基于分布式光纤温度测井的注入和产出剖面解释方法研究

Research on injection and output profile interpretation method based on distributed fiber temperature logging

近年来,随着分布式光纤温度传感(DTS)技术的快速发展,由于其对井干扰小、施工方便、能实时提供准确且连续的温度数据等优势,越来越多的被应用于井下的动态监测中.然而,实际应用中DTS数据量巨大且复杂,如何分析数据和用其解释井下的流量剖面及生产动态仍是一项巨大挑战.为此,本文基于井筒与地层间的传热机理,建立了多相流井筒温度分布模型,分析了不同影响因素下井筒的温度曲线响应特征.对实测DTS数据进行分析,建立基于井筒温度分布模型的拟合评价目标函数,用L-M(Levenberg-Marquarelt算法)和Sqp-legacy(Sequential quadratic programming-legacy,顺序二次规划遗传算法)两种算法进行反演后,将PSO(Particle Swarm Optimization,粒子群优化算法)与两种算法结合,对比两组组合算法的反演误差后选用PSO-LM算法,PSO-LM算法既具有PSO算法的随机性也具有L-M算法的高效性.然后对两口实测井进行解释,误差结果表明PSO-LM算法的精度较高,满足实际应用,验证了反演解释模型的正确性和可靠性.

In recent years,with the rapid development of Distributed Fiber Optic Temperature Sensing(DTS)technology,it has the advantages of low interference to well,convenient construction,and can provide accurate and continuous temperature data in real time.It is more and more applied in downhole dynamic monitoring.However,the application of DTS data is large and complex,and how to analyze the data and use it to interpret downhole flow profiles and production dynamics remains a major challenge.Therefore,based on the heat transfer mechanism between wellbore and formation,a multi-phase flow wellbore temperature distribution model is established in this paper,and the characteristics of wellbore temperature curve response under different influencing factors are analyzed.The measured DTS data was analyzed,the fitting evaluation objective function based on the wellbore temperature distribution model was established.L-M(Levenberg-Marquarelt algorithm)and Sqp-legacy(Sequential quadratic programming-legacy)were used.After inversion of the two algorithms,the Particle Swarm Optimization(PSO)algorithm is combined with the two algorithms,and the PSO-LM algorithm is selected after comparing the inversion errors of the two combined algorithms.PSO-LM algorithm has both the randomness of PSO algorithm and the efficiency of L-M algorithm.The error results show that the accuracy of PSO-LM algorithm is high,which meets the practical application,and verifies the correctness and reliability of the inversion interpretation model.