| Two methods have been developed for evaluating formation permeability using log data. One method is an integrated simulation technique that can be used to analyze time-lapse logging measurements. The second method involves a multiple parameter correlation of core permeability with logging measurements. These two methods have been used to analyze field data from three Gas Research Institute (GRI) test wells.;Formation permeability controls the strategies involving well completion, well stimulation and reservoir management. In general, permeability can be evaluated from core analysis, well test analysis, and well log analysis. The most economic method to evaluate formation permeability will usually be from well logs. However, the available methods to evaluate permeability from well logging data are difficult to apply and may not be accurate. The petroleum industry needs more accurate and easier methods to estimate permeability from well logging data.;When a well is drilled, mud filtrate invades the formation around the borehole. The volume of mud filtrate lost to a formation will be a function of formation permeability, the drilling mud properties, and the time the formation is exposed to the drilling mud system. As mud filtrate invasion progresses, unique salinity profiles and, thus, unique resistivity profiles are created in the formation near the borehole. Therefore, the data from well logs change with time. By observing and analyzing the changes in well logging data versus time, one can estimate formation permeability, provided one can characterize the mud system and the mud cake behavior.;To simulate logging tool response to the mud filtrate invasion process, three simulators have been integrated using a KAPPA-PC expert system as a platform. These three simulators are (1) a two-phase, two-dimensional, fully implicit reservoir simulator, (2) a convection transport simulator, and (3) a logging tool response simulator. The permeability values for several intervals in two GRI test wells have been estimated by history matching the time-lapse logging measurements.;The new multiple parameter correlation developed in this dissertation has been applied to three GRI test wells. The advantages of the new correlation are (1) the effects of shale volume on permeability are taken into account, and (2) the uncertainty surrounding irreducible water saturation or grain diameter measurement has been eliminated. The multi-parameter correlations work well for the formations analyzed; however, the specific correlations do not apply universally.;The permeability values from simulation and correlation have been compared with the average core permeability, resulting in good agreement. The methodology developed in this dissertation can be applied to virtually any formation to estimate formation permeability from time-lapse logging data. |
