Analysis of Data from the Barnett Shale with Conventional Statistical and Virtual Intelligence Techniques
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Water production is a challenge in production operations because it is generally costly to produce, treat, and it can hamper hydrocarbon production. This is especially true for gas wells in unconventional reservoirs like shale because the relatively low gas rates increase the economic impact of water handling costs. Therefore, we have considered the following questions regarding water production from shale gas wells: (1) What is the effect of water production on gas production? (2) What are the different water producing mechanisms? and (3) What is the water production potential of a new well in a given gas shale province. The first question was answered by reviewing relevant literature, highlighting observed deficiencies in previous approaches, and making recommendations for future work. The second question was answered using a spreadsheet based Water-Gas-Ratio analysis tool while the third question was investigated by using artificial neural networks (ANN) to decipher the relationship between completion, fracturing, and water production data. We will consequently use the defined relationship to predict the average water production for a new well drilled in the Barnett Shale. This study also derived additional insight into the production trends in the Barnett shale using standard statistical methods. The following conclusions were reached at the end of the study: 1) The observation that water production does not have long term deleterious effect on gas production from fractured wells in tight gas sands cannot be directly extended to fractured wells in gas shales because the two reservoir types do not have analogous production mechanisms. 2) Based on average operating conditions of well in the Barnett Shale, liquid loading was found to be an important phenomenon; especially for vertical wells. 3) A neural network was successfully used to predict average water production potential from a well drilled in the Barnett shale. Similar methodology can be used to predict average gas production potential. Results from this work can be utilized to mitigate risk of water problems in new Barnett Shale wells and predict water issues in other shale plays. Engineers will be provided a tool to predict potential for water production in new wells.
Awoleke, Obadare O. (2009). Analysis of Data from the Barnett Shale with Conventional Statistical and Virtual Intelligence Techniques. Master's thesis, Texas A&M University. Available electronically from