# title
Practical Considerations for Forecasting Production Data in Unconventional Reservoirs  Variable Pressure Drop Case

# abstract
<jats:title>Abstract</jats:title>                <jats:p>The premise of this work is the development, validation, and application of a methodology to forecast production data in unconventional reservoirs where variable rate and pressure drop producing conditions are typically observed. In unvonentional reservoirs, it is not common practice to maintain or even arrive quickly upon a constant flowing bottomhole pressure which is the primary assumption for the application of traditional time-rate decline curve analysis. As a result the application of traditional time-rate relations to these cases yields misleading results (i.e., EUR values) at best.</jats:p>                <jats:p>Our methodology involves the application of the rigorous convolution/superposition theory with the pressure drop normalized "empirical" rate decline relations as the "well/reservoir" model and the "measured/calculated" pressure drop data. Diagnostic plots of the loss ratio and the loss ratio derivative, or the so called "qDb" plots, are utilized to minimize the non-uniqueness inherent in the history matching process by providing guidance in the selection of rate decline model parameters. Following the selection of model parameters, the normalized rate decline relations are superposed with pressure (or pseudopressure) drop data to achieve a history match and, correspondingly, a production forecast.</jats:p>                <jats:p>Validation and application of the methodology is demonstrated using a variety of synthtic data generated to closely represent common operational practices in tight/shale oil and gas plays. A special emphasis is placed on handling non-linearities and performing sensitivities to account for future drawdown management. We show that the methodology effectively removes pressure variations from the rate history for each of the synthetic examples presented. We present our results using a variety of diagnostic and forecasting plots and both the magnitude of the EUR and the shape of the production profile for all cases.</jats:p>                <jats:p>Introduction</jats:p>                <jats:p>Decline curve analysis (DCA), or the extrapolation of only "time-rate" production data into the future, is one of the most commonly used techniques in the petroleum industry to estimate ultimate recovery (EUR) for producing wells. Essentially decline curve analysis refers to the calibration of a time-rate model, or decline curve, to a single well (or multiple wells) and extrapolating production to an abandonment limit to yield an estimate of ultimate recovery.</jats:p>                <jats:p>he simplicity of the method along with the fact that production from conventional reservoirs honors most of the underlying assumptions have led to Arps' hyperbolic and exponential decline curve relations becoming the industry standard for production forecasts (Arps 1945). Johnson and Bollens (1927) laid the foundation for the exponential and hyperbolic relations when they introduced the loss ratio and the derivative of the loss ratio which are given below.</jats:p>

# authors[].organizations[].label
Texas A&M Engineering Experiment Station (TEES)

# authorList[]
Collins, P., Ilk, D., & Blasingame, T. A.