Mapping the Barnett Shale Gas With Probabilistic Physics-Based Decline Curve Models and the Development of a Localized Prior Distribution

Holanda, Rafael Wanderley de (Texas A&M University) | Gildin, Eduardo (Texas A&M University) | Valko, Peter P. (Texas A&M University)


Monthly production data can be easily obtained from public and commercial databases, and are essential information to assess the performance of operators across different fields. Additionally, analyzing the production of the wells via maps is helpful in the visualization of general aspects of the field geology and potential identification of sweet spots. In this context, decline curve models are a feasible choice to process the available production data, because this is the only data required by these models, they have a reduced number of parameters which can be promptly history matched and analyzed, and they provide production forecasts and estimated ultimate recoveries (EUR's). As summarized in the work of Arps (1945), decline curve analysis has been applied to predict oil production since the beginning of the last century. Arps (1945) presented differential equations for the rate-time relationship, which resulted in the exponential, harmonic and hyperbolic models. Although initially these models were derived from empiricism, subsequent works attempted to explain those equations from a fluid flow perspective (Fetkovich, 1980; Camacho-Velázquez, 1987; Camacho-Velázquez and Raghavan, 1989). However, in unconventional reservoirs, the Arps equations are not a reasonable extrapolation for the extended transient flow period, because it does not account for a transition to boundary dominated flow and results in an infinite EUR (Lee and Sidle, 2010).