Effective Applications of Extended Exponential Decline Curve Analysis to both Conventional and Unconventional Reservoirs
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AbstractIn the last decade, the hydrocarbon production from shale plays has increased dramatically, which has greatly impacted the petroleum industry. While this increased production has benefited the industry, at the same time these unconventional resources have presented many challenges to oil and gas reserves evaluators. One of these challenges is predicting long-term shale production performance and life, especially in a timely and reliable manner.When Arps derived the hyperbolic model in 1944, b-factor was assumed as a constant and limited to values less than or equal to 1.0. However, many literature papers and field observations have shown that the b-factor instead changes with time in shale wells and, in many cases, can be well above 1.0, especially during the transient period. As a result, evaluators have modified the original DCA ("modified hyperbolic model") to incorporate a b-factor larger than 1.0 and a minimum exponential decline rate (Dmin) at the late-time life in shale production predictions. This paper further discusses this transient b-factor effect and the benefits of the Extended Exponential Decline Curve Analysis (EEDCA), (Zhanget. al , 2015).EEDCA does not require an estimate of when to switch to a Boundary-Dominated Flow (BDF) model or when to switch to exponential decline for shale oil and gas. All of the model parameters are interdependent and can be calibrated by fitting from the first production data point. Meanwhile, the Dmin used in the modified hyperbolic model is independent from early-time data. This paper further extends the use of EEDCA by applying it to conventional wells. It shows EEDCA is a useful alternative for the Arps method while it holds certain advantages in forecasting shale production. Thus, EEDCA is an integrated solution for both conventional and unconventional reservoirs.
