Upstream reservoir engineers simulate downhole conditions using models which have a heavy dependency on data-driven, correlation-based analytics rather than rigorous first principles-based models. Correlation-based analytics tools are typically convenient, simple to set up, and quick to generate an answer. The consequence of this approach, however, is the intensive and continuous exercise of using spreadsheets in an attempt to update the correlations against reservoir history, before they lose their predictive validity.
Conversely, process and production engineers who are focused on topside facilities understand the value of first principles simulation models to design and operate the asset. They know that chemical and physical interactions and dependencies must be respected in order to draw safe and meaningful conclusions.
Therefore, while reservoir engineers are very comfortable playing within ranges of probabilities (P50, P75, P90 and P95), process and production engineers have an inherent and valid dislike of correlation-based analytics, due the lack of precision. As a result, major siloes exist between subsurface and topsides organizations. These two worlds don’t speak the same “language” yet the business’s success relies on their ability to interact and cooperate with each other. For example, in processes such as WAG (water alternating gas), injections that stimulate depleted wells in mature basins using recycles from the surface process, will require both reservoir and process/production engineers to collaborate.
In order to unlock trapped value, more precision is needed in subsurface reservoir engineering, involving unification of first principles and correlation-based analytics. Whilst this is the case, topside process/production engineers must relax their quest for ultra-precision within the small operating window of what’s happening today and look to the next 1-24 months.
When looking forward over this time frame, the operating window may be much wider than today’s operation requiring the rigor of simulation, but many possible futures may need to be explored requiring the convenience of correlation-based analytics. These two disjointed worlds need to come together using the ‘ensemble’ approach of an integrated asset model (IAM) that is neither reservoir-centric or facilities-centric. The IAM must strike the right balance of correlation-based analytics and first principles simulation to enable fit-for-purpose prediction over time with shared workflows embedded within it.
The compelling event for this unification of subsurface and topsides operations worlds is Digitalization. It is upstream’s ‘electric car’ moment. An IAM enables more effective economic evaluation and portfolio management decisions to be made, taking a much more holistic approach to deliver the required return on capital. This approach will create the major cultural change that will see a step change in upstream operator’s profitability.