Comparison of Type Well Generation Methods for Unconventional Reservoirs

Taji O., Alp D.

SPE RESERVOIR EVALUATION & ENGINEERING, vol.24, no.3, pp.552-569, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 3
  • Publication Date: 2021
  • Doi Number: 10.2118/205022-pa
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), Chemical Abstracts Core, Communication Abstracts, Compendex, Computer & Applied Sciences, Geobase, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.552-569
  • Middle East Technical University Affiliated: Yes


Due to ultralow permeability, there is practically no pressure interference between wells producing from tight oil (approximate to 0.1 md average permeability) and shale oil reservoirs (similar to 0.001 md average permeability). This renders type well methodology as a commonly used tool for forecasting production performance of these "unconventionals." Several authors proposed different methods for constructing type wells for unconventional reservoirs, but none compared them. In this study, we compare three of the most common types of well generation methods. In the absence of real field data, individual production histories for wells are established by picking Arps decline curve parameters q(i), b, and D-i, which govern a well's production performance, from respective distributions of these parameters. Next, we compare type wells constructed using the Monte Carlo (MC) method, final cumulative (FC) method, and time slice (TS) method. Moreover, we study the impact of a possible linear correlation (also linear C) between b and D-i (comparable to field observations) on MC, FC, and TS type wells. We also study the effect of well count, and D-min value, which is the 4th parameter introduced with modified Arps equation for unconventionals. In this paper, we show that type wells generated with TS and FC methods have almost the same behavior, whereas the MC method is affected the most by stochastic experimentation, well count, and D-min.