Productivity Decline: Improved Production Forecasting Through Accurate Representation of Well Damage

Li, Yan (Chevron ETC) | Zaki, Karim (Chevron ETC) | Tan, Yunhui (Chevron ETC) | Wu, Ruiting (Chevron ETC) | Rijken, Peggy (Chevron ETC)



PI (Productivity Index) degradation is a common issue in many oil fields. To obtain a highly reliable production forecast, it is critical to include well and completion performance in the analysis. A new workflow is developed to assess and incorporate the damage mechanisms at the wellbore, fracture and reservoir into production forecasting. Currently, most reservoir models use a skin factor to represent the combined well damages mechanisms. The skin factor is adjusted based on the user's experience or data analysis instead of physical modeling. In this workflow, a detailed model is built to explicitly simulate the damage mechanisms, assess the dynamic performance of the well and completion with depletion, and generate a physics-based proxy function for reservoir modeling. The new workflow closes the modeling gap in production forecasting and provides insights into which damage mechanisms impact PI degradation.

In the workflow, a detailed model is built, which includes an explicit wellbore, an explicit fracture and the reservoir. Subsurface rock and flow damage mechanisms are represented explicitly in the model. Running the model with an optimization tool, the damage mechanisms’ impact on productivity can be assessed separately or in a combination. A physics-based proxy is generated linking the change in productivity to typical well parameters such as cumulative production, drainage region depletion and drawdown. This proxy is then incorporated into a standard reservoir simulator through the utilization of scripts linking the PI evolution of the well to the typical well parameters stated above. The workflow increases the reliability of generated production forecasts by incorporating the best representation of the near wellbore flow patterns.

By varying the damage mechanism inputs the workflow is capable of history matching and forecasting the observed field behavior. The workflow has been validated for a high permeability, over pressured deep-water reservoir. The history match, PI prediction and damage mechanism analysis are presented in this paper. The new workflow can help assets to: (1) history match and forecast well performance under varying operating conditions; (2) identify the key damage mechanisms which allows for potential mitigation and remediation solutions and; (3) set operational limits that reduce the likelihood of future PI degradation and maintain current performance.