Since 1998, over 4000 wells completed in the low-permeability Codell formation of the 300,000 acre Wattenberg Field in northeast Colorado have been remedially stimulated with massive hydraulic fracturing treatments. This remedial program has been extremely successful. A majority of the refracturing treatments in this study have yielded higher oil and gas rates than experienced following the original treatment, performed many years previously. Fluid and proppant volumes of the remedial treatments have been very similar, but certain characteristics of the fracturing fluid correlate significantly with variability in well productivity. The main correlating parameter has been the fracturing-fluid viscosity profile (FVP), which is defined by the early-time rate of viscosity buildup, the peak viscosity developed, and the rate of viscosity degradation following the peak. For each treatment, the FVP has been evaluated with a HTHP (high temperature/ high-pressure) rheometer, using a shear and thermal history representative of the Codell treatments. Within the Wattenberg Field, there is evidence that FVP has a multi-faceted impact on well productivity that is more than just being able to place the proppant into the formation.


For this paper, we have studied more than 1,000 Codell wells, all treated with the same type of fracturing fluid (i.e., zirconium-crosslinked CMG.) Many changes have been made to the base fracturing fluid properties in an attempt to improve productivity, and although the Codell is a continuous, marine sandstone deposit, there are characteristics in the pay and bounding zones that warrant varying the fracture design for areas within the field. By recording the changing pre-job testing and job execution parameters, and correlating this data with the post-treatment well productivity, it has been possible to determine the most significant factor that effects well productivity. It was found that exceptional treatment results correlated strongly with the FVP. During the past year, there has been a significant improvement to well productivity resulting from a systematic modification of the FVP.

Measuring Well Performance

Since these wells are all restimulations, the prior well history has to be taken into account to compare well performance. This is done by utilizing a mathematical algorithm on each well that accounts for critical parameters such as cumulative and ultimate recovery factors, Gas-Oil-Ratio, original completion type, and performance of off-set wells.1 This algorithm establishes an expected performance for each well expressed in peak incremental BOE/month. The treatment results are then measured as the peak month incremental BOE which is the net gain in BOE/month. To then compare treatment performance between wells, the actual well performance is divided by the algorithm predicted performance and expressed as a percentage (i.e. >100% indicates outperforming the algorithm prediction). Figure 1 shows the results for the whole field expressed as actual/predicted results.

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