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Characterization and estimation of gas-bearing properties of Devonian coals using well log data from five Illizi Basin wells (Algeria)

Rafik Baouche, David A. Wood

(Published: 2020-09-12)

Corresponding Author and Email:David A. Wood,; ORCID:

Citation:Baouche, R., Wood, D.A. Characterization and estimation of gas-bearing properties of Devonian coals using well log data from five Illizi Basin wells (Algeria). Advances in Geo-Energy Research, 2020, 4(4): 356-371, doi: 10.46690/ager.2020.04.03.

Article Type:Original article


In Algeria, wells drilled in the Illizi Basin suggest the presence of a significant areal trend of Devonian coal seams with the thickest coal seams penetrated in the Lower. Devonian stratigraphic unit F6. This makes them some of the oldest thick coal seams encountered. These coals exist between approximately 1500 and 4000 meters below surface. In particular, numerous coals in these formations drilled in the Oudoume field have recorded gas shows while drilling. A study of basic well log data from five wells penetrating Illizi Basin coals is conducted to characterize their distribution and provisionally evaluate their gas-bearing potential using petrophysical analysis coupled with machine learning. As imple multi-layer perceptron model (one hidden layer with four nodes) is used in a novel way to replicate estimates of gas saturation in the coal samples calculated approximately with the modified Kim equation. It does so by considering three commonly measured well-log variables: gamma ray, sonic travel time, deep resistivity (307 data records from the five wells studied). The log-calculated approximations (modified Kim equation) can be matched to better than plus or minus 1 scf/ton by the multi-layer perceptron model.The results and analysis presented provide preliminary encouragement that suggests the presence of a potentially extensive gas-bearing Devonian coal trend in the Illizi Basin that is worthy of further exploration. Future work is required to integrate data from additional wells and laboratory analysis of core samples to verify the extent of that coal trend and to quantify its gas concentrations.

Keywords:Illizi Basin coals Algeria, coal-bed methane potential, Devonian coal seam areal trend, gas content estimates by modified Kim equation, machine learning.


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