Forecasting Unconventional Volatile Oil Reservoirs Using Compositional Reservoir Simulation and Hybrid Decline Curve Models

Abstract

Despite emerging technology in the areas of unconventional forecasting, recovery factors are merely a fraction of its conventional counterparts. Unconventional reservoirs are characterized by their ultra-low permeability. It is to be noted that traditional decline curve analysis (DCA) is not best suited to forecast unconventional reservoirs. This is due, in part to a variety of reasons the most important being lengthy transition zones from transient flow to boundary-dominated flow which is highlighted in this paper via the usage of diagnostic plots. The objective of this paper is to compare the production performance of volatile oil reservoirs, generated from a commercial compositional simulator, by using simple decline models used in the industry. Fluids with different initial gas to oil ratio (GOR), due to different fluid composition, was simulated for a period of 30 years. Oil rate was forecasted by assuming different lengths of available production history. We present the application of diagnostic plots to identify different flow regime. The results from our study showed that the duration of linear flow period and the transition from linear to boundary dominated flow varies drastically based on the initial fluid composition. With respect to the decline curve analysis performed, a hybrid decline curve model was used to model different sections of the production profile. Since we are analyzing volatile oil reservoirs, the biggest challenge in performing traditional DCA is the effect of multi-phase flow behavior. So, use of hybrid decline model results in a better production forecasting compared to a single decline curve. With the advent of the shale boom, many oil and gas producers struggle to forecast unconventional reservoirs effectively. We believe that this paper serves to further elucidate the theory and application behind the concept of unconventional forecasting.