Real-Time Formation Evaluation For Optimal Decision Making While Drilling: Examples From The Southern North Sea Available to Purchase

In recent years there has been a rapid growth in horizontal well completions driven by the need to reduce field development costs. Logging while drilling (LWD) technology and geosteering techniques have advanced to ensure high rates of success in reaching reservoir targets that are smaller and less clearly defined than those attempted previously. Three recent examples illustrate the benefits of these techniques where LWD data are acquired at the rig-site, transmitted real-time to the operator's office and interpreted by a multidisciplinary asset team who update formation models to enable optimum geosteering decisions. Prior to drilling the horizontal wells, prejob forward modeling based on offset well data and structural information from the earth model is performed to predict the LWD log responses along the planned well trajectory. While drilling, the formation model is refined to minimize spatial uncertainties within the reservoir and to provide a predictive model of the formation relative to the well path. This is achieved by correlating the real-time LWD logs with forward-modeled log responses. The resulting correlations constrain the position of the bit in the formation, and so apparent formation dip can be computed. Synthetic LWD logs are predicted for the projected trajectory 150 ft ahead of the bit. Uncertainties in the formation structural model are further reduced by interpreting LWD azimuthal density images retrieved between bit runs. These are processed immediately on a workstation in the operator's office and provide dip information to constrain the structural interpretation and lateral changes in stratigraphic thickness. The image data also provide facies information and in these wells help identify zones of higher permeability. Three case studies show how using geosteering based on predictive real-time modeling can help manage the risk associated with drilling horizontal wells by reducing positioning uncertainties. They also show how optimizing well placement improves well productivity.