Multi-dimensional interpretation of electromagnetic data from Silai geothermal field in Kenya : comparison of 1-D, 2-D and 3-D MT inversion

Abstract

With development of MT interpretation codes and advancement in computer hardware, 3-D electromagnetic data interpretation has become attainable. This study therefore seeks to compare results of Electromagnetic data using different interpretational techniques in order to provide reliable information about the presence, location, and size of geothermal systems in Silali field. Resistivity study of the Silali area in Kenya was carried out by the combined use of TEM and MT soundings. Joint inversion of the EM data was used to correct for static shifts in the MT data, which can be severe due to large near-surface resistivity contrasts. Joint 1-D inversion of 102 TEM/MT sounding pairs and a 3-D inversion of a 97 sounding subset of the MT data were performed. Additionally 2-D inversion of the same data set was done and results are compared with those of 1-D and 3-D inversion models. The robustness of the final 3-D inversion models was tested by using three different initial models, which gave similar results with RMS of between 1.5 and 1.7 for all three models.

Similarly 2-D inversion modelling was done using two different inversion codes, REBOCC and WinGlink and their results compare fairly well. The resistivity models resulting from the inversion were elevation corrected and smoothed and are presented as planar maps and cross sections. The inverted model of electrical resistivity reveals the presence of highly resistive near surface layer, identified as unaltered formations, which covers a low resistivity cap corresponding to the smectite-zeolite zone. Beneath this cap a more resistive zone is identified as the epidote-chlorite zone (the resistive core) and interpreted as the host of geothermal reservoir. Further at depth of about 6 km an electrically conductive feature has been imaged, and has been tentatively interpreted as a heat source for geothermal system in this field. The aim of modelling EM data using all the three interpretational techniques is to compare results and establish which resistivity anomalies stand out irrespective of the dimensional inversion used. In this study results from 1-D, 2-D and 3-D models, recover near surface resistivity structure fairly well but differ somewhat at depth. The 3-D inversion however reveals much more consistent details than the 1-D and 2-D inversion confirming that the resistivity structures in the area is highly three dimensional. At depth below 6 km the three approaches give different results implying that the models do not resolve deeper structures. This has been attributed to noise in the data at long periods.