Data Mining and Statistical Analysis of Completions in an Unconventional Play: The Canadian Montney Formation

Abstract

The drilling, completion, and stimulation of multiple fractured horizontal wells has proven to be an effective means of extracting hydrocarbons from unconventional resources. Since the first application of this technology by Maersk in the Dan Field in the mid-1980's oil and gas reservoirs have seen improved productivity and profitability. However, identifying the key drivers for success of multiple fractured horizontal well technology has proven difficult especially in unconventional reservoirs where data is limited. With few vertical wells, logs and core data typically used for building a basis of completion and stimulation design are often lacking. As a result, other methods of identifying success drivers must be developed and utilized. To this end, this paper utilizes a data-mining and statistical analysis of well, completion, fracture stimulation, and production data to establish the important parameters for success in horizontal wells in the Montney Formation of Alberta and British Columbia, Canada. In this study more than 3,300 horizontal wells were characterized with respect to lateral length, completion type, number of stages, fracture fluids pumped, proppant loading, costs, and production. The study utilized the statistical software JMP to identify key relationships between well data. The software system allowed standard screening and more advanced graphical methods to be applied to validate the dataset. From the quality assured dataset various additional parameters were calculated and used in the analysis. Both regression analysis and statistical 'heat maps' were used to correlate and visualize data trends. Heat maps are shown as a useful tool for visualizing strongly trending data. Another finding from this study is that cased and cemented horizontal wells in the Montney Formation had significantly better initial productivity (+31%) and first year cumulatives (+42%) than open hole external packer completion systems even though the cased and cemented wellbores had fewer stages (-40%), larger stimulations (+390%), and increased costs (+14%). While additional completed stages may increase cumulative recovery in the Montney Formation, statistical analysis demonstrates the recovery per stage decreases after a certain stage density. This conclusion is consistent with recent findings (VISAGE and Jim Gouveia 2014). Results of the study clearly demonstrate that wells with the smallest frac fluid load recovery have the best cumulative gas recovery with time, and spending more for the completion translates into higher production. This work is important as it identifies relevant completion trends in the Montney Formation and completion and stimulation practices linked to higher recovery and well success. This is also the first field-wide statistical review of wells completed in the Montney Formation using more advanced data mining and statistical analysis. The work lays a foundation for application of these techniques to more unconventional and tight oil and gas reservoirs.

Meeting Name

Unconventional Resources Technology Conference (2015: Jul. 20-22, San Antonio, TX)

Department(s)

Geosciences and Geological and Petroleum Engineering

Keywords and Phrases

Data mining; Horizontal drilling; Horizontal wells; Natural gas well completion; Oil well drilling; Petroleum engineering; Petroleum reservoir engineering; Productivity; Quality control; Recovery; Regression analysis; Resource valuation; Statistical methods; Statistics; Well completion; British Columbia , Canada; Fracture stimulation; Fractured horizontal wells; Oil and gas reservoir; Statistical software; Tight oil and gas reservoirs; Unconventional reservoirs; Unconventional resources; Well stimulation

Geographic Coverage

Canada

International Standard Book Number (ISBN)

978-1613994337

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2015 Society of Petroleum Engineers(SPE), All rights reserved.

Publication Date

01 Jul 2015

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