Forecasting oil production for Oligocene C sequence, X field, Cuu Long basin using logistic growth model

N. Bui, A. Le, Muoi Nguyen, H. M. Nguyen
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Abstract

Hydrocarbon production forecasting for the field lifetime in the short and long term is an important phase, the accuracy of this process plays a tremendous role in giving the decision of reasonable field management and development. In this article, the logistic growth models using the function MATLAB’s ‘nlinfit’ have been built to forecast oil production yield for the Oligocene C sequence, X field, Cuu Long basin. Thanks to the combination with the history matching process, the logistic growth model expressed high accuracy, the results of the model are very close to the actual production data with a relative error of 1,85%. The article analyzed and evaluated the production parameters of wells obtained when building logistic growth models such as the time at which half of the carrying capacity has been produced, the steepness of the decline of the rate, and the production rate of the wells at the forecast time. Without applying any improved oil recovery method, the decline of the rate of all wells approaches 100 bbl/d before reaching the validity period of the oil and gas contract. This is the basis for operators to establish and improve field development plans.
运用logistic增长模型预测库龙盆地X油田渐新统C层序产油量
油田生命周期的短期和长期油气产量预测是油田生命周期的一个重要阶段,其准确性对油田的合理管理和开发决策起着重要的作用。本文利用MATLAB的“nlinfit”函数建立了逻辑增长模型,对库龙盆地X油田渐新统C层序进行了产量预测。由于与历史匹配过程相结合,物流增长模型表现出较高的准确性,模型结果与实际生产数据非常接近,相对误差为1.85%。本文对建立logistic增长模型时得到的井的生产参数进行了分析和评价,如已生产一半承载能力的时间、速率下降的陡峭程度、预测时间井的产量等。在未采用任何改进采收率方法的情况下,所有油井的采收率下降幅度接近100桶/天,直至油气合同到期。这是作业者制定和改进油田开发计划的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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