Many oil fields within the Niger Delta have been abandoned after serving their estimated life time largely due to large uncertainties and risks associated with many subsurface complexities and often limited and/or inconsistent surveillance data coupled with the convectional static characterization of the reservoir bodies as is the case of the X- oil Field, south eastern onshore, Nigeria. This research presents a pragmatic approach of integrated dynamic reservoir modelling with uncertainty management techniques, which resulted in robust productivity of the abandoned oil field. The objective is to run and improve comprehensive sensitivity analysis of petrophysical properties in the reservoir, develop PVT analysis, and predict acceptable original oil in place (OOIP), comprehensive production history and expected cumulative oil recovery factor (RF). Integrated dynamic reservoir modelling of static interpreted reservoirs of two vertically stacked reservoirs (A and B) was done. The analysis identified reservoir A with an OWC at 5520 ft with thickness of about 300 ft and STOIIP of 59 MMSTB has an underlying reservoir B with OWC at 6100 ft with thickness of about 300 ft and STOIIP of 21 MMSTB. Average permeabilities and porosities of both reservoirs range from 2.54 to 1115.2 md and 0.2 to 0.33 respectively, with estimated cumulative oil production of 46.62 MMSTB at 55% RF in reservoir A and 17.21 MMSTB at 48% RF in reservoir B. This was estimated to correspond to maximum cumulative oil production of 40 MMSTB by August 2020 indicating that the overall recovery from the field could potentially be increase by 6% from drilling infill wells with drainage targets. Production data analysis indicates that the recovery factors and well recoverable volumes are highly correlated to average net oil pay. The correlations may be used for reserve quality control. It is recommended that improved quality of data couple with integration of statics with dynamic modelling should be a priority to reduce uncertainties and solve problems in situ in field operations leading to increase in oil recovery during activation of abandoned oil field.

尼日尔三角洲内的许多油田在其估计的使用寿命后就被废弃了，这主要是由于与许多地下复杂性相关的巨大不确定性和风险，以及通常有限和/或不一致的监测数据以及储层的对流静态特征。尼日利亚东南陆上X油田的案例。这项研究提出了一种实用的方法，即采用不确定性管理技术对动态储层进行综合建模，从而使废弃油田的生产率提高。目的是运行和改善储层岩石物性的综合敏感性分析，开展PVT分析，并预测可接受的原位油（OOIP），全面的生产历史和预期的累计采油率（RF）。对两个垂直堆叠的油藏（A和B）的静态解释油藏进行了集成的动态油藏建模。分析确定了储层A，其OWC在5520英尺处，厚度约为300英尺，STOIIP为59 MMSTB，下面的储层B在其下储层B中，OWC在6100英尺处，厚度为约300 ft，STOIIP为21 MMSTB。两个油藏的平均渗透率和孔隙率分别为2.54至1115.2 md和0.2至0.33，在油藏A中RF占55％时，估计累计产油量为46.62 MMSTB，在油藏B中RF占48％时的累计产油量为17.21 MMSTB。到2020年8月，最大累计石油产量将达到40 MMSTB，这表明通过钻探有排水目标的填充井，油田的整体采收率可能会提高6％。生产数据分析表明，采收率和可采量与平均净油价高度相关。相关可以用于储备质量控制。建议将提高数据质量以及将静态信息与动态建模集成在一起作为优先事项，以减少不确定性并解决现场作业中的问题，从而在废弃油田的活化过程中提高采收率。