A workflow known as Real Time Productivity Steering (RTPS) has been developed to estimate productivity prior to and while drilling to complement geosteering in horizontal and highly deviated wells. Productivity estimates are made on a well's trajectory and can be compared with estimates for other possible trajectories prior to drilling and while drilling to determine which trajectory and well length will give maximum productivity.
The workflow was applied to two case studies. The first was a simulated horizontal well drilled through multiple fault blocks with varying pressure regimes. A single-well 3D numerical model based on petrophysical, geological, and reservoir data was built for making productivity estimations. Prior to drilling the well, a prejob predictive model was built. While the well was being drilled, the actual well's data were used to update the predrill single-well model. Production predictions were made at the geosteering decision points. However, before the well was steered in accordance with the geosteering decision, the well's trajectory was projected based on the geosteering decision, and productivity was forecasted. A sensitivity analysis was also performed on the projected wellbore trajectory to see if a different trajectory from that decision point could give better productivity. Factors such as impact of dogleg severity and pressure profile in the reservoir and within the wellbore were considered.
The second case study was a complex, thin bed, depleted reservoir, which had a thin oil rim. The horizontal well objective was to place the well in an optimal position and confirm placement in real time. Due to uncertainties with the depth of the oil-water contact (OWC), it was necessary to estimate productivity of the drain hole and determine the optimal drain length in the presence of OWC uncertainty.
For the first case study, the application of the workflow showed that by projecting the well trajectory at specific geosteering decision points and forecasting productivity on different trajectories, it was possible to identify, while drilling, the trajectory that would give maximum productivity. Thus the well was steered in the direction of maximum productivity. Incorporating sensitivity analysis with the productivity estimates in real time showed how the productivity of the well was sensitive to different input parameters. This sensitivity analysis was also used to identify the most significant parameter affecting the well's productivity index (PI) at each decision point. This also provided a range of PIs versus the reservoir footage based on uncertainty in the input parameters.
For the second case study, the estimated productivity by sensitizing on drain length did not justify drilling extra metreage, hence the well total depth (TD) was placed at the original planned TD. By sensitizing on the OWC in real time, it was predicted that if the OWC was 2 m higher than estimated from the petrophysical logs, it could reduce production by about 30%, which would be a huge impact on the well.
The RTPS workflow of complementing geosteering with reservoir engineering will enhance the ability to drill more productive wells because the uncertainty analysis can show additional measurements required to reduce uncertainty in PI estimation. Secondly, it will enable wells to be steered in the direction of maximum productivity, and thirdly, operators can have sufficient information while drilling to make informed decisions for completions and for future wells.