摘要：

随着海上油田开发对实时监测和高效管理需求的不断增加，分布式光纤声波传感技术(DAS)在油井产液解释中扮演着越来越重要的角色。但目前对油井产出过程中的DAS声波响应特征和响应规律认识不足，并且经典的声速—流量解释方法要求有较高流速，难以用于国内油井产液解释。本文通过对井下流动的DAS响应机理的理论研究，结合海上典型油井生产管柱和测试工艺，搭建“储层—全尺寸井筒—测试管柱”全耦合物理模拟实验装置，系统开展油水两相流体从模拟储层岩心流入井筒过程中的DAS响应实验，深入研究不同流量和含水率情况下的声波响应特征。在对DAS数据进行降噪处理和频带能量(FBE)计算的基础上，发现油水两相混合流体的黏度是影响声波响应的重要参数，油水两相占比变化引起的多种尺度界面动力学过程以及流型不稳定性是造成两相流动中频率特征变化的主要原因；井筒中油水两相流动的频带范围集中在500 Hz以内，当某一相占优时频谱多呈单峰特征，而两相比例接近时频谱多呈多峰特征。选取能综合表征流体性质和管道结构特征的雷诺数(Re)作为特征值，建立油水两相FBE-Re关系模型，呈现高度相关的对数变化关系，实现了井筒中油水两相流动与DAS响应关系的量化表征。现场井实测DAS数据的解释结果表明，其响应频段与室内实验确定频段高度一致，解释的总液量与总含水率符合率均大于85%，满足现场生产解释要求，验证了所建立FBE-Re模型的可靠性和实用性。本文研究成果深化了对井下产液的DAS声波响应特征和响应规律的认识，为油井产液剖面解释、高含水段识别提供了理论基础和措施决策依据。

关键词: 分布式光纤声波传感, 油水两相流, 物理模拟实验, FBE-Re模型, 产液剖面解释

Abstract:

With the increasing demand for real-time monitoring and efficient management in offshore oilfield development, Distributed Acoustic Sensing (DAS) has emerged as a powerful tool for downhole fluid monitoring and production interpretation. Despite its growing application, the understanding of DAS acoustic response characteristics and underlying mechanisms during well production remains insufficient. Moreover, conventional sound velocity-flow interpretation methods typically require relatively high flow rates, which limits their applicability in domestic wells with lower production rates. Addressing these challenges, this study presents a systematic investigation of the DAS response mechanisms associated with downhole oil-water two-phase flow. A theoretical analysis was first conducted to elucidate the acoustic response mechanisms of multiphase flow within the wellbore. Building on this analysis, a fully coupled physical simulation apparatus was designed, comprising a reservoir analog, a full-scale wellbore, and a test tubular string, replicating realistic downhole production conditions. Experiments were performed to monitor the DAS response during the flow of oil-water mixtures from simulated reservoir cores into the wellbore, considering varying flow rates and water cut conditions. DAS data were processed with advanced denoising techniques, and Frequency Band Energy (FBE) metrics were computed to quantitatively characterize the acoustic response. The experimental results reveal that the viscosity of oil-water mixtures is a key factor influencing DAS responses. Variations in the oil-water ratio generate complex multiscale interfacial dynamic processes and flow regime instabilities, which are identified as the primary causes of changes in the spectral characteristics. The frequency spectrum of two-phase flow within the wellbore was found to be concentrated below 500 Hz. Specifically, when one phase predominates, the spectrum typically exhibits a single dominant peak; whereas for near-equal oil-water ratios, multiple peaks emerge in the frequency spectrum, reflecting the complex dynamics of the multiphase flow. To enable quantitative interpretation, the Reynolds number (Re) was selected as a representative characteristic parameter integrating both fluid properties and pipe geometry. An FBE-Re relationship model was subsequently established, showing a highly correlated logarithmic relationship. This model provides a robust framework to quantitatively link DAS responses to downhole two-phase flow characteristics. Field validation demonstrates that the observed DAS frequency bands closely match the laboratory-determined ranges, and the interpreted total liquid production and water cut achieve an accuracy exceeding 85%. These results confirm the reliability and practical applicability of the proposed FBE-Re model for field production monitoring. Overall, this study significantly advances the understanding of DAS acoustic response characteristics and governing mechanisms in oil-water two-phase downhole flow. The findings provide a theoretical foundation and practical guidance for accurate well production profiling, high water-cut zone identification, and enhanced field-level production monitoring, offering substantial potential for improving offshore oilfield management and operational decision-making.

Key words: distributed acoustic sensing, oil-water two-phase flow, physical simulation experiment, FBE-Re model, production profiling interpretation

中图分类号: 

• TE34

• TP212.14