SPE WA April Luncheon: Integrated Asset Modelling (IAM) for Improved Surveillance Capabilities and Sustained Overall Optimised Production

Integrated Asset Modelling (IAM) for Improved Surveillance Capabilities and Sustained Overall Optimised Production

Traditional approach to asset modelling couples 2 or 3 models at best; this methodology is not only prone to data transmission, data conversion errors but even use of incorrect data sets. As optimisation is achieved at each level, it almost always delivers less than a global-optimised solution. On the other hand, as an orchestrated solution, a fully integrated set of models from reservoir to economics aims providing operational and maintenance guidelines that are within the systems operating envelope (subsurface, gathering system and facility) and commercial constraints.

This solution is a single platform that can connect various models and inputs from other systems (e.g. equipment downtime due to maintenance or well test activities). Real-time data is processed and coupled with analytics to calibrate the models during stable production. Conversely, the models are used to re-train the analytics data as it encounters new operating conditions (e.g. water break-through, coning). This cross-calibration approach eliminates the need to calibrate the individual models.

This approach provides the following benefits:-

• Enables Engineering and Commercial Teams to focus on engineering and business decisions instead of building and calibrating models.
• Reduces forecast uncertainties by eliminating errors introduced through manual handling of data.
• Enables reservoir-to-economics optimisation while honouring reservoir, production, facility and economic constraints.
• Improves collaboration across disciplines.

While the integrated model approach offers good drivers to implement, there are some challenges to implementing this approach. First, integrated models require a multi-disciplinary team. Although it seems easy to have such a team, organisational structures present natural barriers to implement. Further, there are a lot of modelling tools available in the market, the choice of which is driven by several factors (best-of-breed, commercial incentives, familiarity, JVs selection), which changes over time. This makes it difficult to integrate the models. On the positive side, most vendors provides an Application Programming Interface (API) that enables third-party applications to control their models.

Having various models for different objectives is quite challenging. Often, organisation would have models for allocation different to the ones used for forecasting. However, enforcing a single model can introduce runtime issues when using the model for a different purpose. Needless to mention, that while it is possible to use a single set of models, it requires experience and technical expertise to qualify which components are material to the modelling objectives.

Presenter: Arman Vahedi, PetroAus Pty Ltd.

Arman has more than 15 years experience as a petroleum engineer. His experience in Digital Oil field implementation, production engineering and Integrated Asset Modelling sees him providing support for many major gas development projects in Australia and internationally. Prior to founding PETROAUS, Arman had worked for Chevron and Schlumberger.