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http://dx.doi.org/10.7842/kigas.2013.17.4.58

Study on Production Performance of Shale Gas Reservoir using Production Data Analysis  

Lee, Sun-Min (Dept. of Energy & Mineral Resources Engineering, Dong-A University)
Jung, Ji-Hun (Dept. of Energy & Mineral Resources Engineering, Dong-A University)
Sin, Chang-Hoon (R&D Division, Korea Gas Corporation)
Kwon, Sun-Il (Dept. of Energy & Mineral Resources Engineering, Dong-A University)
Publication Information
Journal of the Korean Institute of Gas / v.17, no.4, 2013 , pp. 58-69 More about this Journal
Abstract
This paper presents production data analysis for two production wells located in the shale gas field, Canada, with the proper analysis method according to each production performance characteristics. In the case A production well, the analysis was performed by applying both time and superposition time because the production history has high variation. Firstly, the flow regimes were classified with a log-log plot, and as a result, only the transient flow was appeared. Then the area of simulated reservoir volume (SRV) analyzed based on flowing material balance plot was calculated to 180 acres of time, and 240 acres of superposition time. And the original gas in place (OGIP) also was estimated to 15, 20 Bscf, respectively. However, as the area of SRV was not analyzed with the boundary dominated flow data, it was regarded as the minimum one. Therefore, the production forecasting was conducted according to variation of b exponent and the area of SRV. As a result, estimated ultimate recovery (EUR) increased 1.2 and 1.4 times respectively depending on b exponent, which was 0.5 and 1. In addition, as the area of SRV increased from 240 to 360 acres, EUR increased 1.3 times. In the case B production well, the formation compressibility and permeability depending on the overburden were applied to the analysis of the overpressured reservoir. In comparison of the case that applied geomechanical factors and the case that did not, the area of SRV was increased 1.4 times, OGIP was increased 1.5 times respectively. As a result of analysis, the prediction of future productivity including OGIP and EUR may be quite different depending on the analysis method. Thus, it was found that proper analysis methods, such as pseudo-time, superposition time, geomechanical factors, need to be applied depending on the production data to gain accurate results.
Keywords
shale gas; production data analysis; flowing material balance; square root time; production forecasting; stimulated reservoir volume;
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