油-气-水多相混输管内流水合物生-消过程可视化识别

In deepwater gas and oil exploration, hydrate plug occurs in the gas-oil-water multiphase flow pipeline while under the high pressure, low temperature condition. It will be a key issue of the marine oil transportation security. Thus, it is important to in-situ measure the key parameters of the flows, e.g. flow regimes, water content in the early stage of the hydrate formation process, so that the behavior of hydrate formation-decomposition can be characterized. A conventional method is using software to simulate and predict the hydrate plug, however it is not the real measurement technique and the software cannot in-site address the changes in the hydrate formation-decomposition process. Some measurement technologies such as optics, MRI, X-ray are not be possible to apply on the subsea multiphase flow pipe due to their drawbacks in the deepwater environment. This project is proposed to use electrical capacitance tomography (ECT) to visualize the hydrate formation-decomposition process in gas-oil-water multiphase flows. Based on these ECT measurements, the flow regimes and change law of the hydrate formation-decomposition process in gas-oil-water multiphase flows will be addressed. The model of the capacitance and hydrate formation-decomposition can be built up. A novel, efficiency and robust in-situ visualization-based measurement and analysis tool is researched and finally applied on the management and risk control of the hydrate plug in gas-oil-water multiphase flows in deepwater. The research background of the applier is electrical capacitance tomography and its application on the measurement of gas-oil-water multiphase flows. Applier is familiar with image reconstruction algorithms, calculation of key parameters, sensor design and etc. the kernel research tasks of this proposal include change low of equivalent dielectric constant of the hydrate, optimal ECT sensor design, image reconstruction of the hydrate formation-decomposition process and capacitance-hydrate formation and decomposition process modeling.

深水油气开采中高压、低温油-气-水多相混输管道易发生水合物堵塞，严重威胁海洋石油输送安全。在水合物形成初期进行有效、实时检测，获取多相流流型、水合物含水率等参数，掌握影响其生-消规律因素至关重要。传统分析基于软件模拟预估哪里会发生水合物，非真实测量。多数测量手段不适用海洋环境，或只能测量局部区域。本课题将电容层析成像首次用于油-气-水多相混输管内水合物生-消过程，研究解决目前无针对混输流动安全中水合物在线可视化识别状况，揭示多相流型及水合物变化规律，阐述电容与生-消过程数学关系，为有效进行海洋多相混输管内水合物生成的抑控提供一种创新、科学、可靠的在线可视化测量工具。申请人多年研究油-气-水多相流电容层析成像测量，在图像重建、流体参数计算、传感器设计、实际工业应用解决方案等方面经验丰富。本课题研究内容含水合物等效介电常数变化规律；电极优化设计；水合物生-消过程成像；电容-水合物变化数学模型。

深水油气开采中高压、低温油-气-水多相混输管道变化复杂，易发生水合物堵塞，严重威胁海洋石油输送安全。因此，对多相流动过程中的关键动态参数的在线测量及分析非常重要。在水合物未形成之前进行有效、实时检测，获取多相流流型、含水率、分相流量等参数，是掌握影响其生-消规律，了解多相流动机理的关键。本课题将电容层析成像结合微波、文丘里差压，用于油-气-水多相混输管内动态参数的监测与分析，并观察压力、温度对水合物生-消过程的影响。与此同时，采用基于经典模型结合人工智能算法，来提高对多相流气、液各分相流量的测量精度。本课题研究针对目前没有混输流动安全中水合物在线可视化识别现状，初步揭示多相流型及水合物变化与压力、温度的规律，阐述电容、电导以及微波射频信号与多相流含水率的数学关系。硬件方面，本课题研究开发一套基于电容+微波+文丘里多传感器融合的油-气-水多相流在线测量设备，设备口径为DN80，承压10MPa，实现工作温度范围 -40～80度。其中，电容层析成像模块实现8/16通道可选，SNR为70dB,采样频率300 fps。微波模块实现300/800MHz激励频率可选，采用传输线设计实现对多相流含水率的测量。算法方面，第一，探索采用ECT/文丘里经典模型结合机器学习模型，实现对液相、气相流量的在线计量，以提高测量精度。第二，采用机器学习模型结合双频微波的相位、幅值信号，以建立微波-含水率之间的数学关系。第三，采用ECT/ERT双模态，实现对油-气-水含水率的全量程测量。第四，水合物生-消过程中会同时存在四种物质，分别是油、气、水和水合物。而且这四种物质之间的介电常数相差非常大。这为水合物的可视化增加了难度。研究将ROF模型引入TOTAL VARIATION图像重建算法中，并提出了简化扩增拉格朗日（SAL）和加速交替方向乘子（AADMM）构想，以提高ECT图像重建质量。本课题的研究，对如何利用多传感融合结合人工智能算法来解释和揭示油-气-水多相流流动变化特征具有科学意义。