In this work, curves of current dimensionless potential versus recovery factor are computed with models of hydrocarbon production systems. Additionally, a method to estimate production profiles using curves of current dimensionless potential versus recovery factor is presented. The author introduces three definitions, (1) the “production potential” is the maximum rate of hydrocarbon delivery for a production system at a given recovery factor. (2) The “maximum production potential” is defined as the maximum rate of hydrocarbon delivery at initial recovery factor. (3) The “current dimensionless potential” is defined as the production potential normalized by the maximum production potential. Several cases and modeling approaches, using coupled models of reservoir, well and gathering network are used. The reservoir was modelled using two approaches: a tank model (material balance equation) and a three-dimensional (3D) simulator. This work studies the effect of changes to the production system on the curve of current dimensionless potential, and how to handle such changes over the lifetime of the field when computing production profiles. It also discusses production scheduling using multiple curves of current dimensionless potential. Expressions and curves of current dimensionless potential versus recovery factor were derived using Arps decline equations and production data of a Norwegian offshore dry gas field.

Results

show that the curve of current dimensionless potential is not affected significantly by (1) changes in number of wells, (2) initial surface volume in place, (3) layout of gathering system, (4) pipe and tubing diameter, (5) artificial lift and (6) formation permeability. However, the curve is strongly dependent on (1) reservoir drive mechanism, (2) model components considered in the flow-path from reservoir to separator and (3) model upstream and downstream boundary pressures. Curves of current dimensionless potential derived with the Arps exponential decline equation are similar to the results of the dry gas study case.

中文翻译：

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根据碳氢化合物生产系统模型计算的当前无量纲电势与采收率的关系曲线的观察和使用

在这项工作中，当前的无量纲电势与采收率的关系曲线是用烃生产系统的模型计算出来的。此外，提出了一种使用当前无量纲电势与采收率的曲线估算产量曲线的方法。作者介绍了三个定义，（1）“生产潜力”是在给定的采收率下，生产系统中最大的碳氢化合物输送速率。（2）“最大生产潜力”定义为在初始采收率下的最大油气输送速率。（3）“当前无量纲电势”定义为通过最大生产电势标准化的生产电势。使用储集层，井网和收集网的耦合模型的几种情况和建模方法。使用两种方法对储层进行建模：储罐模型（物料平衡方程）和三维（3D）仿真器。这项工作研究了生产系统的变化对当前无量纲电势曲线的影响，以及在计算生产曲线时如何在整个生命周期中处理这种变化。它还讨论了使用当前无量纲电势的多条曲线的生产计划。使用Arps下降方程和挪威海上干燥气田的生产数据，得出了当前无量纲电势与采收率的关系式和曲线。以及在计算生产资料时如何处理整个生命周期中的此类变化。它还讨论了使用当前无量纲电势的多条曲线的生产计划。使用Arps下降方程和挪威海上干燥气田的生产数据，得出了当前无量纲电势与采收率的关系式和曲线。以及在计算生产资料时如何处理整个生命周期中的此类变化。它还讨论了使用当前无量纲电势的多条曲线的生产计划。使用Arps下降方程和挪威海上干燥气田的生产数据，得出了当前无量纲电势与采收率的关系式和曲线。

结果

表明当前无量纲电势的曲线不受以下因素的显着影响：（1）井数的变化；（2）初始表面体积就位；（3）收集系统的布局；（4）管道和管道直径；（5）人工举升和（6）地层渗透率。但是，该曲线在很大程度上取决于（1）储层驱动机制，（2）在从储层到分离器的流路中考虑的模型分量以及（3）建模上游和下游边界压力。用Arps指数下降方程得出的无因次电流曲线与干燥气体研究案例的结果相似。