LAUSR

Abstract Eliminating wellbore storage (WBS) effects inherent in pressure transient data is one of the challenges in well test analysis. The available WBS-removal techniques are either direct or time-consuming approaches. The direct methods are mostly unstable and require accurate data with almost no noise. However, well test data often have noise in both rate and pressure measurements. This work discusses the development of a stable technique to overcome the shortcomings in the available WBS-removal methods. The technique presented here takes advantage of the recently developed stable deconvolution algorithms (e.g. von Schroeter algorithm) to achieve a stable WBS-removal process. The developed approach provides longer WBS-free reservoir response signal (extended over the entire test duration) than the previous methods. In addition, the approach introduced here can remove WBS-effects in noisy data and does not require sandface rate measurements. Different simulated and field examples were used to validate the proposed approach. The examples included data with different levels of rate and pressure measurement errors and covered wide variety of well/reservoir models. The available approaches were implemented to the same examples. A comparison of the results shows the superiority of the approach presented in this paper.