Summary
A Barnett shale water-production data set from approximately 11,000
completions was analyzed using conventional statistical techniques.
Additionally, a water/hydrocarbon ratio and first-derivative diagnostic-plot
technique developed elsewhere for conventional reservoirs was extended to
analyze Barnett shale water-production mechanisms. To determine hidden
structure in well and production data, self-organizing maps and the
k-means algorithm were used to identify clusters in data. A
competitive-learning-based network was used to predict the potential for
continuous water production from a new well, and a feed-forward neural network
was used to predict average water production for wells drilled in Denton and
Parker Counties, Texas, of the Barnett shale.
Using conventional techniques, we concluded that for wells of the same
completion type, location is more important than time of completion or
hydraulic-fracturing strategy. Liquid loading has potential to affect vertical
more than horizontal wells. Different features were observed in the spreadsheet
diagnostic plots for wells in the Barnett shale, and we made a subjective
interpretation of these features. We find that 15% of the horizontal and
vertical wells drilled in Denton County have a load-water-recovery factor
greater than unity. Also, 15 and 35% of the horizontal and vertical wells
drilled, respectively, in Parker County have a load-recovery factor greater
than unity.
The use of both self-organizing maps and the k-means algorithm showed
that the data set is divided into two main clusters. The physical properties of
these clusters are unknown but interpreted to represent wells with high water
throughput and those with low water throughput. Expected misclassification
error for the competitive-learning-based tool was approximately 10% for a data
set containing both vertical and horizontal wells. The average prediction error
for the neural-network tool varied between 10 and 26%, depending on well type
and location.
Results from this work can be used to mitigate risk of water problems in new
Barnett shale wells and predict water issues in other shale plays. Engineers
are provided a tool to predict potential for water production in new wells. The
method used to develop this tool can be used to solve similar challenges in new
and existing shale plays.
© 2011. Society of Petroleum Engineers
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History
- Original manuscript received:
27 October 2010
- Meeting paper published:
11 February 2010
- Revised manuscript received:
8 March 2011
- Manuscript approved:
29 March 2011
- Published online:
27 September 2011
- Version of record:
13 October 2011
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