Better predictions and fewer surprises
Too often, unexpected events occur over the life cycle of a reservoir that take an operator by surprise. Whether it is a sudden pressure drop, a water breakthrough or an infill well that finds poor reservoir properties, it is a clear indication that there were flaws in the model used to drill the producing and injection wells and to forecast production.
For the past 30 years reservoir modeling and production simulation has worked to build a single most probable model. Various methods were used to simplify or remove uncertainties without actually resolving them, creating liabilities in the future as evolving reservoir conditions can make once-insignificant uncertainties become very relevant. If a given model was matching data reasonably, little or no effort was made to see if alternate models may match as well or even better.
Resoptima offers a radically new approach to reduce risks and avoid costly surprises in the future. Ensemble-based modeling recognizes that a single model cannot represent the many possible ways a reservoir can be understood based on the existing static and dynamic data. Modern computational processes make it possible to represent all the possible uncertainties, many millions in most cases, and populate a large number of probable models that respect the existing data. Within this diversity of models, scenarios that include unlikely future occurrences are presented, and geologists and engineers can review them and assess them. As the reservoir progresses though its life cycle new data is acquired and incorporated in the Ensemble-based models.
The result: no more surprises! Being able to anticipate events that affect the continuity of production rates and take corrective action before the incidents occur is a vast improvement in operational efficiency. Using better predictions to plan infill wells that actually deliver increased production justifies the capital expenditure.