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产品展厅>>研发&服务>>2020年试油公司光纤测试数据处理及解释技术研究

随着勘探开发的不断深入，水平井动态评价监测、水平井重复压裂方案决策、注采剖面监测提出了迫切需求，常规生产剖面测井手段无法满足该类井的生产需求，利用连续油管复合光缆测试技术，通过底带直读式CCL三参数仪可实现井筒内精准定位，通过光纤测试技术实现全井筒分段同时监测。光纤测试数据的处理解释受井筒流态、地层信息等参数的影响往往存在多解性，部分井测试解释结果与实际产量相关度低。需结合井筒流态、井筒-地层热流耦合、产层热传导、热对流等因素，开展光缆测试数据处理及解释方法研究，建立合适处理解释模型，有效评价水平井产出（注入）情况。 

 本项目研究包括海量数据的处理及图形绘制、井筒中的流体复杂流动、地层中产层中的热传导和非产层中热传导及热对流、井筒与地层中的热流耦合、和声波资料解释方法和光纤测试数据的综合评价方法，具体技术方法有：

绘制海量数据处理及图形

通过CADOProvider实现对海量深度温度数据的高效读取，形成不同时间下不同深度的温度分布云图以及三维分布动态图，可以进行温度变化及温度断面分布曲线的多尺度观测。

确定井筒热流耦合模型的建立及初始条件和边界条件

从各类数据文件导入井筒及流体的基础数据，考虑井筒内流体的速度、流态、物性的不同对流体的传热影响，建立不同管流流态的热流耦合模型。以稳态条件下连续性方程、动量方程、和能量方程求解作为初始条件，以井口处的速度分布为边界条件。

建立井筒与地层之间热流耦合

建立井筒与地层间的热交换模型。

建立井筒与地层间的流体的状态方程。

确定流体力学与热力学物性状态

确定井筒内与地层流体的粘度等物性参数以及比热容、导热系数等热力学参数。

确定产层与非产层地层区域的地层参数。

确定产层与非产层地层区域的导热系数、比热容等热力学参数。

建立井筒流动和地层渗流中的温度压力耦合模型求解方法

采用数值模拟方法求解井筒和地层中的温度压力耦合方程，数值模拟涉及到网格划分、方程离散、大型稀疏矩阵求解。网格方面，井筒内采用一维网格，地层中采用轴对称二维网格。方程离散方面温度和压力都采用有限体积离散。大型稀疏矩阵采用广义最小残量法（GMRES方法）进行求解。

探索分布式声波数据解释方法

采用组件化技术方法对光纤测试数据处理及解释软件进行开发。

由于国内至今还没有光纤测试数据处理及解释软件，国外仅仅提供解释服务，并无任何针对适用于石油天然气的光纤测试温度反演类的软件出售，无任何技术可借鉴。本项目从海量数据处理，井筒-地层热流固耦合模型求解、地层参数反演等方面开发具有独立知识产权的光纤测试数据及解释软件，具有很强的领先优势。

Products>>Project Development>>Research on optical fiber test data processing and interpretation technology of oil testing company in 2020

With the continuous deepening of exploration and development, there is an urgent need for dynamic evaluation and monitoring of horizontal wells, decision-making of refracturing scheme of horizontal wells, and monitoring of injection production profile. Conventional production profile logging methods can not meet the production needs of such wells. Using coiled tubing composite optical cable testing technology, accurate positioning in the wellbore can be achieved through bottom zone direct reading CCL three parameters instrument, and optical fiber testing technology can be used to monitor the whole wellbore simultaneously. The processing and interpretation of optical fiber test data are often influenced by wellbore flow pattern, formation information and other parameters, and the correlation between test interpretation results of some wells and actual production is low. It is necessary to study the data processing and interpretation method of optical cable test in combination with wellbore flow pattern, wellbore formation heat flow coupling, production layer heat conduction, heat convection and other factors, establish appropriate processing and interpretation model, and effectively evaluate the production (injection) of horizontal wells.

This project includes massive data processing and graphics drawing, complex fluid flow in wellbore, heat conduction in formation and non production layer, heat flow coupling between  wellbore and formation, acoustic data interpretation method and comprehensive evaluation method of optical fiber test data.

Drawing massive data processing and graphics.

By using CADOProvider, we can efficiently read the massive depth temperature data, and form the temperature distribution cloud images and three-dimensional dynamic distribution maps of different depths at different times, which can be used for multi-scale observation of temperature change and temperature cross-section distribution curve.

The establishment of wellbore heat flow coupling model and the initial and boundary conditions are determined.

The basic data of wellbore and fluid are imported from various data files. Considering the influence of different velocity, flow pattern and physical property of fluid in wellbore on the heat transfer of fluid, the heat flow coupling model of different pipe flow pattern is established. The solution of continuity equation, momentum  equation and energy equation in steady state is taken as the initial condition, and the velocity distribution at the wellhead is taken as the boundary condition.

Heat flow coupling between wellbore and formation is established 

The heat exchange model between wellbore and formation is  established, and the equation of state of fluid between wellbore and formation is established.

The physical properties of fluid mechanics and thermodynamics are determined.

Determine the viscosity and other physical parameters of wellbore and formation fluid, as well as the specific heat capacity, thermal conductivity and other thermodynamic parameters; determine the formation parameters of pay formation and non pay formation area; determine the thermal conductivity, specific heat capacity and other  thermodynamic parameters of pay formation and non pay formation area.

The solution method of temperature pressure coupling model in wellbore flow and formation seepage is established.

Numerical simulation method is used to solve the temperature and pressure coupling equations in wellbore and formation. Numerical simulation involves mesh generation, equation discretization and large sparse matrix solution. In terms of grid, one-dimensional grid is used in the wellbore and axisymmetric two-dimensional grid is used in the formation. The temperature and pressure are discretized by finite volume. The large sparse matrix is solved by GMRES method.

The distributed acoustic data interpretation method is explored

The data processing and interpretation software of optical fiber  test is developed by using component technology.

Since there is no optical fiber test data processing and interpretation software in China, foreign countries only provide interpretation services, and there is no software for optical fiber test temperature inversion applicable to oil and gas, and there is no technology to learn from. This project develops optical fiber test data and interpretation software with  independent intellectual property rights from massive data processing, wellbore formation thermal fluid solid coupling model solving, formation parameter inversion and other aspects, which has a strong leading advantage.