杨顺辉, 豆宁辉, 赵向阳, 柯珂, 王志远. 多层合采智能井井筒温度场预测模型及应用[J]. 石油钻探技术, 2019, 47(4): 83-91. DOI: 10.11911/syztjs.2019049
引用本文: 杨顺辉, 豆宁辉, 赵向阳, 柯珂, 王志远. 多层合采智能井井筒温度场预测模型及应用[J]. 石油钻探技术, 2019, 47(4): 83-91. DOI: 10.11911/syztjs.2019049
YANG Shunhui, DOU Ninghui, ZHAO Xiangyang, KE Ke, WANG Zhiyuan. Temperature Field Prediction Model for Multi-Layer Commingled Production Wellbore in Intelligent Wells and It's Application[J]. Petroleum Drilling Techniques, 2019, 47(4): 83-91. DOI: 10.11911/syztjs.2019049
Citation: YANG Shunhui, DOU Ninghui, ZHAO Xiangyang, KE Ke, WANG Zhiyuan. Temperature Field Prediction Model for Multi-Layer Commingled Production Wellbore in Intelligent Wells and It's Application[J]. Petroleum Drilling Techniques, 2019, 47(4): 83-91. DOI: 10.11911/syztjs.2019049

多层合采智能井井筒温度场预测模型及应用

Temperature Field Prediction Model for Multi-Layer Commingled Production Wellbore in Intelligent Wells and It's Application

  • 摘要: 智能井多层合采过程中为了优选温度监测设备和确定测点位置,需要准确预测井筒温度剖面。根据智能井多层合采过程中的井筒内流体流动特征,考虑流体经过流量控制阀时,节流效应对井筒内流体流动参数的影响,建立了含流量控制阀的单油管多层合采井筒温度预测模型,并结合生产井的工况进行了数值模拟。模型预测结果表明,井筒温度随产层产出液性质、产液量、产层厚度、产层配比和地层温度梯度的变化呈规律性变化;与各产层单独开采相比,合采时的井筒温度高于各产层单独开采时的平均温度,且合采时的温度梯度最低。为了有效应用多层合采井筒温度场预测模型,基于流量控制阀处温度测量误差最小的原则,提出了温度传感器指标及测点的优选方法;基于井筒温度、温度梯度及流量控制阀处温降变化规律,提出了产层温度异常的解释方法。多层合采智能井井筒温度场预测模型为多层合采智能井温度测量装置的优选和温度变化规律的解释提供了理论依据。

     

    Abstract: In order to optimize the temperature monitoring equipment and properly determine the positions of measuring points for the multi-layer commingled production of intelligent wells, it is necessary to accurately predict the whole wellbore temperature profile. According to the characteristics of fluid flow in the commingled production wellbore of intelligent wells, a prediction model for single-tubing multi-layer commingled production wellbore temperature with the flow control valve was established. Taking the throttling effect of flow control valve on fluids flow parameters in the system into account, a numerical simulation was carried out in combination with the working conditions of production wells. The model prediction results showed that the wellbore temperature changed regularly with several variables, including the produced fluids properties, liquid production rate, thickness of payzone, production allocation of each layer and geothermal gradient. Compared with the individual production layer, the wellbore temperature of commingled production wells is higher than the average temperature of wells with individually produced layer, and the temperature gradient of commingled production wellbore is the lowest. Based on the principle of minimum temperature measurement error at the flow control valve, an optimization method for temperature sensor index and measuring point was proposed. Taking into consideration the wellbore temperature, temperature gradient and the laws of temperature drop at flow control valve, it was possible to obtain an interpretation method of production layer temperature anomaly. The temperature field prediction model of multi-layer commingled production wellbore in intelligent wells provided a theoretical basis for optimizing the temperature measuring equipment and temperature data interpretation in multi-layer commingled production.

     

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