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产品展厅>>项目研发>>基于压裂停泵数据评价压裂效果研究

随着油气勘探向着复杂、低渗透和非常规储层领域不断开展,直井分段压裂、水平井多段压裂工艺等技术应用越来越广泛。目前页岩油藏普遍采用体积压裂技术实现开发,其中识别裂缝类型及规模是压裂现场急需攻克的国际难题。目前压裂效果评价主要分为三大类,均不能很好地评价压裂效果:

1、物理监测手段:采用微地震、电位监测方法、广域电磁法等实现裂缝识别,但该方法成本高、施工难度大、精度也不高,且无法获得渗透率及地层压力等参数。

2、压后压力恢复测试:页岩储层压力恢复测试不容易获得准确的地层参数和原始地层压力,且获得的裂缝半长参数是多条裂缝的一个平均值,对压裂效果的刻画不够细致。

3、压后试采数据分析:生产数据中的地面压力和流量波动大,而且井筒多相管流使得压力折算有较大的误差,且压后较长时间才能实施,这也导致返排数据分析方法难以获得准确的地层参数。

为了更好的提高储层勘探开发效果,对压裂效果开展评价分析,现场急需提出一种即时、准确、低成本的裂缝识别方法。

基于停泵压力数据的页岩气井压裂裂缝评价方法研究

国内外非常规油气藏压裂评价方法调研与应用案例剖析

压裂停泵数据分析方法在川南深层页岩气井适应性分析

非常规油气藏压裂停泵数据分析模型优化

非常规油气藏压裂停泵数据模型求解方法研究

页岩气井停泵数据评价方法现场应用

非常规油气藏压裂停泵数据分析方法现场试验

实施效果评价与分析方法优化

四川盆地海相页岩气资源主要蕴藏在埋深大于3500m的深层,储层具有埋藏深度大(大于3500m)、高温(大于100℃)、高压(大于70MPa)的特征,普遍采用多段压裂水平井进行开发,单井开发成本超过3000万元。为了稳定高效的开采页岩气,需要对压裂效果进行评价,进而制定合理的后续焖井返排制度。

通过本项目形成的压裂停泵数据分析方法,仅需在压裂过程中在井口安装压力计全程记录压裂过程中的压力数据,后续采用数据分析的方法就可以评价压裂规模,不仅成本远低于微地震等物理手段且操作简单方便。同时由于方法可以提供裂缝半长、渗透率等参数,还能够指导后期焖井和返排方案,合理规划产气制度。

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.

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