All Days 1984
DOI: 10.2118/13046-ms
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Cementing Temperatures for Deep-Well Production Liners

Abstract: Temperature of cement is an important factor in properly cementing deep well production liners, yet current methods of determining cement temperatures do not account for all variables. In this paper a computer model predicts temperatures of cement while pumping and while waiting on cement, compares computed and measured temperatures, defines the importance of certain cementing variables on temperatures, and provides an explanation of difficulties encountered while cementing liner tops.

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Cited by 16 publications
(3 citation statements)
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“…7 Under normal cementing conditions for vertical wells, API tables and calculations have been used successfully for many years. However, for HPHT wells, the high temperatures cause the slurries to be sensitive to temperature and, therefore, the accuracy of the predicted cementing temperature is more critical.…”
Section: Temperaturementioning
confidence: 99%
“…7 Under normal cementing conditions for vertical wells, API tables and calculations have been used successfully for many years. However, for HPHT wells, the high temperatures cause the slurries to be sensitive to temperature and, therefore, the accuracy of the predicted cementing temperature is more critical.…”
Section: Temperaturementioning
confidence: 99%
“…Computer models specific to well cementing have been available for more than 20 years and have been shown to have reasonable accuracy in conventional wells 4 , deviated wells 5 , HTHP wells 6 , and deepwater wells 7,8,9 . Until recently, output from these simulators had been considered adequate for most cementing applications.…”
Section: Introductionmentioning
confidence: 99%
“…Many such models have appeared in the literature taking into account many variables that affect temperature. The complexity varies from correlation [7] and one-dimensional steadystate models [8] to two or three-dimensional transient simulators [9][10][11][12][13][14][15][16]. Some of them are unconvincing since the validations are based on incomplete sets of data inputs.…”
Section: Introductionmentioning
confidence: 99%