DISTORTED PRESSURE-BUILDUP TESTS BY PHASE REDISTRIBUTION – CHANGING WELLBORE STORAGE EFFECTS
Reliable data about in-situ reservoir measurements is significant in many phases of petroleum reservoir engineering. The reservoir engineer must have sufficient data and information about the reservoir to effectively analyze reservoir performance and forecast future production under various means of operation. The production engineer must know the condition of production and injection wells to choose the best possible performance from the reservoir. Much of that information can be obtained from pressure transient tests. Analysis of pressure transient data is normally done by analytical solution and modern simulation programs. Several programs are available for performing well testing analysis. In this paper, Saphir software is used along with the normal analytical models to develop and analysis the pressure build up data in a different way in order to detect and investigate the effect of wellbore phase redistribution in the test. This work is mainly performed to investigate and detect the wellbore phase redistribution (WPR) and explain the different phases and types qualitatively and quantitatively using 6 pressure transient tests, one of them is Egyptian case. The average reservoir permeability of the tested well is ranging from 9.91 md to 497 md, and the reservoir pressure covers a range from 237 psi to about 5000 psia. It presents analysis of pressure buildup, fall of tests, and DST taken from the oil field. In addition, it describes the effect of the wellbore two phase segregation of the pressure derivative curves while performing pressure buildup tests. Moreover, this work may leads to a method for eliminating or reducing wellbore phase redistribution in pressure transient tests especially in high GOR reservoir and tight oil reservoirs. It helps to better understanding the variable wellbore storage and phase redistribution mechanisms involved in the pressure buildup tests and improved physical understanding of the phase segregation process and it influences pressure buildup data. Such level of understanding is critical to our success of developing new models or approaches in order to handle field tests both from design and interpretation point of views.
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