Empirical Methods for Detecting Regional Trends and Other Spatial Expressions in Antrim Shale Gas Productivity, with Implications for Improving Resource Projections Using Local Nonparametric Estimation Techniques

• Published in: Natural resources research (New York, N.Y.) N.Y.), 2012-03, Vol.21 (1), p.1-21
• Main Authors: Coburn, Timothy C., Freeman, Philip A., Attanasi, Emil D.
• Format: Article
• Language: English
• Subjects: Algorithms; Chemistry and Earth Sciences; Clustering; Computer Science; Devonian; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; Empirical analysis; Estimation; Exact sciences and technology; Fossil Fuels (incl. Carbon Capture); Gas production; Geography; Mathematical Modeling and Industrial Mathematics; Metallic and non-metallic deposits; Mineral Resources; Oil and gas production; Physics; Shale; Shale gas; Shales; Statistics for Engineering; Sustainable Development; Trends
• ISSN: 1520-7439; 1573-8981
• DOI: 10.1007/s11053-011-9165-x

The primary objectives of this research were to (1) investigate empirical methods for establishing regional trends in unconventional gas resources as exhibited by historical production data and (2) determine whether or not incorporating additional knowledge of a regional trend in a suite of previously established local nonparametric resource prediction algorithms influences assessment results. Three different trend detection methods were applied to publicly available production data (well EUR aggregated to 80-acre cells) from the Devonian Antrim Shale gas play in the Michigan Basin. This effort led to the identification of a southeast–northwest trend in cell EUR values across the play that, in a very general sense, conforms to the primary fracture and structural orientations of the province. However, including this trend in the resource prediction algorithms did not lead to improved results. Further analysis indicated the existence of clustering among cell EUR values that likely dampens the contribution of the regional trend. The reason for the clustering, a somewhat unexpected result, is not completely understood, although the geological literature provides some possible explanations. With appropriate data, a better understanding of this clustering phenomenon may lead to important information about the factors and their interactions that control Antrim Shale gas production, which may, in turn, help establish a more general protocol for better estimating resources in this and other shale gas plays.