Geosteering Methods of a Dynamic Geological Model Based on Kalman Filter

Due to the fact that existing 3D geosteering technology requires passive adjustment, and it has poor predictive qualities with the information while drilling, the author proposed a geosteering method using the dynamic geological models based on a Kalman filter (EnKF). In doing so, the researcher established an initial geological model including the current structure and attribute understanding based on the regional geological and logging data. The data for measurement while drilling (MWD) and logging while drilling (LWD) were processed using the EnKF method to yield many simulation results for the formation in the target area. Best-fit simulation results containing the best matching with the data while drilling were extracted to calculate the true thickness and dip angle of the formation in the target area. These results were input to the initial geological model to update the model structure and geological attributes. The goal was to optimize the geosteering drilling strategies under the control of the latest geological model. This method for geosteering drilling was used in the Well YP1 of the YP Oilfield in the Ordos Basin. The borehole trajectories were adjusted in time according to the MWD and LWD data, so as to get the drilling rate of high-quality reservoirs up to 92.1% in the 1901m long horizontal section of the well. The research and application results showed that the geosteering method incorporating dynamic geological models based on EnKF can use the information while drilling to pre-assess the drilled formation and actively adjust the geosteering strategy, maintaining the borehole travel in the zone of high-quality reservoirs.