Murat Cinar

An Investigation of Recent Deconvolution Methods for Well-Test Data Analysis

In this work, we present an investigation of recent deconvolution methods proposed by von Schroeter et al. (2002, 2004), Levitan (2005) and Levitan et al. (2006), and Ilk et al. (2006a, b). These works offer new solution methods to the long-standing deconvolution problem and make deconvolution a viable tool for well-test and production-data analysis. However, there exists no study presenting an independent assessment of all these methods, revealing and discussing specific features associated with the use of each method in a unified manner. The algorithms used in this study for evaluating the von Schroeter et al. and Levitan methods represent our independent implementations of their methods based on the material presented in their papers, not the original algorithms implemented by von Schroeter et al. and Levitan. Three synthetic cases and one field case are considered for the investigation. Our results identify the key issues regarding the successful and practical application of each method. In addition, we show that with proper care and attention in applying these methods, deconvolution can be an important tool for the analysis and interpretation of variable rate/pressure reservoir performance data.

A Comparative Study of Recent Robust Deconvolution Algorithms for Well-Test and Production-Data Analysis

In this work, we provide a comparative study of recently proposed deconvolution algorithms which were designed to function in the presence of reasonable levels of noise in both the rate and pressure input data. The algorithms considered for comparison are those presented by von Schroeter et al., 1,2