Analysis of gas production data via an intelligent model: application to natural gas production

Abstract

Predicting the future oil and gas production rate and evaluating oil/gas reserves are very challenging issues. Many engineers have found decline curve analysis a useful approach (Ahmed, 2010; Arps, 1945; Ebrahimi, 2010; Fetkovich, 1980; Gentry, 1972; Li and Horne, 2005; Ling and He, 2012; Oghena, 2012; Shirman, 1999; Zheng and Fei, 2008). The production rate or cumulative production at a constant bottom-hole pressure declines with time (Ahmed, 2010). Since mechanisms affecting the production are constant throughout the lifetime of a reservoir, extrapolating decline curves is used to forecast the future production rate. To do so, initial production rate, the decline curvature, and its rate should be considered (Ahmed, 2010). Arps’s equations are fundamental for the most heuristic and conventional decline curve analysis models (Arps, 1945). Arps demonstrated that the hyperbolic family of equations can express mathematically the curvature behaviour of the production rate versus time curve. The Arps (Arps, 1945) equations are divided into three categories, including exponential, hyperbolic, and harmonic decline curve models. Fetkovich (Fetkovich, 1980) proposed type curves for analysing decline curves. The procedure of type curve matching is summarized by the visual matching with log-log paper that includes pre-plotted curves of production data. Each of the curves has characteristics which can be shown when plotting them on Cartesian, semi-log and log-log scales as shown in Figure 1.