Header  home

A Quick Economic Evaluation Method for Horizontal Multi-Stage Wells in Unconventional Reservoirs Using Public Domain Data

2 minutes to read

Shale gas has become an increasingly significant source of energy in the last decade especially in the U.S. and Canada. Improving completion technologies in long horizontal wells makes these plays one of the most attractive investment opportunities in oil and gas industry. The objectives of this study are to quantify the influence of individual completion parameters on the production in complex shale/tight gas formations and to predict production from large completion datasets of public domain information without having in-depth reservoir characterization.

In this research, we propose methodology to predict horizontal well performance using publically available completion data sets.  Multivariate linear regression method was used on the public domain data of 440 wells in Montney in British Columbia to build predictive model for well performance from completion parameters such as lateral length, number of stages, number of perforation clusters and amount of injected fluid and sand. Furthermore, the impact of completion parameters on well production performance was investigated; number of fracture stages and the number of perforation clusters per stage are the most important completion parameters for predicting well performance in Montney area., Then, Monte Carlo simulation have been used with advanced statistical analysis to predict well performance probabilistically by converting deterministic regression coefficients to probabilistic coefficients to account for uncertainties and parameters not considered in the model. The result showed we could match up to 95% of actual well performance.

Considering the significant of shale gas resources to supply energy in the last decade especially in the U.S. and Canada and difficulty of characterizing shale gas reservoirs, petroleum data driven analysis could offer a unique advantages of providing a predictive model for well production performance. This analysis is valuable for high level, rapid evaluation in scoping studies.