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由垩系Qishn上部碎屑岩是Masila区块开发区的主要产层。这个低压、低气油比油藏在初次完井后需要进行人工提升。采用电动潜油泵从这些储层中采出石油。因此,了解有关储层的初始产能对于完井设计和确定泵径大小是关键的。由于储层品质的不同和油藏间的相变,用常规岩心和测井评价法预测储层产能变得不可靠。使用一般能得到的裸眼井测井数据已开发出一种简单、有效的预测方法。这一方法使用由测井导出的归一化电阻率比值(R_n=log{(R_t/R_w)/(R_(xo)/R_(mf)})法来表征储层流体的流动性,并预测单井产能指数(PIs)使用9口井中20个含油层的井测试数据来研究相关关系,并将其常规地用于预测新开发井中的初始PIs。在Masila区块4年多来的开发和生产中,该方法被证明是有效的。 R_n技术是测井分析中常规可动油图方法的自然扩展,后者用于推断最大渗透率和可动油气带。模型简单且不受粒度大小控制。更进一步,该技术不需要复杂的岩石物性和地质分析,它使用井间一致性的测井数据集(如带有微球聚集电阻率器件的双侧向电阻率测井)。
The Upper Cretaceous Qishn clastic rocks are the main production zone in the Masila block development zone. This low-pressure, low-gas-oil ratio reservoir needs to be manually upgraded after its initial completion. Electric submersible pumps were used to extract oil from these reservoirs. Therefore, understanding the initial production capacity of a reservoir is critical for well completion design and determining the size of the pump. Due to differences in reservoir quality and phase transitions between reservoirs, predicting reservoir productivity using conventional core and logging evaluation methods becomes unreliable. A simple and effective prediction method has been developed using generally available borehole log data. This method uses the normalized resistivity ratio (R_n = log {(R_t / R_w) / (R_ (xo) / R_ (mf)}) method derived from logging to characterize the fluidity of reservoir fluids and to predict Single well productivity indices (PIs) used well test data from 20 wells in nine wells to study the correlation and routinely used it to predict initial PIs in newly developed wells. In the Masila block more than four years of development and This method has proven to be effective in production. The R_n technique is a natural extension of the conventional method of movable oil mapping in log analysis, which is used to extrapolate the maximum permeability and the moveable hydrocarbon zone. The model is simple and not subject to particle size control Further, the technique does not require complex petrophysical and geological analyzes, and it uses well-to-well log data sets such as double-sided resistivity logs with microsphere-aggregating resistivity devices.