Integrated Asset Modeling: Modernizing the Perspective for Short-Term Forecasting and Production Enhancements

摘要

Declining production and dwindling reserves are a main challenge for many mature fields. For such fields rejuvenation projects are common and may include the use of an integrated operations (IO) or digital oilfield (DOF) system as an asset management decision support tool. Forecasting future production in the short- term is a key part of the asset decision making process. However, in traditional practice with multiple locations and teams modeling in silos, not all production system interactions are considered for short- term decision making. In many cases, short-term production (STP) forecasting is done using a simplistic analytical approach, in which a decline rate is used to forecast, and the forecast is adjusted on a monthly basis. Many assumptions are made, which limits realistic prediction of field potential by ignoring reservoir- network interactions. This can result in large deviations from actual production in fields with secondary or tertiary recovery and preclude the engineers understanding what is actually happening in their production system. The objective of this work was to provide a streamlined methodology for making short-term forecasts using integrated models that help engineers better understand the interactions between different parts of the production system. This would provide a proactive approach to managing the production. To recognize the true potential of the asset, an "integrated asset model" is introduced as part of a DOF or IO project with state-of-the-art modeling techniques that models the asset as a whole unit rather than isolated silos. The integrated asset model framework used in this work includes eight dynamic reservoir models coupled to a production network model and a complex process facilities model. Although such an integrated model is expected to provide improved forecasts, it is can also be time consuming to keep the model updated. To mitigate this, the integrated asset model framework is also supported by an underlying system that keeps the model up-to-date by incorporating the latest production data to reflect current reservoir/production changes making it "live" and always ready for predictions. The model has been modified to support detailed modeling of events and activities. For STP, the workflow automates calculation of well and field potentials as well as planned/unscheduled deferments based on the activity plan and expected production. In addition to making short-term forecasts, the model can also be used to validate production enhancement activities before they are approved and implemented. In this way, the impact of these production enhancement activities can be assessed, not only for the single well, but also for the entire production system. Some of the expected benefits and value gains from this approach are - 1. Improved confidence/accuracy in the forecasts and effectiveness of proposed enhancements. 2. Systematic and streamlined process for short-term forecasting and validating proposed enhancements. 3. Additional information and increased confidence in estimates used to support cost of production enhancements. 4. Identification of the impact of planned short-term activities and production enhancements on the entire asset. 5. Capability to run "what-if" scenarios to improve the effectiveness of planned activities and enhancements. 6. Increased collaboration between different engineers, models and domains for better decision making. This novel approach modernizes perspective for short-term forecasting and reveals that an asset's true production potential can best be predicted using an integrated modeling approach.