Improved Workflow for EUR Prediction in Unconventional Reservoirs Conference Paper uri icon


  • Copyright 2016, Unconventional Resources Technology Conference (URTeC). This paper presents a comprehensive workflow which improves our ability to forecast future production and estimate ultimate recovery more accurately in ultra-low permeability reservoirs. These forecasts have long been problematic for the petroleum industry. The proposed workflow incorporates diagnostic plots, hybrid decline models (e.g., the Duong model for transient flow and the Arps model for boundary-dominated flow), improved data smoothing methodologies, and systematic analysis procedure for the transition flow regime between transient and boundary- dominated flow (the boundary-influenced flow regime). We have applied the workflow to situations with either single-phase or multi-phase flow in the reservoir. We have tested the workflow rigorously on data from many shale reservoirs (both dry gas and liquids rich) and found that it is more accurate than the industrys most-commonly used approach, the modified Arps decline curve model; i.e., the Arps hyperbolic decline model with a minimum terminal decline rate. The paper presents detailed results for all these reservoirs. By implementing improved practices at each step of decline data modeling, our validation analysis (based on hindcasting) showed increased accuracy averaging about 10% for production rate forecasts. In the current price environment, reliable and accurate production forecasts and EUR values have become even more vital aspects of any companys decision-making process. The proposed workflow provides a field-tested approach to achieving reliability and accuracy objectives.

name of conference

  • Proceedings of the 4th Unconventional Resources Technology Conference

published proceedings

  • Proceedings of the 4th Unconventional Resources Technology Conference

author list (cited authors)

  • Sharma, A., & Lee, W. J.

citation count

  • 20

complete list of authors

  • Sharma, Akash||Lee, W John

publication date

  • January 2016