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A Generic Model for the Prediction of Sand Production in Oil and Gas Well Systems

机译:油气井系统出砂预测的通用模型

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A model is presented to predict, qualify and quantify sand production in oil and gas well systems for different reservoir types. Sand production is normally caused when the shear stresses acting on the rock surrounding the perforation cavities or well bore exceed the rock strength, which leads to rock failure. The numerical model that evolves incorporates a sanding factor K_(Ds) in the fluidized solid flow and erosional model; characterizing different reservoir types under the influence of various in-situ stresses, reservoir drawdown pressures and rock failure criteria relevant to the reservoir type The rock type and field conditions; derived directly from field observations, correlated with the characteristic modeled sanding factors K_(ds) can be used to benchmark a variety of reservoir sand producer well systems for various production and pressure profile scenarios. Using the simulated data of porosity, pressure and fluidized solid phase saturation represented as characteristic eigenvalue data points, which is derived from a characteristic deviation matrix, the solution variables can result in an efficient model to predict and quantify sand production in oil and gas reservoirs. This model representation allows the simulation of different sand reservoir producing scenarios under different production index and formation pressure profile. The numerical simulation solution strategy employed benefited from use of the Crank Nicholson finite difference as well as the Gaussian Elimination Method to solve the set of matrix of linear equations. Operators field data have being used to tuned and calibrate the model against observed production and well data logs, core and fluid property information from operator's database, which was used for the simulation program. This allows us to provisionally identify candidate sand prone wells that were considered to be most at risk from sand production as well as improve understanding of in-situ stresses, rock strength and failure processes using the sanding factors K_(ds) as important benchmarks. The results and plots of simulation studies demonstrates that using porosity deviation eigenvalues solution data simulated over the metrics of the pressure and production profile data studied in time and depth would always produced definite sand production signatures above a predetermined value of 1, in time for a specific production index and sanding factor K_(ds), which would allow the evaluation of sand produced in the reservoir. Also sand signatures were indicated by computing the standard deviation of eigenvalue data points, where standard deviation (SD) points above 1 indicates sand signatures in the reservoir flow spectrum. It is also clear from our study that high pressures draw down or low productivity of the well tends to lead to higher sand production. Also fludised solids in flow and sand production decreases and increases respectively with increasing sanding factor K_(ds), or sandstones property in the reservoir type. It is also indicated by the plots that there exist a sanding threshold critical value, Kds<0.5, above which mark the threshold of rock failure which ultimately lead to increased sand production. From our study it has been demonstrated that sand production varies inversely with the productivity or production index of the well. These important benchmarks would offer important design tradeoff advantages for higher oil and gas production rates, effective sand control strategies and cheaper well completions for specified reservoir types.
机译:提出了一个模型,用于预测,鉴定和量化针对不同储层类型的油气井系统中的出砂量。当作用在射孔腔或井眼周围的岩石上的剪应力超过岩石强度时,通常会导致出砂,从而导致岩石破裂。演化的数值模型在流化的固体流和侵蚀模型中纳入了砂磨因子K_(Ds)。在各种原地应力,储层回撤压力和与储层类型相关的岩石破坏准则的影响下表征不同的储层类型;岩石类型和田间条件;直接从现场观察中得出的结果,与特征化的打磨因子K_(ds)相关联,可用于对各种生产和压力剖面场景的各种储层出砂井系统进行基准测试。使用从特征偏差矩阵导出的代表特征特征值数据点的孔隙度,压力和流化固相饱和度的模拟数据,求解变量可以形成一个有效的模型,以预测和量化油气藏的出砂量。该模型表示允许在不同的生产指数和地层压力剖面下模拟不同的砂储层生产方案。所采用的数值模拟求解策略得益于使用Crank Nicholson有限差分以及高斯消元法来求解线性方程矩阵集。作业人员的现场数据已用于根据观察到的产量和油井数据记录,来自作业人员数据库的岩心和流体属性信息对模型进行调整和校准,这些数据已用于模拟程序。这使我们可以临时确定那些被认为最易受制砂风险的易发生砂眼的井,并使用打磨因子K_(ds)作为重要基准来提高对现场应力,岩石强度和破坏过程的理解。模拟研究的结果和图表表明,使用孔隙度偏差特征值解数据对时间和深度研究的压力和生产剖面数据的度量进行模拟,总是可以在特定时间范围内及时产生高于预定值1的确定的出砂特征。生产指数和砂磨系数K_(ds),这将有助于评估储层中产生的砂粒。还通过计算特征值数据点的标准偏差来指示砂特征,其中标准偏差(SD)大于1的点表示储层流频谱中的砂特征。从我们的研究中还可以清楚地看到,高压降或井的低生产率往往会导致更高的出砂量。此外,随着砂磨系数K_(ds)或储层类型中的砂岩特性增加,流动和出砂中的溶解固体分别减少和增加。这些曲线还表明存在打磨阈值临界值Kds <0.5,高于该值标志着岩石破坏的阈值,最终导致增加的出砂量。从我们的研究中已经证明,出砂量与井的生产率或生产指数成反比。这些重要的基准将为重要的设计折衷提供优势,以提高石油和天然气的生产率,有效的防砂策略以及特定油藏类型的较便宜的完井量。

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