利用递减趋势分析技术初步估算油田储量的非常规方法

Celestine A. Udie, F. Faithpraise, Agnes Anuka
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引用次数: 0

摘要

重点介绍了利用非常规方法估算储量、采收率和时间的方法,以减少油田开发中的挑战。对利用长、短生产数据估计储量、产量的一般信息进行了整理。将整理后的数据按时间绘制成产量递减曲线。这些曲线用于估计下降速率趋势和常数。然后利用递减常数预测储量累积采收率。将速率趋势外推到弃井,以估计初始储量、采收率和相应的时间。为了准确性,将储量值与现场值进行比较。结果表明,利用长时间生产历史数据建立的评价模型准确率为99.98%,而利用短时间生产历史数据建立的评价模型准确率为98.64%。模型验证后采用。验证曲线用于建立控制模型,最终用于估计累积储量采收率和初始就位。结果表明,采用速率递减趋势技术可以实现准确的储量、采收率和时间估算。
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Unconventional Method of Estimating Oilfield Reserve Initially in Place Using Decline Trends Analyses Techniques
Methods to estimate reserves, recovery factor and time are highlighted using uconventional method, to reduce the challenges in an oilfield development. General Information about reserves production estimation using long and short production data is collated. The collated data are plotted against time to build production decline curves. The curves are used to estimate the decline rate trends and constants. The decline constant is then used to predict reserves cumulative recovery. The rate trend is extrapolated to abandonment for estimation of reserves initially in place, recovery factor and the correspondent time. The reserves values are compared with field values for accuracy. It was observed that the result using data from long time production history accuracy was 99.98% while evaluation models built with data from short production history accuracy was 98.64%. The models are then adopted after validation. The validated curves are used to build the governing models which are finally used in estimating cumulative reserves recovery and initially in place. It is concluded that accurate reserves, recovery factor and time estimation challenges can be achieved/matched up using rate decline trend techniques.
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