Study On The Method Of Predicting While Geosteering Drilling

During the horizontal well drilling, it is very important to know theposition of the geological target and maintain the well path at a constantrelative position within the target while developing complicated reservoirs orthin reservoirs, which is also a key technique problem of geosteeringdemanding an immediate solution at present in china.Based on the key project of SinoPec---'Research on GeosteeringTechniques', this thesis mainly studies on the methods of predicting whilegeosteering drilling. After analysis of the well-logging parameter, drillingparameter and MWD data, some new methods are proposed to predict thegeological data and the trajectory data at the bit by some new informationprocessing techniques, and they can be used to geosteer the well whiledrilling in real time.The main contributions are as follows:1. A new method for predicting the gamma ray at the bit position isproposed based on support vector machine (SVM).The predicted gamma raycurve is then corrected by the data measured by LWD sensor along the wellpath, and the resistivity curve is predicted also. Experimental results show theproposed method can estimate the gamma ray and the resistivity curve at the bit effectively, and it can be used to geosteer the well while drilling in realtime.2. A novel wellbore trajectory prediction model is founded using thekalman filter, which is based on parameter estimation theory. It is used topredict the well inclination and azimuth angles. The experimental resultsshow that the proposed model is effective.3. Another well trajectory prediction model is established based on thecombination of time series and the SVM. The basic idea of this method is topredict the wellbore trajectory by learning using the trajectory data measuredby MWD. The experimental results show that the proposed method hashigher precision compared with the traditional methods and can be easilyused.