--> --> The Waterton Asset Study: An Example of Data Integration, by W.H. Asyee, K.D. Rawnsley, S. Bettembourg, M. De Keijzer, J.L. Massaferro, L. Wei; #90029 (2004)

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The Waterton Asset Study: An Example of Data Integration

W.H. Asyee, K.D. Rawnsley, S. Bettembourg, M. De Keijzer, J.L. Massaferro, L. Wei
Shell International E&P, Rijswijk, The Netherlands

 

This poster summarizes the work performed in the Shell Carbonate Development team in 2001 on the Canadian Waterton asset. Shell Canada is the major gas producer in the tectonically complex foothills of the Rocky Mountains (Southern Alberta). The Devonian and Mississippian aged tight carbonate reservoirs are situated in folded thrust stacks (sheet III, IV and IVc). The Waterton Gas fields were discovered in 1957. The Waterton proper asset has been depleted by more than 90% and remaining reserves are mainly situated in the Northern part of the structure.

The Waterton plant has been experiencing steadily decreasing throughputs since the main field experienced decline, as of the 90’s. This decline has been halted and reversed through an aggressive work over program, additional compression in the Waterton Sheets and further development of the Castle River and West Carbondale fields. Apart from this, Shell Canada is still aiming at finding and proving new reserves. 

The technical objectives of the Shell Carbonate Development team asset study were to:

  • Identify key reservoir parameters that control well performance
  • Provide robust reservoir models for future field development
  • Provide recommendations for improved well design and data acquisition to narrow uncertainties
  • Strengthen links with Shell Canada with respect to use of common models, tools, integrate skills etc.
  • Apply findings to other analogues prospects.

In the asset study team it was felt that this asset and its data had to be used as a springboard for developing and advancing technology with a wider business application. The two main conclusions of the study were the GIIP calculation that was constrained by the dynamic data showed an increase from 4.8 BCM to 9 BCM. And also the new drilling strategy is now targeting to large-scale N-S trending seismic lineaments. The integrated workflow showed to be very productive and effective in getting all information combined into a common result.

Figure 1.1

Figure 1.2