原始油藏就地估计的挑战:地质参数不均匀油田的最佳方法选择

Ismail Magomadov, Saad Balhasan, Shakier Khalifa, M. Awad, Saad Yaqoob
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引用次数: 0

摘要

准确的原始储量(OOIP)估计是一个严重的行业问题,不仅是由于经济问题,而且是由于油田的寿命和开发的成功。EE-Pool资源规模的不确定性是由于储层面积和净产层的独特价值。储层面积和净产层的不确定性也影响了估计储量,导致错误地预测了储层潜力。为了降低与EE-Pool不确定性相关的技术和经济风险,采用了一种应用不同OOIP确定技术方法的数据分析方法。EE-Pool包含大量数据:生产数据、PVT数据、压力数据、试井数据、岩石性质数据和地质数据。根据物质平衡方程(直线法)估计,两个地区的OOIP值为1亿储罐桶石油(MMSTB),并已确定为参考值。与OOIP参考值相比,体积法结果最差,误差为63%,MMSTB为63。而蒙特卡罗模拟与水晶球相结合的结果最为乐观,误差为9.1%,产油量为9.1百万桶。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges in Original Oil-In-Place Estimation: Selection of the Best Method for a Field with Non-Uniform Geological Parameters
Accurate original oil in place (OOIP) estimation is a serious industry concern, not only due to the economic issues but also the further field life and success of the development. The uncertainty surrounding the EE-Pool resource size is due to the unique values of the reservoir areas and net pay. This uncertainty in the reservoir area and net pay has also affected the estimated reserves, resulting in wrongly predicted reservoir potential. In order to reduce technical and economic risks associated with the uncertainty of EE-Pool, a data analytics approach applying different methods of OOIP determination techniques was used. EE-Pool contains a heavy amount of data: production data, PVT data, pressure data, well testing data, rock properties data, and geological data. The value of OOIP from the Material Balance Equation (Straight-Line method) was estimated at 100-million stock tank barrels of oil (MMSTB) for both areas and has been determined as a reference value. Compared with the reference value of OOIP, the volumetric method demonstrated the worst result with 63-% error and 63 MMSTB. While the Monte Carlo Simulation combined with Crystal Ball provided the most optimistic results with 9.1-% error and 9.1 MMSTB of oil.
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