Most compositional reservoir simulation practices assume that the compositions of various fluid components are the same at all locations within the reservoir system. This constant composition assumption is incorrect and unrealistic as it grossly ignores the occurrences of some less obvious physical processes in the reservoir. Gravitational force, temperature gradient, and thermal diffusion, among other factors, contribute to distribution and gradation of hydrocarbon fluid compositions in the reservoir. Therefore, incorporating compositional grading models that adequately account for the individual and combined effects of gravity force, temperature gradient, and thermal diffusion is crucial when initializing reservoir simulation models. This research seeks to elucidate the technical implications of compositional grading on improved reserve estimation and reservoir performance prediction. The mathematical framework for the compositional grading modeling is based on one-dimensional zero-mass-flow stationary state assumption. The Computer Modeling Group’s equation of state multiphase equilibrium property simulator, WinProp, was used for the fluid modeling, while the Computer Modeling Group’s compositional reservoir simulator, GEM, was used for the reservoir modeling and simulation. In the absence of historical production data, Computer Modeling Group’s CMOST was used to perform uncertainty assessment for the validation of the initialized reservoir models. The research results show that initialized reservoir models that neglected or inadequately accounted for compositional grading effects overestimated oil in-place and underestimated gas in-place. The constant composition (without compositional grading) initialized reservoir model overestimates ultimate cumulative oil production by 14.271 MMbbl more than the isothermal compositional grading model and 24.088 MMbbl more than Kempers’ thermal diffusion compositional grading initialized reservoir model. It underestimated ultimate cumulative gas production by 30.133 Bft³ less than the isothermal compositional grading and 50.408 Bft³ less than Kempers’ thermal diffusion compositional grading initialized reservoir model. These figures suggest that neglecting compositional grading or an inadequate account of compositional grading effects in reservoir simulation initialization has detrimental technical consequences.

中文翻译：

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忽略储层模拟模型中组分分级效应的技术意义

大多数成分储层模拟实践都假设储层系统内所有位置的各种流体成分的组成都是相同的。这种恒定的组成假设是不正确和不现实的，因为它完全忽略了储层中一些不太明显的物理过程的发生。除其他因素外，重力，温度梯度和热扩散有助于储层中烃流体成分的分布和分级。因此，在初始化油藏模拟模型时，纳入足以充分考虑重力，温度梯度和热扩散的个体和综合影响的成分分级模型至关重要。这项研究试图阐明成分分级对改进储量估算和储层性能预测的技术含义。成分分级模型的数学框架基于一维零质量流稳态假设。计算机建模组的状态多相平衡特性模拟器WinProp用于流体建模，而计算机建模组的成分储层模拟器GEM用于储层建模和仿真。在没有历史生产数据的情况下，计算机建模小组的CMOST用于执行不确定性评估，以验证初始化的储层模型。研究结果表明，忽略或不足以解释组成分级影响的初始储层模型，高估了原地的石油，低估了原地的天然气。恒定成分（无成分分级）初始化的油藏模型比等温成分分级模型高14.271 MMbbl，比Kempers的热扩散成分分级初始化油藏模型高24.088 MMbbl。它低估了最终的累计天然气产量30.133英尺 088 MMbbl比Kempers的热扩散成分分级初始储层模型高。它低估了最终的累计天然气产量30.133英尺 088 MMbbl比Kempers的热扩散成分分级初始储层模型高。它低估了最终的累计天然气产量30.133英尺³小于等温组成上分级和50.408风级³比Kempers'更小的热扩散成分递变初始化储层模型。这些数字表明，在油藏模拟初始化过程中忽略成分等级或对成分等级影响的不足说明会产生不利的技术后果。