Producer-flowline temperatures (FLTs) can be measured automatically with a thermistor on an emergency-shutdown system (ESD), or manually on a specified spot on flowline with a handheld unit. Measured FLTs can usually be mapped to represent the formationtemperature distribution for steamflood reservoir management purposes (Hong 1994; Nath et al. 2007). In addition to FLT, wellhead temperature (WHT) is another surface temperature. Predicting the long-term WHT trend in steamflood operation is necessary for designing surface facilities for both oil dehydration/separation and produced-water recycling. This predicted temperature will also be applicable for production-performance monitoring.

To predict the wellhead temperature, Hasan et al. (2009) derived a steady-state analytical solution for calculating WHT from bottomhole temperature (BHT) under flowing conditions of a multisection slant wellbore for the isothermal primary-depletion process, with both WHT and BHT being time independent for a given gross rate (Igec et al. 2010). This steady-state analytical solution has been extended to calculate steamflood producer WHT from BHT (both are time dependent) by consecutively approximating the WHT and monthly average of FLT measurements to a steady-state solution. The monthly averaged FLTs are seasonally variable and higher in the summer months of July through September and lower in the winter months of December through February. Monthly averaged FLT measurements depend on an annual ambient-temperature cycle within the depth needed for reaching an undisturbed ground temperature (typically 30 to 50 ft) (Gwadera et al. 2017). WHT, if measured, should be comparable with FLT for their close typical distance of 5 to 10 ft. WHT prediction, however, is only process dependent and not seasonally variable because of the inability to describe seasonally undisturbed depth in the geothermal gradient. Therefore, WHT prediction can be validated with average summer-month FLT measurements when heat loss becomes minimal. BHTs in this analytical approach are predicted by the Lauwerier (1955) analytical model and improved by calibration with the available reservoir-simulation model or several years of FLT measurements for steamflood response time.

The objective of this study is to develop an integrated production-monitoring approach using only the surface information, including WHT and FLT, oil/water-production rate, and injection-pressure/rate data, which can be applied to diagnose and optimize steamflood production performance. A field case study for the South Belridge Diatomite steamflood was investigated. WHT prediction is compared with FLT measurement for diagnosing and understanding the production performances, such as premature water or steam breakthrough, interference by the waterflood on the steamflood boundary producers, as well as the FLT variation related to the target rates for steam injection. This diagnostic analysis approach combined with the Buckley-Leverett theory-based displacement-efficiency analysis, and injection pressure and rate signal, will help to develop an improved understanding of the displacement detail and form a decision base to optimize the production performance.

可以通过紧急停机系统（ESD）上的热敏电阻自动测量出水管道温度（FLT），也可以使用手持式装置在出水管道的指定位置手动测量出水管道温度。通常可以将测得的FLT映射成代表地层温度分布的蒸汽驱油藏管理目的（Hong 1994； Nath等，2007）。除FLT外，井口温度（WHT）是另一种表面温度。对于设计油脱水/分离和采出水再循环的地面设施，必须预测蒸汽驱操作中的长期WHT趋势。该预测温度还将适用于生产性能监控。

为了预测井口温度，Hasan等人。（2009年）推导出了稳态分析解决方案，用于在等温一次枯竭过程的多段斜井眼流动条件下，根据井底温度（BHT）计算WHT，WHT和BHT在给定总速率下均与时间无关（Igec等（2010）。通过将WHT和FLT测量值的月平均值连续逼近为一个稳态解决方案，该稳态分析解决方案已扩展为从BHT计算蒸汽驱生产商WHT（两者均与时间有关）。每月平均FLT随季节变化，在7月至9月的夏季月份较高，而12月至2月的冬季月份较低。每月平均FLT测量值取决于在达到不受干扰的地面温度（通常为30至50 ft）所需深度内的年度环境温度周期（Gwadera等，2017）。如果测量WHT，它们的典型典型距离为5到10 ft，应该与FLT相当。但是，WHT的预测仅取决于过程，而不能季节性变化，因为无法描述地热梯度中季节性不受干扰的深度。因此，当热量损失最小时，可以使用夏季夏季平均FLT测量值来验证WHT预测。这种分析方法中的BHT由Lauwerier（1955）分析模型预测，并通过使用可用的储层模拟模型或几年的FLT测量法对蒸汽驱响应时间进行校准而得到改进。

这项研究的目的是仅使用表面信息（包括WHT和FLT，油/水生产率，注入压力/速率数据）开发一种集成的生产监控方法，该方法可用于诊断和优化蒸汽驱生产性能。对South Belridge硅藻土蒸汽驱进行了现场案例研究。将WHT预测与FLT测量进行比较，以诊断和了解生产性能，例如过早的水或蒸汽突破，注水对蒸汽驱边界生产商的干扰以及与注汽目标速率相关的FLT变化。这种诊断分析方法结合了基于Buckley-Leverett理论的位移效率分析以及注射压力和速率信号，