Enhancing Pressure Transient Analysis through the Application of Deconvolution Methods, Case Study
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Copyright © 2017 Society of Petroleum Engineers. Well testing is an integral element in reservoir and fluid characterization. It is a continuously developing discipline and has seen steady progress over the years. Interpretation techniques have evolved significantly over time, starting with straight-line analysis, then onto log-log analysis, followed by log-log derivative analysis and finally onto the newest standing technique today, deconvolution. Shutting in wells in producing fields to carry out pressure transient analysis can prove to be difficult and often expensive. Frequent short shut-ins are normally dictated by operational well requirements, however, these shut-ins are normally not long enough for the classical pressure transient analysis to be conducted. In this paper, we show how this issue can be resolved by applying deconvolution methods to aid us with pressure transient analysis for these short build up durations Deconvolution is fundamentally a mathematical algorithm used to convert variable rate data to constant rate data. In other words, it can be used to convert data into a single drawdown with a constant rate. This conversion yields to simplified analysis by allowing more of the same data to be analyzed. As a result of this approach, attaining definite conclusions about reservoir properties becomes possible. Prior to this, unclear and uncertain conclusions were often made. The data presented below was first analyzed using standard transient analysis techniques. This resulted in non-unique solutions. The data was later analyzed using the deconvolution algorithm (von Schroeter 2001). It was found that this analysis, using deconvolution, along with an understanding of the geological setting, managed to produce clear and conclusive results about the reservoir. In this paper, we demonstrate that for a given production scenario, a dedicated well test may not necessarily be required. Instead, deconvolution can be utilized on short build ups, which are often already conducted for well maintenance, leading to both clearer results and significant cost savings.
author list (cited authors)
Osman, Y., Retnanto, A., Samir, M., & Fraim, M.