Prediction of velocity, gas content from neural network modeling and estimation of coal bed permeability from image log in coal bed methane reservoirs: Case study of South Karanpura Coalfield, India

Abstract

P-wave velocity and gas content of major coal seams are predicted from three wells from the South Karanpura coalfield, India. Multilayered feed-forward neural network (MLFN) model is developed for prediction P-wave velocity from two wells using three input log parameters: gamma ray, resistivity and bulk density. The model is tested on coal seams: Sayal, Balkudra, Banasgarah and Argada of three wells namely; A, B and C with satisfactory goodness of fit (R² = 0.77). The ratio of P-wave and S-wave velocities (Vp/Vs) ranges from 1.68 to 3.10 in the coal seams of this field. Cleat density using image log is obtained from four major coal seams namely; Balkudra, Kurse, Hathidari, Banasgarah varying from 1/m to 11/m. Ash content varies from 15 to 51% whereas gas content of major coal seams varies from 2.30 to 4.4 10⁻3 kg/m³. There is a good correlation between ash content and Vp/Vs of coal seams under the study area. MLFN model for prediction of gas content of the above-mentioned coal seams from two well is trained with input parameters such as: Vp/Vs, bulk density, cleat density and ash content. The model estimates gas content of other coal seams: Argada from well A, Hathidari from well B and Balkudra, Kurse, Banasgarah from well C with satisfactory R² = 0.77. Maximum horizontal stress orientation is observed from azimuthal shear wave anisotropy from cross multipole array acoustic (XMAC) log for a well A. It varies from N110° to N115° in these coal seams. Permeability of coal seams are computed from X-tended Range Microresistivity Imager (XRMI) tool from a well C. Permeability of coal is varying from 0.5 md in Saunda seam to 17.29 md in Banasgarah seam. The estimated permeability matches well with the pre-fracture permeability of these seams. It is observed that increase in cleat density enhances coal seam fracture permeability in coal seam.