause of failure.It can be used to help determine thestate of well for workover operations or plug and abandonment operations.Accurate casing wear predictionat planning stage allows the anticipation of costly but fit for purpose mitigation means & measures.