Abstract

After a successful decade of exploration and development activities in major tight/shale reservoirs, the industy now has access to incredible sets of data, modeling tools, and technologies for multi-fractured horizontal well (MFHW) completion. A review of the available data and models shows that performance of a MFHW is governed by hydraulic facture properties (dimension, conductivity, and distribution) and reservoir fluid and rock characteristics (reservoir fluid properties, and rock storage and flow capacities). Workflows are required to link the characterization attempts (reservoir and MFHW), learnings from completion expriments, modeling approaches (reservoir and fracture modeing) and pettern recognition exercises (relationship between well performance metrics and the governing parameters).

In the current study, an interative workflow is proposed for design and optimization of MFHW completion based on a mixed-method approach combining three major paradigms: experiments, modeling, and data science. Each cycle of the workflow starts with data gathering and characterization of reservoir fluid and rock, followed by reservoir and fracture modeling, statistical analysis, updated design, economc analysis, and ends with implementation, monitoting and data analysis. The first cycle of the workflow is the most time-consuming and tedious one which requires a great deal of discussions and instructions.

The proposed workflow is tried on a population of Montney gas condensate wells. Rate-transient analysis (RTA) and numerical reservoir modeling were applied to a group of 16 Monteny gas condensate wells with detailed daily production and flowing pressure data. Further, a simplified RTA-based approach and statistical analysis were applied to more than 90 Montney gas condensate wells (from the same region) with publically available production data.

A new design with optimized completion paramteres is obtained from the results of RTA, numerical reservoir modeling, statistical and ecnomic analyses. The new design is applied to six new wells in the same area. The average performance of the new wells is reasonably close to the predicted performance by the proposed workflow. The workflow is believed to optimize the well performance, save the operator millions of dollars through optimization, and give the management and technical teams confidence in the next phase of corporate planning.

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