Establishing a practical method to accurately determine and manage wellbore thermal behavior in high-temperature drilling

Mou Yang, Dayu Luo, Yuanhang Chen, Gao Li, Daqian Tang and Yingfeng Meng

Applied Energy, 2019, vol. 238, issue C, 1483 pages

Abstract: As deeper reservoirs are pursued around the globe, the oil and gas industry has shown a keen interest in high-temperature operations, despite the significant drilling problems such operations pose. In order to formulate guidelines to manage wellbore temperatures accurately and maintain drilling safety, it is crucial to develop a method to quantitatively identify the effects of various parameters, both controllable and uncontrollable, on circulating fluid temperature through sound statistical methods with field validations. In this paper, the transient heat transfer mechanisms of each region of wellbore and formation were investigated. Based on the first law of thermodynamics, a set of transient heat transfer models were developed and solved using the fully implicit finite difference method. The change in the thermal behavior of the wellbore and formation was analyzed to ascertain the range of change in the sensitivity parameters. Using the Monte Carlo simulation technique, the input parameters were treated as uniform, and triangular distributions were applied to estimate the probability distribution of the bottom-hole temperature. The contributing factors of the bottom-hole temperature were ranked based on their level of influences as fluid heat capacity, formation thermal conductivity, inlet temperature, flow rate, and fluid density. The research findings from this study provides a quantitative evaluation of each parameter’s relative significance to circulating fluids temperatures during oil and gas wells or geothermal well drilling operations and therefore provides practical guidance in managing downhole temperatures by identifying the most effective and controllable operation parameters.

Keywords: Managed wellbore temperature; High-temperature formation; Monte Carlo simulation; Sensitivity analysis (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:238:y:2019:i:c:p:1471-1483

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DOI: 10.1016/j.apenergy.2019.01.164

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